[HN Gopher] Mistral Releases Deep Research, Voice, Projects in L...
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       Mistral Releases Deep Research, Voice, Projects in Le Chat
        
       Author : pember
       Score  : 381 points
       Date   : 2025-07-17 15:00 UTC (7 hours ago)
        
 (HTM) web link (mistral.ai)
 (TXT) w3m dump (mistral.ai)
        
       | jddj wrote:
       | The examples aren't great. The personal planning one for example
       | answers the prompt better without deep research than with (with
       | answers only the Visas point)
        
       | tdhz77 wrote:
       | I'm struggling with MRF. Model Release Fatigue. It's a syndrome
       | of constantly context switching new large models. Claude 4, gpt,
       | llama, Gemini 2.5, pro-mini, mistrial.
       | 
       | I fire off the ide switch the model and think oh great this is
       | better. I switch to something that worked before and man, this
       | sucks now.
       | 
       | Context switching llm, Model Release Fatigue
        
         | didibear wrote:
         | I believe perfs of previous versions are worse because
         | providers reallocate resources to newer versions. Also because
         | of training data cut-off to previous years. This is what
         | happened between claude sonnet 3.5 and 3.7.
         | 
         | Personally I only use Claude/Anthropic and ignore other
         | providers because I understand it the more. It's smart enough,
         | I rarely need the latest greatest.
        
         | emilsedgh wrote:
         | Why do you even follow? Just stick to one that works well for
         | you?
        
           | barbazoo wrote:
           | Totally, I feel like though you do have to pay some attention
           | for example in the context I'm working on, for the last
           | while, Gemini was our gold standard for code generation
           | whereas today, Claude subjectively produces the better
           | results. Sure you can stick to what worked abut then you're
           | missing the opportunity to be more productive or less busy,
           | whichever one you choose.
        
             | exe34 wrote:
             | I remember the days when I was looking for the perfect
             | note-taking system/setup - I never achieved anything with
             | it, I was too busy figuring out the best way to take notes.
        
               | barbazoo wrote:
               | Once we find the best way though...
        
           | tartoran wrote:
           | FOMO may be one of the reasons amongst others.
        
         | mrcwinn wrote:
         | What a luxury!
         | 
         | One way to avoid this: stick with one LLM and bet on the
         | company behind it (meaning, over time, they'll always have the
         | best offering). I've bet on OpenAI. Others can make different
         | conclusions.
        
           | tenuousemphasis wrote:
           | When the medicine is worse than the disease...
        
         | criemen wrote:
         | I totally get it. Due to my work, I mostly keep up with new
         | model releases, but the pace is not sustainable for
         | individuals, or the industry. I'm hoping that model releases
         | (and the entire development speed of the field) will slow down
         | over time, as LLMs mature and most low-hanging fruits in model
         | training have been picked. Are we there yet? Surely not.
        
         | bee_rider wrote:
         | A major reason I haven't really tried any of these things
         | (despite thinking they are vaguely neat). I think I will wait
         | until... 2026, second half, most likely. At least I'll check if
         | we have local models and hardware that can run them nicely, by
         | then.
         | 
         | Hats off to the folks who have decided to deal with the nascent
         | versions though.
        
