Mistral

Mistral Small 4 ships as an Apache 2.0 open-weight model with 119B total parameters and only 6.5B active per token through a 128-expert Mixture-of-Experts architecture. It handles reasoning, vision, and coding through a single endpoint, replaces three separate Mistral models, and is priced at $0.40/M input tokens through the Mistral API. Mistral Small 4 Review 2026: The EU-Compliant Open-Weight Model Mistral Small 4 scores 28 on the AA Intelligence Index and outperforms GPT-OSS 120B on LiveCodeBench while generating outputs that are 20% shorter — a combination that matters directly for production cost. Released by Mistral AI, a Paris-based company, the model inherits EU data residency by default: API traffic stays inside the European Union without any additional configuration, which makes it the first credible option for GDPR-sensitive workloads that do not want to negotiate Standard Contractual Clauses with US cloud providers. Beyond compliance, the Apache 2.0 license removes all royalty and usage restrictions, meaning the same weights can be fine-tuned, redistributed, and embedded in commercial products without legal overhead. The model replaces Magistral for reasoning tasks, Pixtral for vision tasks, and Devstral for code tasks. It achieves 40% lower end-to-end latency and 3x higher throughput compared to Mistral Small 3, which makes it viable not just as a quality upgrade but as a direct cost reduction for teams already running Mistral in production. The model ID on the Mistral API is mistral-small-2603 and weights are available on Hugging Face at 242 GB in BF16. ...

Magistral is Mistral AI’s first reasoning model family, released in 2025. The 24B open-weight Small variant runs on a single RTX 4090 or 32 GB MacBook, scores 70.7% on AIME-2024 pass@1, and is licensed Apache 2.0 — making it the most capable locally-deployable reasoning model available today. What Is Magistral? Mistral’s First Reasoning Model Explained Magistral is the reasoning model family from Mistral AI, a French AI company founded in 2023. It comes in two variants: Magistral Small, a 24-billion-parameter open-weight model released under Apache 2.0, and Magistral Medium, a larger mixture-of-experts (MoE) model available exclusively via API. Unlike most reasoning models that distill knowledge from proprietary giants like GPT-4o or Claude, Magistral was trained using Reinforcement Learning with Verifiable Rewards (RLVR) applied directly to the Mistral Medium 3 checkpoint — no distillation from other reasoning models was involved. This means its reasoning chain is genuinely self-developed, not borrowed. Magistral Medium scores 73.6% on AIME-2024 pass@1 — a 50% relative improvement over the base Mistral Medium 3 — and reaches 90% with majority voting at 64 samples. Magistral supports multilingual chain-of-thought reasoning across English, French, Spanish, German, Italian, Arabic, Russian, and Simplified Chinese, making it the first openly verifiable multilingual reasoning model from a European AI lab. ...

Devstral Small 2 is a 24B-parameter coding model from Mistral AI that scores 68% on SWE-bench Verified and runs on a single 24GB GPU or a Mac M-series with 32GB unified memory — making it the first cloud-grade coding agent most developers can realistically self-host. This guide covers three setup paths: Ollama for beginners, vLLM for production teams, and llama.cpp for CPU-only or low-VRAM machines. What Is Devstral Small 2? Devstral Small 2 is Mistral AI’s open-weight coding specialist, released December 10, 2025 under the Apache 2.0 license. With 24 billion parameters and a 256K-token context window, it achieves 68.0% on SWE-bench Verified — a real-world benchmark measuring a model’s ability to resolve open GitHub issues autonomously. That puts it on par with models up to five times its parameter count, including closed-source proprietary systems. Because it ships under Apache 2.0, you can run it locally with no API fees, no data leaving your machine, and no usage restrictions — even in commercial projects. The model is fine-tuned specifically on agentic coding workflows: reading multi-file codebases, writing patches, running tool calls, and self-correcting from test failures. Devstral Small 2 outperforms Qwen 3 Coder Flash (30B) despite being a smaller model, and its larger sibling Devstral 2 (123B) hits 72.2%, compared to Claude Sonnet 4.5’s 77.2% — at up to 7x lower cost per coding task. For teams or individuals who need a capable coding agent without cloud dependency, Devstral Small 2 is the most practical choice available today. ...

Devstral 2 is Mistral AI’s most capable open-weight coding model, achieving 72.2% on SWE-bench Verified — the highest score ever recorded by an open-source model at its parameter count. Released in late 2025 alongside the Mistral Vibe CLI, it costs $0.40 per million input tokens, making it up to 7x cheaper than Claude Sonnet for typical coding workloads. What Is Devstral 2? Overview of Mistral’s Latest Open-Source Coding Agent Devstral 2 is a 123-billion parameter open-weight large language model purpose-built for agentic software engineering tasks — it can autonomously navigate codebases, edit multiple files, run tools, and resolve GitHub issues end-to-end. Released by Mistral AI in December 2025, it achieves 72.2% on SWE-bench Verified (the industry-standard benchmark for autonomous bug-fixing), placing it at the frontier of all open-weight models and ahead of significantly larger competitors including DeepSeek V3.2 (672B) and Kimi K2 (1T). Unlike most frontier coding models, Devstral 2 is released under the Apache 2.0 license, meaning developers can download, self-host, fine-tune, and deploy it commercially without restriction. In human evaluations against DeepSeek V3.2, Devstral 2 wins 42.8% of coding tasks versus a 28.6% loss rate — a meaningful real-world advantage that SWE-bench alone doesn’t fully capture. The model supports a 256K-token context window, enabling comprehension of entire repositories in a single pass. For teams that need frontier-grade coding intelligence without proprietary lock-in, Devstral 2 is the clearest option available in 2026. ...