[HN Gopher] Mistral AI Releases Forge
___________________________________________________________________
Mistral AI Releases Forge
Author : pember
Score : 695 points
Date : 2026-03-17 21:04 UTC (1 days ago)
(HTM) web link (mistral.ai)
(TXT) w3m dump (mistral.ai)
| roxolotl wrote:
| Mistral has been releasing some cool stuff. Definitively behind
| on frontier models but they are working a different angle. Was
| just talking at work about how hard model training is for a small
| company so we'd probably never do it. But with tools like this,
| and the new unsloth release, training feels more in reach.
| csunoser wrote:
| Huh. I initially thought this is just another finetuning end
| point. But apparently they are partnering up with customers on
| the pretraining side as well. But RL as well? Jeez RL env are
| really hard to get right. Best wishes I guess.
| mark_l_watson wrote:
| I am rooting for Mistral with their different approach: not
| really competing on the largest and advanced models, instead
| doing custom engineering for customers and generally serving the
| needs of EU customers.
| w4yai wrote:
| Go Mistral !
| jerrygoyal wrote:
| their ocr model is goated
| stavros wrote:
| Better than Qwen? I guess the best overall is Gemini, right?
| ph4rsikal wrote:
| Gemini? Not anywhere near.
| thefounder wrote:
| Gemini is the worst
| stavros wrote:
| Really? This article was gushing about it:
|
| https://generativehistory.substack.com/p/gemini-3-solves-
| han...
|
| Which one's the best?
| SyneRyder wrote:
| Did they make significant improvements in OCR 3? The quality
| I was getting from Mistral OCR 2 was nowhere near as good as
| what I could get from just sending the same files to Claude
| Sonnet via an API call.
|
| I have been finding Voxtral useful though.
| SyneRyder wrote:
| Too late to edit / update my comment, but I finally tried
| Mistral OCR 3 tonight on a PDF file I had. Results were
| good, and fast... but I actually got better quality output
| from sending it to Haiku 4.5 instead.
|
| In particular, Haiku 4.5 detected some footers that were on
| every page and moved them to be the footer at the end of
| the entire document instead, so that the document read more
| fluently.
|
| I imagine Mistral OCR 3 might have an edge on speed &
| pricing, but in my low volume / prioritizing-quality case,
| seems that Claude is still better than Mistral.
| oakpond wrote:
| probably yes. considering that even some of their non-ocr
| models can recognize my shitty handwritten math
| doctorpangloss wrote:
| first, there was .ai
|
| next, it sounds like it's going to be .eu
|
| but what about ai.eu
| fnord123 wrote:
| > but what about ai.eu
|
| oh, .. why?
| ChrisGreenHeur wrote:
| I found it to be the best model if you want to talk about
| topics philosophical. It has no problems going deep and
| technical while other models tend to be afraid of overshooting
| the comprehension of the reader.
| nicman23 wrote:
| also offering support for local deployments
| bsjshshsb wrote:
| Id training or FT > context? Anyone have experience.
|
| Is it possible to retrain daily or hourly as info changes?
| rorylawless wrote:
| The fine tuning endpoint is deprecated according to the API docs.
| Is this the replacement?
|
| https://docs.mistral.ai/api/endpoint/deprecated/fine-tuning
| aavci wrote:
| Interesting to see. I thought they were promoting fine tuning
| dmix wrote:
| This is definitely the smart path for making $$ in AI. I noticed
| MongoDB is also going into this market with
| https://www.voyageai.com/ targeting business RAG applications and
| offering consulting for company-specific models.
| andai wrote:
| They mention pretraining too, which surprises me. I thought that
| was prohibitively expensive?
|
| It's feasible for small models but, I thought small models were
| not reliable for factual information?
| simsla wrote:
| Typical stages of training for these models are:
|
| Foundational:
|
| - Pretraining - Mid/post-training (SFT) - RLHF or alignment
| post-training (RL)
|
| And sometimes...
|
| - Some more customer-specific fine-tuning.
|
| Note that any supervised fine-tuning following the Pretraining
| stage is just swapping the dataset and maybe tweaking some of
| the optimiser settings. Presumably they're talking about this
| kind of pre-RL fine-tuning instead of post-RL fine-tuning, and
| not about swapping out the Pretraining stage entirely.
| ryeguy_24 wrote:
| How many proprietary use cases truly need pre-training or even
| fine-tuning as opposed to RAG approach? And at what point does it
| make sense to pre-train/fine tune? Curious.
| baby wrote:
| RAG is dead
| charcircuit wrote:
| Using tools and skills to retrieve data or files is anything
| but dead.
| nathanappere wrote:
| I think people just mean "using vector databases to enable
| RAG".
| menaerus wrote:
| Even that doesn't make sense. Why would you not build a
| vector database to complement your RAG engine?
| charcircuit wrote:
| For coding use cases you may want a way to search for
| symbols themselves or do a plain text exact match for the
| name of a symbol to find the relevant documents to
| include. There is more to searching than building a basic
| similarity search.
| menaerus wrote:
| Sorry but who mentioned coding as a use-case? My comment
| was general and not specific to the coding use-case, and
| I don't understand where did you get the idea from that I
| am arguing that building a similarity search engine would
| be a substitute to the symbol-search engine or that
| symbol-search is inferior to the similarity-search?
| Please don't put words into my mouth. My question was
| genuine without making any presumptions.
|
| Even with the coding use-case you would still likely want
| to build a similarity search engine because searching
| through plain symbols isn't enough to build a contextual
| understanding of higher-level concepts in the code.
| charcircuit wrote:
| I mentioned coding as a use case in my comment you
| replied to. You were asking for an example for when one
| wouldn't use vector search and I provided one. I did not
| say similarity search would be a substitute. I said that
| for the coding case you do not need it.