           | nosianu wrote:
           | I have a modified tiered approach, that I adopted without
           | consciously thinking hard about it.
           | 
           | I use AI mostly for problems on my fringes. Things like
           | manipulating some Excel table somebody sent me with invoice
           | data from one of our suppliers and some moderately complex
           | question that they (pure business) don't know how to handle,
           | where simple formulas would not be sufficient and I would
           | have to start learning Power Query. I can tell the AI exactly
           | what I want in human language and don't have to learn a
           | system that I only use because people here use it to fill
           | holes not yet served by "real" software (databases, automated
           | EDI data exchange, and code that automates the business
           | processes). It works great, and it saves me hours on fringe
           | tasks that people outsource to me, but that I too don't
           | really want to deal with too much.
           | 
           | For example, I also don't check various vendors and models
           | against one another. I still stick to whatever the default is
           | from the first vendor I signed up with, and so far it worked
           | well enough. If I were to spend time checking vendors and
           | models, the knowledge would be outdated far too quickly for
           | my taste.
           | 
           | On the other hand, I don't use it for my core tasks yet. Too
           | much movement in this space, I would have to invest many
           | hours in how to integrate this new stuff when the "old"
           | software approach is more than sufficient, still more
           | reliable, and _vastly_ more economical (once implemented).
           | 
           | Same for coding. I ask AI on the fringes where I don't know
           | enough, but in the core that I'm sufficiently proficient with
           | I wait for a more stable AI world.
           | 
           | I don't solve complex sciency problems, I move business data
           | around. Many suppliers, many customers, different countries,
           | various EDI formats, everybody has slightly different data
           | and naming and procedures. For example, I have to deal with
           | one vendor wanting some share of pre-payment early in the
           | year, which I have to apply to thousands of invoices over the
           | year and track when we have to pay a number of hundreds or
           | thousands of invoices all with different payment conditions
           | and timings. If I were to ask the AI I would have to be so
           | super specific I may as well write the code.
           | 
           | But I love AI on the not-yet-automated edges. I'm starting to
           | show others how they can ask some AI, and many are surprised
           | how easy it is - when you have thee right task and know
           | exactly hat you have and what you want. My last colleague-
           | convert was someone already past retirement age (still
           | working on the business side). I think this is a good time to
           | gradually teach regular employees some small use cases to get
           | them interested, rather than some big top-down approach that
           | mostly creates more work and many people then rightly
           | question what the point is.
           | 
           | About politically-touched questions like whether I should
           | rather use an EU-made AI like the one this topic is about, or
           | use one from the already much of the software-world
           | dominating US vendor, I don't care at this point, because I'm
           | not yet creating any significant dependencies. I am glad to
           | see it happening though (as an EU country citizen).
        
             | bee_rider wrote:
             | > About politically-touched questions like whether I should
             | rather use an EU-made AI like the one this topic is about,
             | or use one from the already much of the software-world
             | dominating US vendor, I don't care at this point, because
             | I'm not yet creating any significant dependencies. I am
             | glad to see it happening though (as an EU country citizen).
             | 
             | Another nice thing about waiting a bit--one can see how
             | much (if any) the EU models get from paying the "do things
             | somewhat ethically" price. I suspect it won't be much of a
             | penalty.
        
           | Nezteb wrote:
           | Depending on the definition of "nicely", FWIW I currently run
           | Ollama sever [1] + Qwen Coder models [2] with decent success
           | compared to the big hosted models. Granted, I don't utilize
           | most "agentic" features and still mostly use chat-based
           | interactions.
           | 
           | The server is basically just my Windows gaming PC, and the
           | client is my editor on a macOS laptop.
           | 
           | Most of this effort is so that I can prepare for the arrival
           | of that mythical second half of 2026!
           | 
           | [1] https://github.com/ollama/ollama/blob/main/docs/faq.md#ho
           | w-d...
           | 
           | [2] https://huggingface.co/collections/Qwen/qwen25-coder-66ea
           | a22...
        
             | QRY wrote:
             | Thanks for sharing your setup! I'm also very interested in
             | running AI locally. In which contexts are you experiencing
             | decent success? eg debugging, boilerplate, or some other
             | task?
        
               | bogzz wrote:
               | I'm running qwen via ollama on my M4 Max 14 inch with the
               | OpenWebUI interface, it's silly easy to set up.
               | 
               | Not useful though, I just like the idea of having so much
               | compressed knowledge on my machine in just 20gb. In fact
               | I disabled all Siri features cause they're dogshit.
        
             | Kostic wrote:
             | Agentic editing is really nice. If on VSCode, Cline works
             | well with Ollama.
        
           | randomNumber7 wrote:
           | It is completely unreasonable to buy the hardware to run a
           | local model and only use it 1% of the time. It will be
           | unreasonable in 2026 and probably very long after that.
           | 
           | Maybe s.th. like a collective that buys the gpu's together
           | and then uses them without leaking data can work.
        
