Mistral AI
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Mistral AI Launches La Plateforme: First API Endpoints in Early Access
Mistral AI opened beta access to its first developer platform, La Plateforme, offering three generative text endpoints (mistral-tiny, mistral-small, mistral-medium) and an embedding endpoint. Mistral-tiny serves Mistral 7B Instruct v0.2, mistral-small serves Mixtral 8x7B, and mistral-medium serves an unreleased prototype model scoring 8.6 on MT-Bench. The platform also introduces Mistral-embed with a 1024-dimension embedding model achieving 55.26 on MTEB. The API follows OpenAI-compatible chat interface specifications and is ramping toward general availability.
Mistral Launches Medium 3.5 (128B Open Weights), Remote Cloud Coding Agents in Vibe, and Work Mode in Le Chat
Mistral AI has released Mistral Medium 3.5, a 128B dense open-weights model with a 256k context window, configurable reasoning effort, and a vision encoder trained from scratch, scoring 77.6% on SWE-Bench Verified. Alongside the model, Mistral is launching remote cloud-based coding agents in its Vibe CLI and Le Chat interface, enabling async parallel coding sessions that run independently and notify users on completion. A new Work mode in Le Chat provides a multi-step agentic interface for cross-tool workflows including email, calendar, research, and issue tracking. Mistral Medium 3.5 replaces Devstral 2 as the default model in both Le Chat and the Vibe CLI, and is available for self-hosting on as few as four GPUs under a modified MIT license.
Mistral AI Launches Workflows: Enterprise AI Orchestration Layer in Public Preview
Mistral AI has released Workflows in public preview, an enterprise-grade orchestration layer integrated into its Studio platform that enables durable, observable, fault-tolerant AI pipeline execution in production. The system supports human-in-the-loop approvals via a single API call, full execution tracing with OpenTelemetry, and Python-based workflow authoring that publishes to Le Chat for non-developer triggering. Early enterprise customers including ASML, ABANCA, CMA-CGM, and La Banque Postale are already using it for cargo release automation, KYC compliance, and customer support triage. The product targets the gap between proof-of-concept AI pipelines and reliable production deployment.
Mistral Releases Voxtral TTS: 4B-Parameter Multilingual Text-to-Speech Model
Mistral AI has launched Voxtral TTS, its first text-to-speech model, built on a 4B-parameter transformer-based autoregressive flow-matching architecture derived from Ministral 3B. The model supports 9 languages with zero-shot voice adaptation from as little as 3 seconds of reference audio, achieving 70ms latency for typical inputs and a real-time factor of ~9.7x. Human evaluations claim superior naturalness compared to ElevenLabs Flash v2.5 and parity with ElevenLabs v3. The model is available via Mistral Studio and API, targeting enterprise voice agent workflows.
Mistral AI Launches Connectors in Studio: Built-in and Custom MCP Support with Direct Tool Calling
Mistral AI has released Connectors in Studio, enabling developers to integrate enterprise data sources into AI applications via reusable connectors built on the Model Context Protocol (MCP). The feature supports both built-in connectors (GitHub, web search) and custom MCP servers, accessible via Conversation API, Completions API, and Agent SDK. New capabilities include direct tool calling for deterministic invocation, human-in-the-loop approval flows for governance, and programmatic connector management. Connectors are centrally registered and shared across Mistral products including LeChat and AI Studio.
Mistral AI Introduces Forge: Enterprise Custom Model Training Platform
Mistral AI has launched Forge, a platform enabling enterprises to build frontier-grade AI models trained on their proprietary internal data, including documentation, codebases, and operational records. Forge supports the full model training lifecycle—pre-training, post-training, and reinforcement learning—across both dense and mixture-of-experts (MoE) architectures, with multimodal input support. The platform is designed to give enterprises strategic autonomy over their AI models and data, with early partners including ASML, Ericsson, the European Space Agency, and DSO National Laboratories Singapore. Forge is also agent-native, allowing autonomous agents like Mistral Vibe to orchestrate fine-tuning, hyperparameter search, and synthetic data generation via natural language.
