--- title: "Mistral Large 4: An Open-Weight Model With No Weights and No License (Yet)" date: 2026-10-12 tags: ["mistral","open-weight","benchmarks","models","licensing"] categories: ["Industry"] summary: "Mistral launched Large 4 on October 6 as a ~1T-parameter MoE at $1.36/$4.18 per million tokens, scoring 61.7% on DeepSWE v1.1 by its own measurement. The weights are promised for end of October with no license announced, and independent numbers put it below GLM-5.3 and Kimi K3." --- ![Mistral Large 4: An Open-Weight Model With No Weights and No License (Yet)](/images/mistral-large-4-open-weight-promise-no-weights-no-license.png) Mistral shipped **Large 4** on October 6, 2026, and called it an open-weight model. As of today, October 12, you can't download it. What exists is a preview API on Mistral Studio, a promise that "weights drop end of this month," and a model card that never names a license. That distinction matters if you plan to build on it. ## What's actually shipped According to [Mistral's announcement](https://mistral.ai/news/mistral-large-4), Large 4 is a natively multimodal mixture-of-experts model with about 1 trillion parameters, 52 billion active, merging instruction and reasoning modes. Outlets disagree on the exact size (MarkTechPost cites 1.05T), so treat the numbers as approximate until a checkpoint exists to count. Preview pricing is **$1.36 per million input tokens and $4.18 per million output tokens**, with cached input at $0.14. That sits well below Claude Sonnet 5.5's $2/$10 but far above DeepSeek-class pricing. Mistral also stresses European hosting: trained and served in its own EU datacenters, with a private-cloud or on-prem cyber offering for vetted partners. ## The benchmark picture Every headline number comes from Mistral: - DeepSWE v1.1: **61.7%** - Terminal-Bench 4.0: **28.3%** - SWE-Atlas-QnA: 59.4% - Cybench: 93%; vulnerability reproduce-and-patch: 82% - Blind human coding rating: 3.74/5, second behind Claude Opus 5 (4.22) The agentic coding runs were done privately, so nobody can reproduce them. The independent data is less flattering. Artificial Analysis measured Terminal-Bench 4.0 at **26.8%** (close to Mistral's figure, to be fair) but put Large 4 at **38 on its Intelligence Index**, behind GLM-5.3 (45) and Kimi K3 (44), per [secondary coverage](https://letsdatascience.com/blog/mistral-trillion-parameter-weights-this-month-license-blank). On the public DeepSWE board, closed models sit around 74% and the leading Chinese open models near 69%. Large 4 isn't listed yet. Credit where due: Mistral publishing its own human-eval loss to Opus 5 is more honest than most launch posts. But 28% on Terminal-Bench 4.0 against Opus 5.5's self-reported 66.4% tells you where this model sits for autonomous work. It isn't a Claude Code replacement; it's a sovereign-hosting option. ## The license is the real question Large 3 shipped under Apache 2.0. Large 4's page says only "open-weight." One outlet predicts a custom Mistral license; that is speculation, not a confirmed term. We've seen this movie recently: [Kimi K3's open-weights license surprise](/posts/kimi-k3-open-weights-license-surprise/) showed how much "open" can hide in the fine print. A custom license with revenue caps or use restrictions changes whether a model is a foundation or a liability. ## What to do with this 1. **Don't plan around it yet.** No weights, no license, no independent coding leaderboard entry. Re-evaluate after the end-of-October drop. 2. **Treat it as a data-residency play.** If EU-hosted inference is a hard requirement, the preview API is worth a pilot on non-critical workloads. 3. **Keep your specs model-agnostic.** This is the case for Spec-Driven Development: a well-written spec lets you swap Large 4, Sonnet 5.5, or Kimi K3 behind the same harness and measure the difference on your own repo instead of trusting launch tables. 4. **Keep the primary agent on Claude.** For long-horizon autonomous work, the gap on Terminal-Bench 4.0 is not close. I'll revisit when the weights and license land. Until then, "open-weight" is a roadmap item, not a property. ## Sources - [Mistral: Large 4 announcement](https://mistral.ai/news/mistral-large-4) - [LLM Gateway: new models this week](https://llmgateway.io/blog/new-ai-models-this-week-2026-10-11) - [Let's Data Science: weights this month, license blank](https://letsdatascience.com/blog/mistral-trillion-parameter-weights-this-month-license-blank) - [CNBC: Mistral unveils new AI model](https://www.cnbc.com/2026/10/06/mistral-ai-model-le-chonk.html) (search snippet only; page not readable)