           | Uehreka wrote:
           | When ChatGPT, then Llama, then Alpaca came out in rapid
           | succession, I decided to hold off a year before diving in.
           | This was definitely the right choice at the time, it's
           | becoming less-the-right-choice all the time.
           | 
           | In particular it's important to get past the whole need-to-
           | self-host thing. Like, I used to be holding out for when this
           | stuff would plateau, but that keeps not happening, and the
           | things we're starting to be able to build in 2025 now that we
           | have fairly capable models like Claude 4 are super exciting.
           | 
           | If you just want locally runnable commodity "boring
           | technology that just works" stuff, sure, cool, keep waiting.
           | If you're interested in hacking on interesting new technology
           | (glances at the title of the site) now is an excellent time
           | to do so.
        
         | reilly3000 wrote:
         | Not to invalidate your feelings of fatigue, but I'm sure glad
         | that there are a lot of choices in the marketplace, and that
         | they are innovating at a decent clip. If you're committed to
         | always be using the best of all options you're in for a wild
         | ride, but it beats stagnation and monopoly.
        
           | ivape wrote:
           | We're also headed into a world where there will be very few
           | open weight models coming out (Meta going closed source, not
           | releasing Behemoth). This era of constant model releases may
           | be over before it even started. Gratitude definitely needs to
           | be echoed.
        
             | echelon wrote:
             | If China stays open, then the rest of the world will build
             | on open. I'm frankly shocked that a domestic player isn't
             | doing this.
             | 
             | Fine tuning will work for niche business use cases better
             | than promises of AGI.
        
               | seszett wrote:
               | > _If China stays open, then the rest of the world will
               | build on open_
               | 
               | I was listening to a Taiwanese news channel earlier today
               | and although I wasn't paying much attention, I remember
               | hearing about how Chinese AIs are biased towards Chinese
               | political ideas and that some programme to create a more
               | Taiwanese-aligned AI was being put in place.
               | 
               | I wouldn't be surprised if just for this reason, at least
               | a few different open models kept being released, because
               | even if they don't directly bring in money, several
               | actors care more about spreading or defending their ideas
               | and IAs are perfect for that.
        
               | kakapo5672 wrote:
               | It's curious that China is carrying the open banner
               | nowadays. Why is that?
               | 
               | One theory is that they believe the real endpoint value
               | will be embodied AIs (i.e. robots), where they think
               | they'll hold a long-term competitive advantage. The
               | models themselves will become commoditized, under the
               | pressure of the open-source models.
        
             | randomNumber7 wrote:
             | I don't agree with that. I didn't expect we ever get open
             | weight models close to the current state of the art, yet
             | china delivered some real burners.
        
         | sunaookami wrote:
         | You only need Claude and GPT. Everything else is not worth your
         | time.
        
         | vouaobrasil wrote:
         | An alternative: don't use LLMs. Focus on the enjoyment of
         | coding, not on becoming more efficient. Because the lion's
         | share of the gains from increased efficiency are mainly going
         | to the CEOs.
        
           | wahnfrieden wrote:
           | This is HN, we are not all wage workers here
           | 
           | For wage workers, not learning the latest productivity tools
           | will result in job loss. By the time it is expected of your
           | role, if you have not learned already, you won't be given the
           | leniency to catch up on company time. There is no impactful
           | resistance to this through individual protest, only by
           | organizing your peers in industry
        
           | freedomben wrote:
           | This might be good short term advice, but in the medium and
           | long term I think devs who don't use any AI will start to be
           | much slower at delivery than devs who do. I'm alreay seeing
           | it IRL (and I'm not a fan of AI coding, so this sucks for me)
        
             | ivape wrote:
             | Slower in initial delivery maybe, but the maintenance and
             | debugging of production applications requires intimate
             | knowledge of the code base usually. The amount of code AI
             | writes will require AI itself to manage it since no human
             | would inundate themselves with that much code. Will it be
             | faster even so? We simply won't know because those vibe
             | coded apps have just entered production. The horror stories
             | can't be written yet because the horror is ongoing.
             | 
             | I'm big on AI, but vibe coding is such a fuck around and
             | find out situation.
        
               | jdiff wrote:
               | Plenty of small FAFO stories circulate already. There
               | will certainly be more. Lots of demonstration code out
               | there in the training data meant only for illustrative
               | purposes, and all too often vibe coding overlooks the
               | rock bottom basics of security.
        