Mistral Small 4: Unified Multimodal, Reasoning, and Coding MoE Model Released Under Apache 2.0
Mistral AI has released Mistral Small 4, a 119B-parameter Mixture-of-Experts model (6B active per token) that unifies capabilities previously split across Magistral (reasoning), Pixtral (multimodal), and Devstral (coding agents) into a single open-weights model. The model features a 256k context window, configurable reasoning effort via a `reasoning_effort` parameter, native text and image input support, and is released under Apache 2.0. Mistral claims 40% latency reduction and 3x throughput improvement over Mistral Small 3, with benchmark results showing competitive performance against GPT-OSS 120B and Qwen models while producing significantly shorter outputs. The release includes day-0 availability as an NVIDIA NIM and support across vLLM, llama.cpp, SGLang, and Transformers.
Mistral Releases Voxtral Transcribe 2: State-of-the-Art Speech-to-Text with Sub-200ms Realtime Model
Mistral AI has released Voxtral Transcribe 2, a family of two speech-to-text models: Voxtral Mini Transcribe V2 for batch transcription and Voxtral Realtime for live applications. Voxtral Realtime features a novel streaming architecture with configurable latency down to sub-200ms, a 4B parameter footprint suitable for edge deployment, and is released as open weights under Apache 2.0. Voxtral Mini Transcribe V2 claims state-of-the-art word error rate on FLEURS at $0.003/min, outperforming GPT-4o mini Transcribe, Gemini 2.5 Flash, AssemblyAI, and Deepgram Nova on accuracy benchmarks. Both models support 13 languages with speaker diarization, word-level timestamps, and context biasing.
Mistral AI joins NVIDIA Nemotron Coalition as founding member, co-developing open frontier models
Mistral AI has announced a strategic partnership with NVIDIA as a founding member of the newly formed NVIDIA Nemotron Coalition, a multi-lab initiative to advance open-source frontier foundation models. The collaboration will combine Mistral's model architectures, multimodal capabilities, and fine-tuning expertise with NVIDIA's DGX Cloud compute and synthetic data pipelines. The coalition's first deliverable is a base model trained on DGX Cloud that will underpin the upcoming NVIDIA Nemotron 4 model family, to be open-sourced. Coinciding with the announcement, Mistral is also releasing Mistral Small 4.
Pixtral Large: Mistral AI's 124B Open-Weights Multimodal Model
Mistral AI released Pixtral Large, a 124B open-weights multimodal model built on Mistral Large 2, featuring a 1B parameter vision encoder and 128K context window supporting at least 30 high-resolution images. The model claims state-of-the-art results on MathVista, DocVQA, and ChartQA, outperforming GPT-4o and Gemini-1.5 Pro on several benchmarks, and leads the LMSys Vision Leaderboard among open-weights models by ~50 ELO points. Simultaneously, Mistral updated its text model to Mistral Large 24.11 with improvements in long-context understanding, function calling, and RAG/agentic workflows. Note: the model has since been deprecated and replaced by newer Mistral vision models.
Mistral Vibe 2.0: Terminal-Native Coding Agent with Custom Subagents and Devstral 2
Mistral AI has released Mistral Vibe 2.0, a major upgrade to its terminal-native coding agent, powered by the new Devstral 2 model family. Key additions include custom subagents for specialized tasks, multi-choice clarifications before execution, slash-command skills for preconfigured workflows, and unified agent modes. The product is available on Le Chat Pro and Team plans with pay-as-you-go credits, while Devstral 2 moves to paid API access at $0.40/M input and $2.00/M output tokens. Enterprise add-ons include fine-tuning on internal DSLs, reinforcement learning with custom environments, and end-to-end codebase modernization.
Mistral Releases Mistral 3 Family: Mistral Large 3 (675B MoE) and Ministral 3 Series (3B–14B), All Apache 2.0
Mistral AI has announced Mistral 3, a family of open-weight models including Mistral Large 3 (41B active / 675B total sparse MoE) and three dense Ministral 3 edge models (3B, 8B, 14B), all released under Apache 2.0. Mistral Large 3 debuts at #2 on LMArena's OSS non-reasoning leaderboard, supports image understanding, and was trained on 3,000 NVIDIA H200 GPUs; a reasoning variant is forthcoming. The Ministral 3 series includes base, instruct, and reasoning variants with multimodal and multilingual capabilities, with the 14B reasoning model achieving 85% on AIME '25. The release involves deep co-optimization with NVIDIA (Blackwell/Hopper kernels, NVFP4 format), vLLM, and Red Hat, and is available across major cloud and inference platforms.