|
| >you would still likely want to build a similarity search
| engine
|
| In practice tools like Claude Code, Codex, Gemini, Kimi
| Code, etc are getting away with searching for code with
| grep / find and understanding code by loading a
| sufficient amount of code into the context window. It is
| sufficient to understand higher level concepts in the
| code. The extra complexity of maintaining vector database
| top of this is not free and requires extra complexity.
| CharlesW wrote:
| And yet your blog says you think NFTs are alive. Curious.
|
| But seriously, RAG/retrieval is thriving. It'll be part of
| the mix alongside long context, reranking, and tool-based
| context assembly for the forseeable future.
| strongly-typed wrote:
| Wait, what does NFTs have to do with RAG?
| LoganDark wrote:
| Nothing, I think they're just pointing out a seeming lack
| of awareness of what really is or isn't dead.
| panarky wrote:
| I, for one, find NFT-shilling to be a strong signal that
| I should downgrade my trust in everything else a person
| says.
| elicash wrote:
| I have no interest in anything crypto, but they are making
| a proposal about NFTs tied to AI (LLMs and verifiable
| machine learning) so they can make ownership decisions.
|
| So it'd be alive in the making decisions sense, not in a
| "the technology is thriving" sense.
| nl wrote:
| I don't think RAG is dead, and I don't think NFTs have any
| use and think that they are completely dead.
|
| But the OP's blog is more about ZK than about NFTs, and
| crypto is the only place funding work on ZK. It's kind of a
| devil's bargain, but I've taken crypto money to work on
| privacy preserving tech before and would again.
| prophesi wrote:
| Not OP, but...
|
| > Of course you would have to set a temperature of 0 to
| prevent abuse from the operator, and also assume that an
| operator has access to the pre-prompt
|
| Doesn't the fact that LLM's are still non-deterministic
| with a 0 temperature render all of this moot? And why was I
| compelled to read a random blog post on the unsolved issue
| of validating natural language? It's a SQL injection except
| without a predetermined syntax to validate against, and
| thus a NP problem we've yet to solve.
| WesleyJohnson wrote:
| The issue I had with RAG when I tried building our own
| internal chat/knowledge bot was pulling in the relevant
| knowledge before sending to the LLM. Domain questions like
| "What is Cat Block B?" are common and, for a human, provide
| all the context that is needed for someone to answer within
| our org. But vectorizing that and then finding matching
| knowledge produced so many false positives. I tried to
| circumvent that by adding custom weighting based on
| keywords, source (Confluence, Teams, Email), but it just
| seemed unreliable. This was probably a year ago and,
| admittedly, I was diving in head first without truly
| understanding RAG end to end.
|
| Being able to just train a model on all of our domain
| knowledge would, I imagine, produce much better results.
| bigyabai wrote:
| In what, X's hype circles? Embeddings are used in production
| constantly.
| loeg wrote:
| Is it??
| Shitty-kitty wrote:
| rag basically gives the llm a bunch of documents to search thru
| for the answer. What it doesn't do is make the algorithm any
| better. pre-training and fine-tunning improve the llm abaility
| to reason about your task.
| mirekrusin wrote:
| You can fine tune small, very fast and cheap to run specialized
| models ie. to react to logs, tool use and domain knowledge,
| possibly removing network llm comms altogether etc.
| troyvit wrote:
| I'm thinking stuff like this:
|
| https://denverite.com/2026/03/12/ai-recycling-facility-comme...
|
| You could take a model like the one referenced in the article,
| retool it with Forge for oh I don't know, compost, and use it
| to flag batches that contain too much paper for instance.
|
| These kinds of applications would work across industries,
| basically anywhere where you have a documented process and can
| stand to have automated oversight.
| aavci wrote:
| How does this compare to fine tuning?
| Otterly99 wrote:
| It seems to me that it is broadly the same thing, except they
| give you the resources to do it and expert knowledge.
| hermit_dev wrote:
| The future of AI is specialization, not just achieving benevolent
| knowledge as fast as we can at the expense of everything and
| everyone along the way. I appreciate and applaud this approach. I
| am looking into a similar product myself. Good stuff.
| reverius42 wrote:
| Ironically that was also the past of AI. In 2016 it was all
| about specialized models (not just training data, everything
| including architecture and model class/type) for specific tasks
| and that's the way things had been for a long time.
|
| Are you suggesting that it's an aberration that from ~2019 to
| ~2026 the AI field has been working on general intelligence (I
| assume this is what you mean by "achieving benevolent
| knowledge")?
|
| Personally I think it's remarkable how much a simple
| transformer model can do when scaled up in size. LLMs are an
| incredible feat of generalization. I don't see why the
| trajectory should change back towards specialization now.
| holoduke wrote:
| I don't think that's true. Nothing points to specialized LLMs
| being better. General purpose LLMs are just much more useful in
| daily work.
| hermit_dev wrote:
| To be more specific, I think the future is local and
| specialized. IBM among others thought the same way with their
| giant mainframe centralized computers and the original way
| people would utilize software in the 70s. It's an interesting
| parallel to today's cloud if you think about it. It's just
| not scalable from a resource (hardware), energy, and cost
| perspective. I think we're living a unique time, but it's
| going to change. Without continued massive funding and a
| pivot to sustainable, things will (and should) change.
|
| Don't get me wrong, general intelligence will always be
| important and should be a part of specialist models to a
| degree for understanding, but it doesn't make sense to use an
| 800B+ parameter model to help write an email or do research
| on company trends. Hell, look at what China has been able to
| do. Qwen 3.5 9B, exceeds Claude 3.5 Haiku and nears Sonnet
| 3.5 levels. The 27B variation of Qwen 3.5 is superior to both
| in many ways and even rivals newer models. There is obviously
| an inherit lag behind, but we will gradually see a shift as
| these models become more capable.
