--- title: Mistral Large 4 (Le Chonk) is now Open Weight | daily.dev description: Mistral has open-sourced the weights of Mistral Large 4 (Le Chonk), a 1-trillion-parameter multimodal model first previewed earlier this month. Additional... canonical: https://daily.dev/posts/mistral-large-4-le-chonk-is-now-open-weight-ovqis0fzq twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Mistral Large 4 (Le Chonk) is now Open Weight | daily.dev og:description: Mistral has open-sourced the weights of Mistral Large 4 (Le Chonk), a 1-trillion-parameter multimodal model first previewed earlier this month. Additional... og:url: https://daily.dev/posts/mistral-large-4-le-chonk-is-now-open-weight-ovqis0fzq og:image: https://api.daily.dev/og/posts/OVqiS0FZq.png og:image:alt: Mistral Large 4 (Le Chonk) is now Open Weight og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Mistral Large 4 (Le Chonk) is now Open Weight **[Hacker News](https://daily.dev/sources/hn)** · 10 min read · 1 upvotes · 0 comments ## Summary Mistral has open-sourced the weights of Mistral Large 4 (Le Chonk), a 1-trillion-parameter multimodal model first previewed earlier this month. Additional reinforcement learning pushed it to lead open-weight coding benchmarks, scoring 19.7% on Cognition's FrontierCode 2.0 and 41% on Terminal-Bench 4.0. It ties GLM-5.3 on the Artificial Analysis Coding Agent Index at 48% while using 47% fewer tokens. It also scores 51% on the Cyber Index with a 96.6% refusal rate on malicious requests. Pricing is $0.70 per million input tokens and $2.10 per million output tokens, under a modified MIT license. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### What license does Mistral Large 4 use for its open weights? Mistral Large 4 is released under the Mistral Ecosystem Open-Weight license, a modified MIT license. It is free to use, modify, fine-tune, and commercialize, with one condition: businesses running a Model-as-a-Service offering must obtain a separate commercial license from Mistral before using it commercially. _Developers picking an open-weight model for production track licensing terms like this on daily.dev._ ### How does Mistral Large 4 compare to GLM-5.3 on coding benchmarks? Mistral Large 4 scores 48% on the Artificial Analysis Coding Agent Index, effectively tied with GLM-5.3, the leading open-weight model, but uses 47% fewer tokens per task on average. On Terminal-Bench 4.0 it improved 13 percentage points to 41%, taking the lead among open-weight models while cutting output tokens by 30%. _Anyone weighing coding agents for cost and performance follows comparisons like this on daily.dev._ ### What is the pricing for Mistral Large 4 API access? Mistral Large 4 is priced at $0.70 per million input tokens, $2.10 per million output tokens, and $0.07 per million cached input tokens. It is also available through Microsoft Foundry, NVIDIA-hosted endpoints, OpenRouter, and Hugging Face for self-hosted deployment with vLLM or SGLang. _Teams budgeting for LLM inference costs keep track of pricing changes like this on daily.dev._ ## Community take How the wider developer community reacted, aggregated from 1 discussion and 114 comments across hackernews (as of 2026-10-30). **TL;DR:** Most of the debate centers on whether 'open weight' is a misleading term given Mistral's commercial-use license restriction, while a separate thread of discussion questions whether the model is actually competitive against Chinese and US rivals despite its aggressive pricing. **Sentiment:** 20% positive · 45% mixed · 35% skeptical **The case for** - The price cut from preview pricing (down to $0.70/$2.10 per million tokens) makes it notably more interesting than before. - Some find it a capable, usable option for everyday coding tasks, especially for EU-based users wanting EU provenance. - Mistral adding third-party models like GLM and DeepSeek to its API has made it a solid overall provider for some business users. **The pushback** - The modified MIT license requires a separate commercial license for 'Model as a Service' businesses, which many argue makes 'open weight' a misleading label versus true open source. - Several benchmarks (e.g. Artificial Analysis Intelligence Index) suggest the model isn't cost/performance competitive against rivals. - The 96.6% refusal rate on malicious requests is seen as a weak or easily gamed metric with no corresponding data on false-positive refusals of legitimate requests. - Personal benchmarking and anecdotal testing suggest it lags behind top Chinese and US open-weight models. **By community** - hackernews (heated): A long, contentious debate over whether the license truly qualifies as 'open weight' dominates, alongside a separate skeptical thread about the model's real-world competitiveness. **Hottest debate:** Whether Mistral's license (which restricts commercial 'Model as a Service' use) can honestly be called 'open weight' or should instead be termed 'weights available'. **Open questions** - What is an authoritative definition of 'open weight' when no single body (OSI or otherwise) is universally recognized as the arbiter? - How does