Mistral AI Launches Agents API with Built-in Connectors, MCP Tools, and Persistent Memory
Mistral AI has released a dedicated Agents API that extends beyond chat completion by providing built-in connectors for code execution, web search, image generation, and document retrieval, alongside support for Model Context Protocol (MCP) tools. The API features stateful conversation management with branching, streaming output, and multi-agent orchestration capabilities. Benchmark results show substantial web search augmentation gains: Mistral Large jumps from 23% to 75% on SimpleQA, and Mistral Medium from 22% to 82% with search enabled. The release targets enterprise-grade agentic workflows and is accompanied by cookbooks covering GitHub coding assistants, financial analysis, and travel planning use cases.
Mistral OCR 3: New Frontier in Document Processing Accuracy and Efficiency
Mistral AI has released Mistral OCR 3 (model ID: mistral-ocr-2512), claiming a 74% overall win rate over its predecessor Mistral OCR 2 across forms, scanned documents, complex tables, and handwriting. The model supports markdown output with HTML-based table reconstruction and is priced at $2 per 1,000 pages ($1 with Batch API). It now powers the Document AI Playground in Mistral AI Studio, offering a drag-and-drop interface for parsing PDFs and images into text or structured JSON.
Mistral Releases Devstral 2 (123B) and Devstral Small 2 (24B) Coding Models Plus Vibe CLI Agent
Mistral AI has released Devstral 2, a 123B-parameter open-weight coding model scoring 72.2% on SWE-bench Verified, and Devstral Small 2, a 24B model scoring 68.0% on the same benchmark and deployable on consumer hardware. Both models support a 256K context window and are permissively licensed (modified MIT and Apache 2.0 respectively). Mistral also launched Vibe CLI, an open-source terminal-based coding agent powered by Devstral that supports multi-file orchestration, natural language code editing, and IDE integration via Agent Communication Protocol. Devstral 2 is currently free via API with post-free pricing of $0.40/$2.00 per million tokens input/output.
Mistral AI Acquires Physics AI Startup Emmi AI to Expand Industrial AI Capabilities
Mistral AI has entered a definitive agreement to acquire Emmi AI, an Austria-based Physics AI company specializing in large engineering models, real-time simulations, and digital twins for industrial applications. The acquisition brings over 30 researchers and engineers to Mistral's Science and Applied AI teams. Mistral aims to build best-in-class AI agents for engineers in sectors like aerospace, automotive, and semiconductors by combining Emmi's physics modeling expertise with its own foundation models. The move is framed as advancing Mistral's 'Science roadmap' and positioning it as the leading AI transformation partner for industrial enterprises.
Mistral AI Acquires Physics AI Startup Emmi AI to Expand Industrial Engineering Capabilities
Mistral AI has entered a definitive agreement to acquire Emmi AI, an Austrian Physics AI startup specializing in large engineering models, real-time simulations, and digital twins for industrial applications. The acquisition brings over 30 researchers and engineers into Mistral's Science and Applied AI teams. Mistral aims to build AI agents for engineers in sectors like aerospace, automotive, and semiconductors, replacing multi-day computations with real-time physics simulations. The move advances Mistral's stated mission to become the leading AI transformation partner for industrial enterprises.
Mistral AI Founding Manifesto and Mistral 7B Release
Mistral AI published its founding mission statement alongside the release of Mistral 7B, a 7-billion-parameter open-weights language model released under Apache 2.0. The model claims to outperform all available open models up to 13B parameters on standard English and code benchmarks, produced in three months from a standing start. The post articulates Mistral's strategic thesis: open-weight models will outcompete proprietary black-box APIs for most enterprise use cases, drawing analogies to Linux, WebKit, and Kubernetes. The company signals intent to release progressively larger frontier models while building a commercial offering around on-premise and VPC deployment.