|
| Right now we are chasing 1-2% improvements at the cost of
| billions. Local are already absurdly capable (more and more
| by the day - same with cloud ofcourse) and smarter than most
| people in specific areas. To do most jobs, can we honestly
| say it requires a PhD or higher level understanding to
| perform? We're chasing something that is becoming more and
| more not needed from a general day to day perspective. AGI is
| outstanding, but not practical (at least today). I think
| we'll get there anyway at our current trajectory (though
| dangerous), but I suspect things will shift.
| upghost wrote:
| > Pre-training allows organizations to build domain-aware models
| by learning from large internal datasets.
|
| > Post-training methods allow teams to refine model behavior for
| specific tasks and environments.
|
| How do you suppose this works? They say "pretraining" but I'm
| certain that the amount of clean data available in proper dataset
| format is not nearly enough to make a "foundation model". Do you
| suppose what they are calling "pretraining" is actually SFT and
| then "post-training" is ... more SFT?
|
| There's no way they mean "start from scratch". Maybe they do
| something like generate a heckin bunch of synthetic data seeded
| from company data using one of their SOA models -- which is
| basically equivalent to low resolution distillation, I would
| imagine. Hmm.
| stingraycharles wrote:
| I can imagine that, as usual, you start with a few examples and
| then instruct an LLM to synthesize more examples out of that,
| and train using that. Sounds horrible, but actually works
| fairly well in practice.
| anon373839 wrote:
| I think they are referring to "continued pretraining".
| mirekrusin wrote:
| Probably marketing speak for full fine-tuning vs PEFT/LoRA.
| gunalx wrote:
| Probably just means SFT fine-tuning a base model, vs
| behavioural dpo and/or SFT fine-tuning a instruction model.
| lelanthran wrote:
| I would guess:
|
| Pre-training: refining the weights in an existing model using
| more training data.
|
| Post-training: Adding some training data to the prompt (RAG,
| basically).
| qntty wrote:
| Pre-training mean exposing an already-trained model to more raw
| text like PDF extracts etc (aka continued pre-training). You
| wouldn't be starting from scratch, but it's still pre-training
| because the objective is just next token prediction of the text
| you expose it to.
|
| Post-training means everything else: SFT, DPO, RL, etc.
| Anything that involves things like prompt/response pairs,
| reward models, or benefits from human feedback of any kind.
| losvedir wrote:
| Er, then what is the "already trained" model? I thought pre-
| training was the gradient descent through the internet part
| of building foundational models.
| ogou wrote:
| Don't sleep on Mistral. Highly underrated as a general service
| LLM. Cheaper, too. Their emphasis on bespoke modelling over
| generalized megaliths will pay off. There are all kinds of
| specialized datasets and restricted access stores that can
| benefit from their approach. Especially in highly regulated EU.
|
| Not everyone is obsessed with code generation. There is a whole
| world out there.
| haraldooo wrote:
| I agree. Just started using it. Can you give some examples of
| fields you maybe even prefer Mistral?
| isodev wrote:
| Indeed, but even for coding use cases, Vibe is more of a
| focused "refactor/ write this function" aid than "write me an
| app" and it can work locally. For me that's a lot more valuable
| as an accelerator to my workflow where the developer stays in
| control and fully involved in the process.
| srivmo wrote:
| > Their emphasis on bespoke modelling over generalized
| megaliths will pay off.
|
| Isn't the entire deal with LLMs that they are trained as
| megaliths? How can bespoke modelling overcome the treasure
| trove of knowledge that megaliths can generically bring in,
| even in bespoke scenarios?
| lelanthran wrote:
| > Isn't the entire deal with LLMs that they are trained as
| megaliths? How can bespoke modelling overcome the treasure
| trove of knowledge that megaliths can generically bring in,
| even in bespoke scenarios?
|
| Think of it as a base model (the megalith) which then has the
| weights adjusted towards a specific use-case (SAP, for
| example).
| wodenokoto wrote:
| ChatGPT is already a small agent that receives your message
| and decides which agent needs to respond. Within those,
| agents can have sub agents (like when it does research).
|
| When generating images most services will have a small agent
| that rewrites your request and hands it off to the generative
| image model.
|
| So from the treasure trove point of view, optimized agents
| have their place. From companies building pipelines, they
| also have their place.
| TeMPOraL wrote:
| > _ChatGPT is already a small agent that receives your
| message and decides which agent needs to respond._
|
| Right, but this was done to value-optimize the product,
| i.e. try to always give you the shittiest (cheapest) model
| you can bear, because otherwise people would always choose
| the smartest (most expensive) model for any query.
|
| Taking away the model choice from the user introduces a lot
| of ways to cut down costs, but one thing it does _not_ do
| is make the product give users better /more reliable
| answers.
| Stromgren wrote:
| Agreed. I've used their platform to train smaller, specialized
| models. Something I could have done in Codelab or some other
| tool, but their platform allows me to just upload a training
| set and as soon as it finishes I have a hosted model available
| at an endpoint. It obviously has some constraints compared to
| running the training yourself, but it also opens up the
| opportunity to way more people.
| umeridrisi wrote:
| Is this the best Grok alternative?
| spiderfarmer wrote:
| Any model is.
| grosswait wrote:
| This sounds like an ideology based reply. Grok is
| underrated and I think has a better chance of long term
| success than most. The current growth strategy means (for
| me) their chat harness is not up to par for serious work.
|
| Their API is consistently among the most used on
| OpenRouter. While I can't vouch for it myself, I think this
| is a decent proxy for capability. You can definitely see
| glimmers of greatness in their chat interface, it just
| feels like the system prompts are focused on something that
| doesn't interest me.
| butILoveLife wrote:
| Grok is not SOTA, but its so obviously better than
| Mistral. Mistral is just some European patriotism or
| something.