Mistral Large 4 actually perform on cost-adjusted intelligence benchmarks compared to competitors like GLM 5.3 and DeepSeek? - Why do malicious-request refusal rate statistics not come paired with false-positive refusal rates on legitimate requests? **Highlights** > Just because OpenAI ran roughshod over the broader software community's notion of "open" which once heavily implied free-as-in-software-not-beer, doesn't mean we need to continue this pattern. Many industries had "source available" without the word "open" for decades, and that was a broadly understood term. "Weights available" would be a reasonable analogue. For clarity, the Mistral model license is here: https://huggingface.co/mistralai/Mistral-Large-4-1T-A52B/raw... > 2. If the Licensee or any of its affiliates operates a Model as a Service business, the Licensee must enter into a separate commercial license with Mistral before using the Model or its derivative works for any commercial purpose. The Licensee may contact Mistral, using this form: https://mistral.ai/contact/, to request a commercial license. > "Model as a Service" means giving a third party access to the Model or its derivative works for inference or post-training by any means (for instance via API or hosted endpoints), in a manner that allows such third party to exercise meaningful control over the inputs, parameters, or training data. This does not include (a) end-user products with model capabilities solely embedded within specific features or harnesses, or (b) mere relaying of requests to models hosted by others. "Meaningful control over the inputs" is so ambiguous as to be nearly meaningless. Does a model merely summarizing a user's submitted support tickets, give that user meaningful control over the inputs? Don't get me wrong - I appreciate that Mistral needs to walk a fine line for its own sustainability, and that sustainability is a good thing! And I may just be an old person ranting at a cloud. But "open" used to mean something, back in my day! > — [btown on hackernews](https://news.ycombinator.com/item?id=50289907) > Ughh the overly positive and cheerful comments here from what is usually the most critical/pessimistic audience on the internet is a huge tell. If we cut through the political bias and wishful thinking for a second, here’s the truth: The model is not competitive. I would never waste my time using it for coding work, and I’m someone in the EU. Great effort, but keep at it. This just isn’t good enough. I’m sure you guys can make a boatload of money with regulatory capture and compliance games in the EU, but please don't give up trying to produce something thats actually competitive. > — [pembrook on hackernews · 3 comments](https://news.ycombinator.com/item?id=50290705) > "Cyber benchmarks, while achieving an average refusal rate of 96.6% on malicious cyber requests, the highest we measure among open models." I feel like stating the obvious here and hence like I'm missing something. Where is the statistic about not refusing the non malicious requests? I can achieve the same performance with refusing when random(1000) < 967. > — [3form on hackernews · 3 comments](https://news.ycombinator.com/item?id=50289898) > Look at the Intelligence Index vs. Cost per Task. Mistral 4 is not competitive. https://artificialanalysis.ai/#intelligence-efficiency-tabs > — [esafak on hackernews · 1 comments](https://news.ycombinator.com/item?id=50290064) > They slashed pricing, it's now nearly half vs the preview (Input: $0.7/M Tokens, Output: $2.1/M Tokens vs Input: $1.36/M Tokens, Output: $4.18/M Tokens). At the original pricing in my evals, Mistral Large 4 Preview was not competitive. With this price point and some improvements on top, this full release warrants a major reassessment. [0] https://docs.mistral.ai/inference/pricing > — [Topfi on hackernews · 4 comments](https://news.ycombinator.com/item?id=50289701) **Source threads** - [hackernews](https://news.ycombinator.com/item?id=50289418) · 382 points · 114 comments ## Similar posts on daily.dev - [Mistral Medium 3.5 is Live in Kilo Code](https://daily.dev/posts/mistral-medium-3-5-is-live-in-kilo-code-rvn0ny7h7) · Kilo Blog · 2 upvotes · 0 comments --- Tags: [#cyber](https://daily.dev/tags/cyber), [#open-source](https://daily.dev/tags/open-source), [#ai-agents](https://daily.dev/tags/ai-agents), [#llm](https://daily.dev/tags/llm), [#mistral-ai](https://daily.dev/tags/mistral-ai) [View this post on daily.dev](https://daily.dev/posts/mistral-large-4-le-chonk-is-now-open-weight-ovqis0fzq) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Mistral Large 4 (Le Chonk) is now Open Weight","url":"https://daily.dev/posts/mistral-large-4-le-chonk-is-now-open-weight-ovqis0fzq","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/mistral-large-4-le-chonk-is-now-open-weight-ovqis0fzq"},"datePublished":"2026-10-29T14:49:57.294Z","dateModified":"2026-10-30T08:15:54.347Z","description":"Mistral has open-sourced the weights of Mistral Large 4 (Le Chonk), a 1-trillion-parameter multimodal model first previewed earlier this month. 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