Mistral AI Now Summit 2026: Industrial AI Stack, Vibe Agent, and Les Ulis Data Center
Mistral announced a suite of enterprise-focused initiatives at its AI Now Summit 2026, including an industrial AI stack combining physics models and robotics with partnerships with Airbus, BMW Group, and ASML. The company also unveiled Vibe, a unified long-horizon productivity agent handling inbox, research, coding, and workflow orchestration. Additionally, Mistral announced a 10 MW inference data center in Les Ulis, France, scheduled to open Q3 2026, and disclosed its acquisition of Emmi to bolster scientific/physics AI capabilities.
Mistral AI Launches 'AI for Citizens' Initiative for Government and Public Sector Deployment
Mistral AI has announced 'AI for Citizens,' a collaborative initiative aimed at helping governments and public institutions deploy sovereign, customizable AI solutions. The program offers open-weight models, self-hosting options, data sovereignty guarantees, and bespoke R&D co-development to reduce dependence on dominant US AI vendors. Mistral states it is already working with governments and institutions in France, Luxembourg, Singapore, the Netherlands, England, Switzerland, and others. The initiative explicitly frames itself as an alternative to 'one size fits all' closed AI offerings from large foreign corporations.
Mistral AI Announces Fine-Tuning for Flagship Models, Agents Alpha, and SDK 1.0
Mistral AI has announced three platform updates: fine-tuning support for all flagship and specialist models on La Plateforme (including Mistral Large 2 and Codestral), an alpha release of an Agents feature enabling custom workflows via Le Chat or API, and a stable 1.0 release of the mistralai Python and TypeScript SDK. Fine-tuning supports base prompts, few-shot prompting, and full fine-tuning with custom datasets. The Agents feature is described as early-stage, with tool and data-source integrations planned.
Mistral Announces Codestral 25.08 and Integrated Enterprise Coding Stack
Mistral AI has released Codestral 25.08, a code generation model update claiming +30% accepted completions, 50% fewer runaway generations, and improved FIM benchmark performance. The announcement also frames a full enterprise coding stack comprising Codestral (completion), Codestral Embed (code-specific retrieval), and Devstral (agentic workflows via OpenHands), all deployable on-prem or in VPC environments. Devstral Medium is reported to achieve 61.6% on SWE-Bench Verified, while Devstral Small (24B, Apache-2.0) reaches 53.6%. The pitch targets regulated industries blocked by SaaS-only competitors through self-hostable, air-gapped deployment options.
Mistral AI Studio: Enterprise Production AI Platform with Observability, Agent Runtime, and AI Registry
Mistral AI has launched Mistral AI Studio, a production-focused platform targeting the gap between AI prototyping and reliable enterprise deployment. The platform is built around three pillars: Observability (traffic inspection, evaluation campaigns, regression tracking), Agent Runtime (durable multi-step agent execution built on Temporal), and AI Registry (versioned system of record for models, prompts, datasets, judges, and workflows). It supports hybrid, VPC, and on-prem deployments with built-in governance, audit trails, and access controls, and is positioned as the productized form of Mistral's own internal infrastructure.
Mistral AI Launches Redesigned Le Chat with Flash Answers, OCR, Code Interpreter, and Enterprise Tier
Mistral AI has unveiled a major overhaul of its Le Chat assistant, introducing Flash Answers (~1000 words/sec inference), web search grounding, advanced document/image OCR, sandboxed code execution, and image generation powered by Black Forest Labs Flux Ultra. The product launches on iOS and Android with free, Pro ($14.99/month), Team, and Enterprise (private preview) tiers. Upcoming features include data connectors for email/documents/databases and multi-step agentic automation. The release positions Le Chat as a direct competitor to ChatGPT and Claude in the consumer and enterprise assistant market.
Mistral 7B: Open-Weights 7B Model Outperforming Llama 2 13B
Mistral AI released Mistral 7B, a 7.3B parameter language model under the Apache 2.0 license that outperforms Llama 2 13B across all evaluated benchmarks and approaches Llama 34B on many tasks. The model employs Grouped-Query Attention (GQA) for faster inference and Sliding Window Attention (SWA) to handle longer sequences at reduced cost, achieving roughly 2x speed improvement at 16k sequence length. A fine-tuned chat variant, Mistral 7B Instruct, outperforms all 7B chat models on MT-Bench and is competitive with 13B-class chat models. The release includes deployment support for AWS, GCP, Azure, HuggingFace, and local use via vLLM.