|
| Grok is nice for asking morally gray questions. ChatGPT
| will lie in these cases.
| Duwensatzaj wrote:
| What lies have you seen? ChatGPT is the most censored
| one, but I've only seen rejections, not lies.
|
| My other complaint is that ChatGPT ends every response
| with a teaser to ask more questions.
| butILoveLife wrote:
| Ask game theory questions with real humans where its best
| to defect.
| spiderfarmer wrote:
| > Grok is nice for asking morally gray questions. ChatGPT
| will lie in these cases.
|
| Are you really that oblivious to the painfully cringy
| manipulation tactics by the man who partied at Epstein's
| island?
| https://www.theguardian.com/technology/2025/nov/21/elon-
| musk...
| spiderfarmer wrote:
| Yes, since it's not American, it will be the de-facto choice
| for most big European companies.
| jstummbillig wrote:
| Why would that be? Most big EU companies use ms teams or
| google workspace, for example.
| schubidubiduba wrote:
| They use those because the decision to use them was made
| years ago. Things have changed since then
| utopiah wrote:
| I want to believe... but I also need proofs of that
| "trend", any reference I could read on please?
| AdamN wrote:
| It's definitely a topic of conversation in Reddit, etc...
| However I agree that the push to reduce US dependence by
| EU companies (and countries) is hampered by the fact that
| US stuff is already embedded (Microsoft but also Google,
| etc...) and that many of these companies are
| transnational anyway (very few European companies are
| solely inside the EU) and finally and most importantly
| just about every company will choose the option that does
| the job best for the right price (sovereignty is a
| distant second for most decision makers).
| spiderfarmer wrote:
| While few companies announce this publicly, I know from
| personal experience with corporate clients that many
| companies are preparing for Trump to use Big Tech as a
| bargaining chip.
|
| And they should. Because the US is not behaving
| rationally at all.
|
| https://nltimes.nl/2026/02/10/rabobank-ing-abn-amro-seek-
| eur...
|
| https://www.theregister.com/2025/11/13/gartner_cio_cloud_
| sov...
|
| https://www.independent.co.uk/news/world/europe/europe-
| zoom-...
|
| https://www.theglobeandmail.com/business/commentary/artic
| le-...
|
| https://sherwood.news/tech/europe-wants-to-break-up-with-
| us-...
| drstewart wrote:
| >While few companies announce this publicly, I know from
| personal experience with corporate clients
|
| Well I have even more personal experience that
| contradicts yours, and this isn't true at all. Everyone
| uses Claude / Gemini / OpenAI. Mistral isn't even on the
| table.
| input_sh wrote:
| Come on, compared to Google Workspace / Microsoft's
| whatever-it's-called-these-days, the cost of switching
| from one LLM provider to another is pretty much zero.
|
| Having _an_ option at the back of your mind is all it
| takes right now, until push comes to shove of course.
| spiderfarmer wrote:
| Just a sample: https://mistral.ai/customers
|
| And you can Google for "We use Mistral" to find thousands
| of usecases by startups and other companies.
| hermanzegerman wrote:
| Multiple Government organisations ditching Microsoft?
| Including entire German states?
|
| My University also migrated to OpenExchange
| utopiah wrote:
| That's the public sector. I can also give examples of
| schools in Denmark, cities in France, education system in
| France, cities in Spain too, but they said "big EU
| companies".
| sunaookami wrote:
| No they haven't. Every company just buys ChatGPT
| Enterprise.
| hk__2 wrote:
| Not at all. We continue taking that decision today.
| drstewart wrote:
| No they haven't.
|
| Proof: Most big EU companies use Claude or Gemini or
| OpenAI, not Mistral. That choice was made recently.
|
| Things have changed in the loud echo chambers of the
| internet, maybe (but not really, since people were saying
| that EU data sovereignty was happening any time now since
| 2016).
| sisve wrote:
| My _feeling_ is that a lot of EU/European politicians has
| talked a lot more about the need to be independent from
| the US after Trump threaten Greenland. At least in the
| nordic countries. Not only concerning data & privacy, but
| defence, communications, space etc. All areas. The wheel
| has started to turn. You will not see it if you look
| around. But in 10 years time, maybe more, Europe will
| have stopped depending on the US. And that will hit US
| hard. We pay a lot of money in services to the US.
| Aerroon wrote:
| The politicians can talk, but they needed to set up an
| environment that would've let a European company have a
| decent shot at competing with the best AI models. But
| they didn't. Should've thought of that before being proud
| of setting up those strict tech regulations.
| sisve wrote:
| That is not how EU does things. If you want no regulation
| and access to capital you should go to the US.
|
| AI will take over a lot and the biggest AI company will
| be in US and China. But there will be room for Europe
| also on the top 10 list.
|
| But there will be an environment that is creating
| sovereignty from US much more the before. We have learned
| our lesson
| saulapremium wrote:
| I consult for various companies and have definitely seen
| a trend. It's not quite the rupture that some expect but
| clearly not nothing either. Until very recently, the risk
| assessment of using US providers was considered very
| hypothetical. Today it still doesn't feel imminent, but
| it _does_ feel very real.
|
| Of course, it will be slow and painful and Europeans will
| need to use their own services for them to grow and
| mature.
| sofixa wrote:
| > Proof: Most big EU companies use Claude or Gemini or
| OpenAI, not Mistral. That choice was made recently.
|
| IS a statement with no supporting facts considered
| "proof"? Just the public list of Mistral customers
| (https://mistral.ai/customers) is proof alone that quite
| a few big EU companies are _not_ in fact using Open AI or
| Claude or Gemini _at the strategic level_.
|
| Contrast with Antrhopic's Europe based customers, the
| majority of which are small companies (only big one I can
| identify from a skim is L'Oreal): https://claude.com/cust
| omers?f80ce999_sort_date=desc&f80ce99...