               | freedomben wrote:
               | Oh yeah, I totally agree. Vibe coding is not (anytime
               | soon at least) going to be a thing.
               | 
               | But using AI tools for things like completing simple
               | functions (co-pilot) or asking questions about a codebase
               | can still be huge time savers. I've also had really good
               | success with having AI generate me basic scripts that
               | would have taken 45 minutes of work, but it gets me a
               | working script in 3. It's not the revolution that's been
               | promised, but it definitely makes me faster even though I
               | don't like it
        
             | jdiff wrote:
             | Good news for you then, this idea is less and less born out
             | by the data. The productivity and efficiency gains aren't
             | there, so there's no reason to be compelled by the spectre
             | of obsolescence. The models may be getting better, but it
             | doesn't seem to be actually changing much for programming.
             | The illusion of busywork, perhaps, is swallowing up the
             | decreased mental bandwidth in constant context switching.
        
         | sva_ wrote:
         | All the competition is great to me. I'm using premium models
         | all the time and barely spent a few euro on them, as there's
         | always some offers that are almost free if you look around.
        
         | zamadatix wrote:
         | Much like with new computer hardware, announcements are
         | constant but they rarely entice me to drop one thing and switch
         | to another. If an average user picked a top 3 option last year
         | and stuck with them through now you didn't really miss out on
         | all that much, even if your particular choice wasn't the
         | absolute latest and greatest the entire time.
        
           | wahnfrieden wrote:
           | Sticking with one year old models would mean no o3 which is a
           | huge loss for dev work
        
       | htrp wrote:
       | is anyone doing online reviews of model performance ? (I know
       | artificial analysis does some work on infrastructure and has an
       | intelligence index)
        
         | reckless wrote:
         | The aggregate picture only tells you so much.
         | 
         | Sites like simonwillison.net/2025/jul/ and channels like
         | https://www.youtube.com/@aiexplained-official also cover new
         | model releases pretty quickly for some "out of the box
         | thinking/reasoning" evaluations.
         | 
         | For me and my usage I can really only tell if I start using the
         | new model for tasks I actually use them for.
         | 
         | My personal benchmark andrew.ginns.uk/merbench has full code
         | and data on GitHub if you want a staring point!
        
         | Eupolemos wrote:
         | Yeah, GosuCoder is interesting.
         | 
         | https://youtu.be/064VC2gFIGY?si=l0LVtUttVrbiBZ3K
        
       | behnamoh wrote:
       | At this point, the entire AI industry seems to just copy OpenAI
       | for the most part. I cannot help but notice that we have the same
       | services just offered by different companies. The amount of
       | innovation in this build is not that high actually.
        
         | scotty79 wrote:
         | That's what a healthy competition in the free market looks
         | like. Things like Apple that "stay innovative" for decades are
         | aberration caused by monopolistic gatekeeping.
        
           | behnamoh wrote:
           | > Things like Apple are aberration.
           | 
           | This used to be a good example of innovation that is hard to
           | copy. But it doesn't apply anymore for two reasons:
           | 
           | 1. Apple went from being an agile, pro-developers, creative
           | company to an Oracle-style old-board milking-cow company; not
           | much innovation is happening at Apple anymore.
           | 
           | 2. To their surprise, much of what they call "innovative" is
           | actually pretty easy to replicate on other platforms. It took
           | 4 hours for Flutter folks to re-create Liquid Glass...
        
             | overfeed wrote:
             | > This used to be a good example of innovation that is hard
             | to copy.
             | 
             | Steve Jobs did say they "patented the hell out of [the
             | iPhone]" and went about saber-rattling, then came the
             | patent wars which proved that Apple also rely on innovation
             | by others, and that patent workarounds would still result
             | in competitive products, and things calmed down afterwards.
        
           | croes wrote:
           | They often copied others but because Apple is more popular
           | they got the fame for ,,their" innovation.
        
         | klntsky wrote:
         | They are not the same service. There is A LOT of difference
         | between offerings if you actually use the models for daily
         | tasks like coding.
        
           | lossolo wrote:
           | It really depends on what you're working on and what was
           | included in the training data of the model you used. From a
           | model architecture point of view, they're basically all the
           | same, the main difference lies in the training data.
        
         | croes wrote:
         | It's basically everywhere the same technology. Maybe a
         | difference in training data and computing power.
        