Mistral AI Launches Model Customization Suite: Open-Source SDK, Managed Fine-Tuning, and Custom Training
Mistral AI has introduced three tiers of model customization on la Plateforme: an open-source LoRA-based fine-tuning SDK (mistral-finetune) for self-hosted use, serverless managed fine-tuning services via API initially supporting Mistral 7B and Mistral Small, and bespoke custom training services including continuous pretraining for enterprise customers. The managed fine-tuning uses LoRA adapters and claims cost and efficiency advantages over full fine-tuning while maintaining comparable performance. This positions Mistral as a full-stack customization provider competing with OpenAI's fine-tuning API and similar offerings.
Codestral 25.01: Mistral AI Releases Updated Coding Model with 2x Speed and Improved FIM Performance
Mistral AI has released Codestral 25.01, a significant upgrade to its Codestral coding model featuring a more efficient architecture and improved tokenizer that generates code approximately 2x faster than its predecessor. The model claims state-of-the-art performance for fill-in-the-middle (FIM) tasks across sub-100B parameter models, with a 256k context window and support for 80+ programming languages. Benchmarks show improvements over Codestral 2405 and competitive or superior results against DeepSeek Coder V2 lite and DeepSeek Coder 33B on HumanEval and FIM metrics. The model is available via Mistral's API, IDE plugins (VS Code, JetBrains via Continue), and for on-premises/VPC deployment, with cloud availability on Vertex AI and Azure AI Foundry.
Mistral AI Releases Codestral Embed: First Code-Specialized Embedding Model
Mistral AI has launched Codestral Embed (codestral-embed-2505), its first embedding model specialized for code retrieval and semantic understanding. The model claims to outperform leading competitors including Voyage Code 3, Cohere Embed v4.0, and OpenAI's large embedding model across benchmarks including SWE-Bench, CodeSearchNet, and Text2SQL tasks. It supports variable output dimensions and precisions (including int8), enabling storage/quality trade-offs, and is priced at $0.15 per million tokens via Mistral's API with batch discounts available.
Codestral Mamba: Mistral AI Releases Apache 2.0 Mamba-Architecture Code Model
Mistral AI has released Codestral Mamba, a 7.3B-parameter code-focused language model built on the Mamba state-space architecture rather than the Transformer architecture. The model offers linear-time inference and theoretically infinite sequence length, tested up to 256k tokens in-context retrieval. Developed with Mamba co-creators Albert Gu and Tri Dao, it is released under Apache 2.0 and available via HuggingFace, mistral-inference SDK, TensorRT-LLM, and Mistral's la Plateforme API. Mistral positions it as a local code assistant that performs on par with state-of-the-art transformer-based code models.
Mistral AI Releases Codestral: 22B Open-Weight Code Generation Model
Mistral AI has released Codestral, a 22B open-weight model explicitly designed for code generation, supporting 80+ programming languages with a 32k context window. The model is available under a non-production license on HuggingFace, with commercial licenses available on request, and is accessible via a dedicated API endpoint (codestral.mistral.ai) free during an 8-week beta. Codestral claims state-of-the-art performance on RepoBench, HumanEval, and fill-in-the-middle benchmarks, outperforming DeepSeek Coder 33B and matching or exceeding GPT-4-Turbo on some language-specific evals. Integrations are available with LlamaIndex, LangChain, Continue.dev, and Tabnine for IDE-based developer workflows.
Mistral AI Releases Devstral Medium and Devstral Small 1.1 for Agentic Coding
Mistral AI, in collaboration with All Hands AI, has released two new agentic coding models: Devstral Small 1.1 (24B parameters, Apache 2.0, 53.6% on SWE-Bench Verified) and Devstral Medium (61.6% on SWE-Bench Verified, API-only). Devstral Medium is positioned as a cost-performance leader, claiming to surpass Gemini 2.5 Pro and GPT-4.1 at roughly one-quarter the price, priced at $0.4/M input and $2/M output tokens. Devstral Small 1.1 sets a new state-of-the-art among open models for code agents without test-time scaling, and supports both Mistral function calling and XML formats for broad agentic scaffold compatibility.