|
| Or OpenAI's customers, of which the only big European
| ones I can spot are Scania and Philips:
| https://openai.com/stories/
|
| Note: I'm talking about strategic enterprise AI
| deployments for the company or at least a division, not
| individual developers being allowed to use Claude Code
| etc. The moat and the money will be in the former, not
| latter.
| jstummbillig wrote:
| I don't think big business is genuinely planning for a
| world where US tech becomes completely unavailable.
| sofixa wrote:
| Not entirely, but putting more eggs in that basket would
| certainly be considered lack of planning. Why increase
| your risk even further when everyone has seen how
| volatile things can get quickly?
| spiderfarmer wrote:
| 2 years ago I would have agreed with you, but after
| Greenland the vibe is very different. And it's not like
| the situation is improving.
| lelanthran wrote:
| I also think that this is the best approach for businesses
| wanting to adopt AI to automate, streamline, etc their
| business.
|
| The problem they have is that this is not a moat - their
| approach is easily reproducible.
|
| If they can pull ahead in having the most number of pre-trained
| models (one for this ERP, one for that CRM, etc) and then being
| able to close sales to companies using these products and sell
| them on post-trained (give us your specific ERP customisations
| and we'll give you access to a model that is tailored to your
| business), then _THAT_ is a moat.
|
| But they need to do this without fanfare. Just close sales, and
| keep closing, basically. After all, even if other AI providers
| copy the process, the moat would already have been established
| for Mistral.
| Lapel2742 wrote:
| > The problem they have is that this is not a moat - their
| approach is easily reproducible.
|
| My 2ct: Currently the moat may be that they are not US-
| American which is not reproducible by any of the US
| alternatives.
| drstewart wrote:
| This moat doesn't seem to be much of a moat considering a
| non-US model doesn't even crack the top 5 by usage - except
| DeepSeek, which would be a strange choice for Europeans
| looking for data sovereignty.
| Lapel2742 wrote:
| > considering a non-US model doesn't even crack the top 5
| by usage
|
| How do you measure "usage" in an enterprise/commercial
| context where no data on usage is available to you? I
| don't expect Mistral AI to make it's money on OpenRouter.
| lelanthran wrote:
| > This moat doesn't seem to be much of a moat considering
| a non-US model doesn't even crack the top 5 by usage -
| except DeepSeek, which would be a strange choice for
| Europeans looking for data sovereignty.
|
| Hang on, where are you getting the numbers from? I looked
| and I couldn't find _any_ numbers on enterprises who
| opened their wallets for custom-trained models.
|
| I looked, and because I believed that it might be a good
| business opportunity to explore, I did spend a bit of
| time trying to find numbers. I came away with the feeling
| that the winner in the AI space is going to be whoever
| successfully whitelabels their offering.
|
| Right now that is Mistral, I think.
| hermanzegerman wrote:
| They offer self-hosted models for big corporate
| customers. I would also expect those serious about the
| security of their data to use that option. So you would
| never get the usage of those customers
| rvnx wrote:
| If you are a company based in Europe it is silly to give
| your data security and privacy to a company based in
| Europe.
|
| If you are in Iran, you don't want to give your data to
| your government.
|
| If you are in France, you don't want to give your data to
| your government.
|
| etc
|
| If you are in France, and you host your e-mails in a
| datacenter in Hong-Kong, well good luck for the
| authorities to get it.
|
| If you host it in "secure France", on the paper you will
| have more privacy and laws behind you, but in reality you
| are jumping into the mouth of the shark.
|
| This is why governments are promoting: "yes yes, host
| here don't worry, we will protect you"
| sofixa wrote:
| This flat out isn't true. Police forces / investigative
| authorities have been collaborating with one another
| since 1923: https://en.wikipedia.org/wiki/Interpol . We
| have tons of examples of this working for the digital
| world as well (like Proton complying with Swiss legal
| orders at the behest of non-Swiss police forces for
| illegal activities in other countries).
|
| The trick is to host your data in a country with a strong
| rule of law, and avoid illegal / geopolitical lines. If
| you're an American company hosting stuff in Russia, you
| can bet the GRU/SVR would be very happy to abuse it. If
| you're running a torrent site in Ukraine, you can bet the
| US would be very happy to claim extraterritorial magic
| jurisdiction and get you extradited from Poland.
|
| As a French company, you're already beholden to French
| law and French legal decisions. "Data is hosted in Hong
| Kong" doesn't matter in the slightest, it only exposes
| you to more risk.
| bob001 wrote:
| > well good luck for the authorities to get it.
|
| "We want your data on X, here;'s a warrant."
|
| "No."
|
| "You are now under arrest for contempt of court."
|
| People have some oddly silly views on what government can
| and can't do to people living in their territories.
|
| And companies really really don't care if the government
| has their data.
|
| > host your e-mails in a datacenter in Hong-Kong
|
| Now China has it, gives it a competitor in China and your
| market share drops like a stone. Congrats! Great choice!
| hermanzegerman wrote:
| It's not about government but about trade secrets...
| lelanthran wrote:
| > My 2ct: Currently the moat may be that they are not US-
| American which is not reproducible by any of the US
| alternatives.
|
| I hope you are right (I am in the process of finalising a
| product and one of the top-5 selling points contains
| "outside the jurisdiction of the US"), but in my
| experience, companies only pay lip service to ethics unless
| it hits their bottom line.
| Lapel2742 wrote:
| > but in my experience, companies only pay lip service to
| ethics unless it hits their bottom line.
|
| Sure, Mistral AI is certainly not the market leader and
| probably never will be but we're not talking about being
| a market leader but about having a moat.
|
| I instantly believe you when you tell me that many
| companies do not care. On the other hand there are
| companies that do. At least partially: ASML, Stellantis,
| AXA, BNP Paribas, the French ministry of defense,
| Helsing, SNCF, ... are all Mistral AI customers.