         | cubefox wrote:
         | > At this point, the entire AI industry seems to just copy
         | OpenAI for the most part
         | 
         | Well, OpenAI copied the Deep Research feature from Google. They
         | even used the same name (as does Mistral).
        
           | cowpig wrote:
           | Weird that you're being downvoted for stating a fact.
           | 
           | All of the major labs are innovating and copying one another.
           | 
           | Anthropic has all of the other labs trying to come up with an
           | "agentic" protocol of their own. They also seem to be way
           | ahead on interpretability research
           | 
           | Deepseek came up with multi-headed latent attention, and
           | publishing an open-source model that's huge and SOTA.
           | 
           | Deepmind's way ahead on world models
           | 
           | ...
        
         | mirekrusin wrote:
         | Whole world is now building stuff on top of `f(input: string):
         | string` function - they're going to be similar.
        
       | Aissen wrote:
       | The Voxtral release seemed interesting, because it brought back
       | competitive open source audio transcription. I wonder if it was
       | necessary to have an LLM backbone (vs a pure-function model)
       | though, but the approach is interesting.
        
         | nomad_horse wrote:
         | > brought back competitive open source audio transcription
         | 
         | Bear in mind that there are a lot of very strong _open_ STT
         | models that Mistral's press-release didn't bother to compare
         | to, making impression they are the best new open thing since
         | Whisper. Here is an open benchmark:
         | https://huggingface.co/spaces/hf-audio/open_asr_leaderboard .
         | The strongest model Mistral compared to is Scribe, ranked 10
         | here.
         | 
         | This benchmark is for English, but many of those models are
         | multilingual (eg https://huggingface.co/nvidia/canary-1b-flash
         | )
        
           | espadrine wrote:
           | The best model there is 2.5B parameters. I can believe that a
           | model 10x bigger is somewhat better.
           | 
           | One element of comparison is OpenAI Whisper v3, which
           | achieves 7.44 WER on the ASR leaderboard, and shows up as
           | ~8.3 WER on FLEURS in the Voxtral announcement[0]. If FLEURS
           | has +1 WER on average compared to ASR, it would imply that
           | Voxtral does have a lead on ASR.
           | 
           | [0]: https://mistral.ai/news/voxtral
        
             | nomad_horse wrote:
             | There are larger models in there, a 8B and a 6B. By this
             | logic they should be above 2B model, yet we don't see this.
             | That's why we have open standard benchmarks, to measure
             | this directly - not hypothesize by the models' sizes or do
             | some cross-dataset arithmetics.
             | 
             | Also note that, Voxtral's capacity is not necessarily all
             | devoted to speech, since it "Retains the text understanding
             | capabilities of its language model backbone"
        
           | jiehong wrote:
           | I just can't find dictation apps for Mac using those models
           | except for open whisper.
           | 
           | IBM's granite models seems multilingual and well ranked, but
           | can't find any app using it.
           | 
           | Anybody aware of a dictation app using one of those "better"
           | models?
        
       | M4v3R wrote:
       | I think they've buried the lede with their image editing
       | capabilities, which seem to be very good! OpenAI's model will
       | change the whole image while editing messing up details in
       | unrelated areas. This seems to perfectly preserve parts of the
       | image unrelated to your query and selectively apply the edits,
       | which is very impressive! The only downside is the output
       | resolution (the resulting image is 1184px wide even though the
       | input image was much larger).
       | 
       | For a quick test I've uploaded a photo of my home office and
       | asked the following prompt: "Retouch this photo to fix the gray
       | panels at the bottom that are slightly ripped, make them look
       | brand new"
       | 
       | Input image (rescaled): https://i.imgur.com/t0WCKAu.jpeg
       | 
       | Output image: https://i.imgur.com/xb99lmC.png
       | 
       | I think it did a fantastic job. The output image quality is ever
       | so slightly worse than the original but that's something they'll
       | improve with time I'm sure.
        
         | sync wrote:
         | FYI, your Input and output URLs are the same (I thought I was
         | crazy for a sec trying to spot the differences)
        
           | M4v3R wrote:
           | whoops, sorry about that, fixed
        
         | pablonaj wrote:
         | They are using Flux Kontext from Black Forest Labs, fantastic
         | model.
        