| soco wrote:
| Mistral is still hosted on US providers, their EU centers
| are only in planning. Data access aside, if AWS or Azure
| (or Cloudflare) are ordered to pull the plug, it's still
| goodbye Mistral. Unless you use a third party hoster that
| is, or do it yourself of course - already possible.
| amonith wrote:
| To extend on that a little bit: they use data centers
| located in EU, but owned by US cloud providers. They can
| still pull the plug ofc, so it's only a small difference,
| but still
| Bombthecat wrote:
| Meh, I feel like we are in the "cloud is bad phase" all
| over again.
|
| Companies will use US ai models without issues in a few
| years.
| erispoe wrote:
| Except the evidence today rather points to SOTA model +
| harness than fine tuned models.
| lelanthran wrote:
| > Except the evidence today rather points to SOTA model +
| harness than fine tuned models.
|
| I have not seen that, actually. I still see most companies
| who want to jump into AI for the business sort of try RAG,
| but more often they just buy Chat accounts for their users.
|
| The only place that harnesses appear to be used is in
| software development, but most companies aren't doing that
| either.
| butILoveLife wrote:
| If you couldn't use the words Europe to describe why you'd
| chose Mistral, you'd have no good reasons to choose Mistral.
|
| Its just not good. Its bottom floor for LLMs.
| danelski wrote:
| > Its bottom floor for LLMs.
|
| What? That's just demonstrably false. The market doesn't
| consist of 5 providers.
| butILoveLife wrote:
| You know about LMarena? I just looked it up, Mistral is
| number 59 on the list.
|
| Free Chinese models are better than it.
| danelski wrote:
| That's one of the possible benchmarks, not the only one.
| Being 59th there, on a list enriched with every variation
| of _Model_Name X.Y (March 2025 Preview) Pro-Thinking_ ,
| translates to being in the top 10 providers worldwide
| which is a very interesting mark of failure considering
| that coincidentally they're also number 1 from their
| economic area. If you don't know why the last part is
| important, go read some news.
| Forgeties79 wrote:
| I use a pretty lightweight local Mistral model in LM studio for
| both creative and technical writing/iterating and it's
| fantastic.
| Bombthecat wrote:
| The companies I work want onprem models, and no Chinese ones.
| Does mistral support onprem? ( For a price)
| supernes wrote:
| > Code agents are becoming the primary users of developer tools,
| so we built Forge for them first, not
|
| ... for humans.
| dash2 wrote:
| I think it's interesting what this approach suggests about who
| will profit from AI. I'm sceptical that having huge numbers of
| GPUs is a moat. After all, real humans - even geniuses - are
| trained on much much less data than the whole Internet. But
| proprietary and specialised data could very well be a moat. It's
| hard to train a scientist/lawyer/analyst without reading a lot of
| science/law/finance. Companies' proprietary data might encode a
| great deal of irreplaceable knowledge. Seems as if Mistral is
| taking this bet.
| copirate wrote:
| > After all, real humans - even geniuses - are trained on much
| much less data than the whole Internet.
|
| It's certainly different data, but one could argue that real
| humans have been trained on 3.5 billion years of evolution
| data.
| speedgoose wrote:
| I was enthusiastic but it's "contact us" priced for now. I was
| expecting a classic cloud LLM forge with a public pricing.
| 0x457 wrote:
| This feels like something more hands-on rather than "here some
| tools to do this"
| zby wrote:
| My bet is that the solution to continuous learning is with
| external storage. There is a lot of talk about context
| engineering - but I have not seen anyone taking context as the
| main bottleneck and building a system around that. This would
| show that even context engineering is kind of wrong term -
| because context does not enter the llm in some mysterious way -
| it goes through prompt and the whole model of passing chat
| history back and forth is not the most efficient way of using the
| prompt limitation.
| Centigonal wrote:
| What do you mean when you say "external storage?"
| zby wrote:
| A knowledge base - something where the LLM knows how to find
| the knowledge it needs for a given task. I am working on this
| idea in https://zby.github.io/commonplace/
| ithkuil wrote:
| A form of context engineering
| mhl47 wrote:
| "External Storage" whatever that is can not be the same as
| continous learning as it does not have the strong
| connections/capture the interdepencies of knowledge.
|
| That said I think we will see more efforts also on the business
| side to have models that can help you build a knowledge base in
| some kind of standardized way that the model is trained to
| read. Or synthesize some sort on instructions how to navigate
| your knowledge base.
|
| Currently e.g. Copilot tries to navigate a hot mess of a MS
| knowledge graph that is very different for each company. And
| due to its amnesia it has to repeat the discovery in every
| session. No wonder that does not work. We have to either
| standardize or store somewhere (model, instructions) how to
| find information efficiently.
| zby wrote:
| The key to make Copilot useful is to take the limited context
| problem seriously enough. There are many dimensions to it:
| https://zby.github.io/commonplace/notes/context-
| efficiency-i... and it should be the starting point for
| designing the systems that extensively use llms.
| andai wrote:
| Well, did you solve the problem of deciding what to
| remember? (And I suppose, how to retrieve it? i.e. LLM can
| retrieve info, but if it doesn't know about something
| because it hasn't been retrieved yet...)
| whatever1 wrote:
| I thought that for pretraining to work and reasoning to emerge
| you need internet scale data. How can forge achieve it with just
| internal company data (unless the said company is AT&T or
| something) ?
| jbverschoor wrote:
| ASML and ESA as clients means something. I dont expect to see the
| first name somewhere else on the logo list
| kioleanu wrote:
| I like Mistral, it hits the exact sweet spot between cost and my
| data staying in the EU, withouth a significant drop in quality,
| but man are their model naming conventions confusing af. They
| mention they have a model called Devstral 2, which is neither
| Codestral nor Devestral. I want to use it, but the api only lists
| devstral-2512, devstral-latest, devstral-medium-latest, devstral-
| medium-2507, devstral-small, devstral-small-2507.