           | koakuma-chan wrote:
           | So Mistral is just hosting a Flux model?
        
             | Squarex wrote:
             | Yes, but it's great that they are both made by european
             | companies.
        
         | bakkoting wrote:
         | Kontext is probably better at this specific task, if that's
         | what Mistral is using. Certainly faster and cheaper. But:
         | 
         | OpenAI just yesterday added the ability to do higher fidelity
         | image edits with their model [1], though I'm not sure if the
         | functionality is only in the API or if their chat UI will make
         | use of this feature too. Same prompt and input image: [2]
         | 
         | [1] https://x.com/OpenAIDevs/status/1945538534884135132
         | 
         | [2] https://i.imgur.com/w5Q0UQm.png
        
         | joshcartme wrote:
         | Wow, that really is amazing!
         | 
         | I couldn't help but notice that you can still see the shadows
         | of the rips in the fixed version. I wonder how hard it would be
         | to get those fixed as well.
        
         | shaky-carrousel wrote:
         | It messed up the titles of the books.
        
           | Lerc wrote:
           | That might be autoencoder loss rather than the image
           | generation itself. It's hard to tell without doing a round-
           | trip using just the autoencoder without any generation, but
           | it kind-of has the look of that sort of loss.
        
       | BrunoWinck wrote:
       | I need that,
        
       | BrunoWinck wrote:
       | I needed that. Now I have it :)
        
       | bangaladore wrote:
       | If you haven't tried OpenAI's deep research feature, you are
       | missing out. I'm not sure of any good alternatives, I've tried
       | Google's, and I'm not impressed.
       | 
       | There is a lot of value to say engineers doing tradeoff studies
       | using these tools as a huge head start.
        
         | ankit219 wrote:
         | Try one from Kimi 2 as well. I was surprised how good it turned
         | out to be.
        
         | crmd wrote:
         | It's been invaluable to me for market research related to
         | starting a business. It's like having a bright early career new
         | hire research assistant/product manager "on staff" to
         | collaborate with.
        
         | criemen wrote:
         | Perplexities isn't bad? Although I lack the OpenAI subscription
         | to compare.
        
         | freedomben wrote:
         | I've gotten pretty different results from OpenAI and Gemini,
         | though it's hard to say one is better/worse than the other.
         | Just different
        
         | ripley12 wrote:
         | Anthropic's Research is pretty good; I'd say on par with
         | OpenAI.
         | 
         | Agreed about Google, accuracy is a little better on the paid
         | version but the reports are still frustrating to read through.
         | They're incredibly verbose, like an undergrad padding a report
         | to get to a certain word count.
        
           | the_duke wrote:
           | That's Gemini Pro now in general. The initial preview was
           | pretty good, but the newer iterations are incredibly verbose.
           | 
           | "Be terse" is a mandatory part of the prompt now.
           | 
           | Either it's to increase token counts so they can charge more,
           | or to show better usage growth metrics internally or for
           | shareholders, or just some odd effects of fine tuning /
           | system prompt ... who knows.
        
       | chickenzzzzu wrote:
       | Back in my day, La Chat was a rapper, not a wrapper.
        
         | dust42 wrote:
         | Actually Le Chat is french for the (male) cat. Also 'Le Chat'
         | is a well known laundry detergent (of german origin - Henkel
         | company). The headline 'Le Chat takes a deep dive' means 'the
         | cat takes a deep dive'. As there is a cooperation with (german)
         | Black Forest Labs, this is all pretty funny for a french
         | speaking person. 'La Chatte' is the female cat. And also
         | colloquial for female private parts.
        
       | rawgabbit wrote:
       | I have been a heavy user of ChatGPT. I guess I should try out
       | LeChat. What can I expect? Are they basically the same tool with
       | slight differences?
        
       | trilogic wrote:
       | Finally EU is waking up. Proud of it. I am switching asap my
       | Openai contract finishes to Mistral. We got to support EU, Viva
       | La France.
        
       | lostmsu wrote:
       | Is Voice available on the free tier? I signed up just to try it,
       | but all I see is the dictation mode.
        
       | maelito wrote:
       | Can we expect Voxtral in the Futo Android keyboard ?
        
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