|
| I think, devstral-latest _should_ be it, no? So I write to
| support and get an answer 12 hours later that says oh, no,
| devstral 2 is definetely called devstral 2 and then a page of
| instructions on how to set it up in Intellij... generated with
| AI. The screens it is refering to don 't exist and never did.
| Manfred wrote:
| I had the same experience. It's even more confusing when you
| want to create an API key because they are separated by
| product, maybe?
| kioleanu wrote:
| no, the key is actually universal, you can't choose a
| specific product
| lis wrote:
| It depends. The key for their vibe-cli is actually
| different. You need to get a separate key if you have a
| subscription and don't want to pay API usage prices.
| hermanzegerman wrote:
| That's the same everywhere. At least with the Chinese
| coding plans
| newswasboring wrote:
| I have a general impression they are not interested too much in
| individual devs and making it suite their workflow. They want
| to be a B2B company and deliver a custom workflow per company.
|
| Or it can just be a Google like problem where a big company one
| part doesn't talk to the other.
| kioleanu wrote:
| you might be correct. for example, they have an intellij
| plugin that allows integration without the AI Assistant, but
| it is only available for Enterprise customers
| soco wrote:
| But wouldn't winning devs be a neat helping point in winning
| b2b contacts? Or they think golf courts are enough for
| success? Okay they might be right here, but still they make
| it so confusing for no obvious reason.
| newswasboring wrote:
| To me it's obvious because the size of companies they are
| targeting (ASML being an obvious one). I think golf course
| marketing works well in the EU context when decisions are
| being made not purely on tech reasons.
| sofixa wrote:
| > I think golf course marketing works well in the EU
| context when decisions are being made not purely on tech
| reasons.
|
| It's not like b2b sales is more technical merit based,
| individual contributor led, elsewhere.
|
| It's always the same, depending on the field individual
| contributors can have some flexibility on picking tools
| (so a developer in a mid sized company would be able to
| pick whatever, an accountant probably would be more
| constrained, meanwhile a developer at a big bank would
| not have any choice). But for strategic software choices,
| that impact the whole company, where standardisation
| makes sense or is even mandatory to get actual value out
| of it, you need to sell to high level decision makers,
| not individual contributors. A CTO or a VP of X can
| decide to buy and mandate the implementation of something
| as impactful, workflow changing and potentially time and
| money saving as a company wide AI platform. A dev can't.
| wqaatwt wrote:
| > being made not purely on tech reasons.
|
| As if that's not true in the US (not just government
| contracts but VC in general as well)...
| MidnightRider39 wrote:
| In my experience devs rarely have anything to say in B2B
| contracts. At best they can recommend a solution to the
| decision maker, but in almost all deals i was a part of
| they didn't have any influence on the final decision. I
| wish it were otherwise but alas
| philipallstar wrote:
| Also EU protectionism itself might be enough.
| hermanzegerman wrote:
| Where is EU protectionist?
|
| I feel we are way less protectionist than most other
| Economic Regions. Including the USA, which are very
| protectionist but always claim otherwise
| philipallstar wrote:
| Well, if every big company gets a giant EU fine for, say,
| preinstalling a web browser in an OS, except for EU
| companies, that could make it easier for the EU
| companies.
| sofixa wrote:
| Every company would get fined for anticompetitive
| behaviour, regardless of where are based.
| wqaatwt wrote:
| Well yes, but because there are approximately zero EU
| tech companies that can be affected by these fines and
| regulations there is very little political pushback
| against them.
|
| In a certain sense it's a way for EU to clawback at least
| a small slice of all that money flowing to the US.
| sofixa wrote:
| https://www.edpb.europa.eu/news/national-
| news/2023/personali...
| hermanzegerman wrote:
| Why should there be pushback against antitrust measures?
|
| It's what keeps markets alive
| brabel wrote:
| Well different discussion, but look at the Mercosur
| agreement and all the opposition from farmers in the EU.
| They are extremely protectionist when it comes to
| agriculture, at least.
| hermanzegerman wrote:
| Yes the farmers are a very vocal and powerful minority.
|
| They get more than 50% of their income from subsidies,
| are quite well off, but always find a reason to complain.
|
| I was thinking more about stuff like "Buy
| American"-Regulations for public tenders. Stuff like that
| doesn't exist here
| prmoustache wrote:
| Well I can certainly understand them. Based on price tgey
| would not be able to compete and have half decent living
| wages so protectionism AND subsidies is a decent strategy
| to maintain local production which I feel allow a country
| / area to not lose a lever in international negociations.
| pembrook wrote:
| Apparently you aren't aware of the EU's deep regulatory
| protectionism and subsidies at both EU and country level.
| A small portion is legitimately about protecting
| consumers, but ultimately this stuff is all designed by
| and for EU industry.
|
| Basically all economic regions get highly protectionist
| when it comes to key areas like agriculture, banking,
| steel production, energy, automotive manufacturing, etc.
|
| On tariffs, the US is now higher, but tariffs are a tax
| that passes through overwhelmingly onto the consumer (by
| like 95%+). Given there's essentially no fully domestic
| US manufacturing supply chains and the US imports
| everything, it's a defacto VAT from the perspective of
| the consumer. The EU has VAT levels that are still much
| higher than the average US tariff level, which is a
| essentially a dampener on consumption.
| hermanzegerman wrote:
| But the VAT applies to all goods regardless where they
| are produced. So that's not a protectionist measure
| victorbjorklund wrote:
| Like American protectionism? Heck, America even prohibits
| its own companies to sell to the government if the
| president doesn't like them enough.
| lelanthran wrote:
| > But wouldn't winning devs be a neat helping point in
| winning b2b contacts?
|
| How? The largest providers that are trying to win devs are
| locked in a competition to get the devs to continue using
| the models _for free!_
|
| The best way to win B2B contracts is to solve the problems
| that plague business, not those that plague devs. The devs
| are fickle, have no stickiness and will jump providers to
| the next free provider, to self-hosted, etc.
|
| Selling to business using Mistral's approach is, I feel,
| just a good business plan.
|
| "Giving away some credits for free, then making a loss on
| subscribers" is an absolutely terrible business plan.
| R0m41nJosh wrote:
| As far as I understood the French president is pushing
| French most valuated companies to use Mistral. There can't
| be a more to down strategy :)
| IanCal wrote:
| I got really lost on their site, but to help a bit according to
| their model page
|
| devstral-2512 devstral-latest and devstral-medium-latest are
| all devstral 2 https://docs.mistral.ai/models/devstral-2-25-12
|
| labs-devstral-small-2512 and devstral-small-latest are devstral
| small 2
|
| devstral-medium-2507 is devstral 1.0
|
| and devstral-small-2507 is devstral small 1.1
| kioleanu wrote:
| wow, thank you, this is great. I was thinking they should
| have a page like this, but I couldn't find myself.
| butILoveLife wrote:
| >data staying in the EU
|
| This is really why Mistral has any support.
|
| The models are bottom barrel, but its the best Europe has...
|
| Although you could use Chinese models on European servers.
| Aldipower wrote:
| I cannot keep up with their products, model names and releases.
| What is what for? Their marketing texts do not make sense for me.
| Is there a nice overview somewhere?
|
| I am a simple stupid Le Chat user with a small mind and the
| Tredict MCP Server connected to it (to Le Chat, not my mind),
| which works ok-ish. :-)
| krinne wrote:
| I wasnt able to find a way to access this - is this something
| accessible only to enterprises ?
|
| Would love to take it for a spin, if that is even possible.
| thecopy wrote:
| Looks interesting. But how to explore or test or use? The product
| page (https://mistral.ai/products/forge) also does not contain
| anything useful. Just "Contact us"
|
| Dissapointing.
| burgerquizz wrote:
| can i use mistral to read my source code and teach it so i don't
| need to inject the whole doc every single time and consume token
| every single time?
| spacesh1psoda wrote:
| Go EU!
| todteera wrote:
| Interesting how Mistral is investing into training models for
| industry specific use cases. With the commoditization of
| intelligence by base models, they're probably looking to creating
| value from specialized verticals.
| jcmartinezdev wrote:
| Mistral is doing some really great stuff lately. Sure, it's hard
| to compete with OpenAI and Anthropic and their models, but they
| are taking up some interesting takes and designing their product
| in unique ways.
|
| I like a lot what they are doing and I'll be watching them a lot
| more closely. I'd love to work for them btw!
| apexalpha wrote:
| This looks good but how much money are we talking here? Are we
| 'retraining' an entire model but adding enterprise data to the
| public data set?
| tho23i42342397 wrote:
| Interesting. Does this actually scale though ? I've never seen
| enterprises which have "internal knowledge" in proper readable
| form - it's often in code, and more importantly in people who
| wrote them.
|
| I recall that even at Google - with its own search engine and so
| on - the best way to understand anything was to read code or to
| reach out to those who wrote them. I don't know how it works in
| places that work with the "real world" like ASML.
|
| Often the issue is not even about documentation - it's just that
| it's extremely hard to include all the nuances in text and still
| have it be readable (code-documentation comes to mind).
|
| Interestingly, I strongly feel that this also where LLMs (and
| some of our more textually-obsessed academics) fail.
| bob001 wrote:
| My sense is that it sounds amazing in theory to executives who
| have never had to themselves look at internal data. In reality
| the internal knowledge base is a mix of incomplete, inaccurate,
| self serving lies, out of date and so on. At worst, the data is
| explicitly biased to hide reality from executives so the AI
| will look extra good to executives. Of course, a business that
| makes all tactical decisions based on lies is not going to do
| well.
| dragochat wrote:
| where sample notebook/script? where github? where signup?
|
| ...learn a thing or two from NVIDIA or gtfo
| troyvit wrote:
| lol
|
| > Mistral AI has already partnered with world-leading
| organizations, like ASML, DSO National Laboratories Singapore,
| Ericsson, European Space Agency, Home Team Science and
| Technology Agency (HTX) Singapore, and Reply to train models on
| the proprietary data that powers their most complex systems and
| future-defining technologies.
|
| When you can actually represent somebody like the ESA get in
| touch with them. Otherwise, uh, gtfo.
| losvedir wrote:
| > _Forge enables enterprises to build models that internalize
| their domain knowledge. Organizations can train models on large
| volumes of internal documentation, codebases, structured data,
| and operational records. During training, the model learns the
| vocabulary, reasoning patterns, and constraints that define that
| environment._
|
| I'm probably really out of date at this point, but my impression
| was that fine tuning never really worked that well for knowledge
| acquisition, and that don't variety of RAG is the way to go here.
| Fine tuning can affect the "voice", but not really the knowledge.
| mikodin wrote:
| I was under this impression as well - I'd love to hear from
| someone who's deeper in the know about this!
| Havoc wrote:
| Good for them. Really hope they find market fit
| alansaber wrote:
| I find the mistral "middle" between small LMs /1T LMs compelling.
| Models that are sufficiently big to be performant but specialised
| for domains and tasks- this is what I assumed we'd always head
| towards.
| vincentbusch wrote:
| lol the AI-generated support reply about their own AI model is
| peak 2026
|
| the naming mess is wild though. i ran into similar confusion
| trying to set up mistral for a side project -- ended up just
| guessing which endpoint was the right one
___________________________________________________________________
(page generated 2026-03-18 23:01 UTC)