Mistral AI Releases Devstral: Apache 2.0 Agentic Coding Model with SWE-Bench SOTA
Mistral AI, in collaboration with All Hands AI, releases Devstral, an agentic LLM specialized for software engineering tasks under the Apache 2.0 license. The model achieves 46.8% on SWE-Bench Verified, surpassing prior open-source state-of-the-art by over 6 percentage points and outperforming larger models like DeepSeek-V3-0324 (671B) and Qwen3 232B-A22B under the same OpenHands scaffold. Devstral is small enough to run on a single RTX 4090 or a Mac with 32GB RAM, and is available via Mistral's API at $0.1/M input tokens, as well as on HuggingFace, Ollama, and other platforms. Mistral indicates a larger agentic coding model is in development.
Mistral Launches Physics AI Division via Emmi AI Acquisition, Targeting Industrial Engineering Simulation
Mistral AI has acquired Emmi AI and is launching a 'physics AI' capability aimed at replacing or accelerating traditional numerical physics simulations (CFD, FEM) used in industrial engineering. The approach uses AI models trained on physics solver outputs to predict physical behavior from geometry and boundary conditions in seconds on a single GPU, rather than hours-to-weeks on HPC clusters. Key enterprise partners include ASML, Airbus, Safran, and Siemens Energy. The offering integrates with Mistral's existing model stack and agentic workflow tooling as part of an AI-native industrial engineering platform.
Mistral AI Announces Strategic Partnerships with SAP and Helsing for German/European AI Sovereignty
Mistral AI has announced a multiyear partnership with SAP to deliver a sovereign AI stack for Germany and Europe, integrating Mistral models into SAP's AI Foundation and co-developing industry-specific solutions. Separately, Mistral is partnering with defense-AI firm Helsing to develop vision-language-action models for defense and security applications. The company is also expanding its physical presence in Germany with a new office and increased local headcount, framing these moves as part of a broader commitment to European AI autonomy.
Le Chat Adds Deep Research, Voxtral Voice Mode, Magistral Reasoning, Projects, and Image Editing
Mistral AI has launched a major feature update to Le Chat, its AI assistant product, introducing five new capabilities: a Deep Research agent mode for structured report generation, a voice mode powered by the new Voxtral speech model, multilingual reasoning via the Magistral model, a Projects workspace for organizing conversations, and advanced image editing in partnership with Black Forest Labs. The update positions Le Chat as a more comprehensive research and productivity assistant across text, voice, and image modalities. Voxtral is introduced here as a new voice-input model, and Magistral is highlighted as the underlying reasoning engine. All features are available immediately at chat.mistral.ai with no credit card required.
Mistral AI Launches Le Chat Enterprise with Mistral Medium 3
Mistral AI has introduced Le Chat Enterprise, a feature-rich AI assistant platform powered by the newly announced Mistral Medium 3 model, targeting enterprise AI adoption challenges such as tool fragmentation and insecure knowledge integration. The platform includes enterprise search with connectors to Google Drive, SharePoint, OneDrive, Gmail, and Google Calendar, plus agent builders, document libraries, custom model support, and hybrid deployment options. Le Chat Enterprise is available now on Google Cloud Marketplace, with Azure AI and AWS Marketplace listings forthcoming. Mistral also announced improvements to its Le Chat Pro and Team plans.
Le Chat Launches MCP Connector Directory and Persistent Memories
Mistral AI has released two major features for Le Chat: a directory of 20+ enterprise MCP-powered connectors (beta) spanning data, productivity, development, automation, and commerce tools, plus custom extensibility for any remote MCP server. A Memories feature (beta) has also launched, enabling persistent cross-conversation context with user-controlled storage and privacy settings. Both features are available on the free plan, with enterprise deployment options including self-hosted and private cloud. Mistral is positioning Le Chat as a unified enterprise AI assistant surface competing directly with ChatGPT and similar products.
Mistral AI Launches Le Chat Conversational Assistant
Mistral AI has released Le Chat, a multilingual conversational assistant built on its own models including Mistral Large, Mistral Small, and a new prototype called Mistral Next. The product serves as both a public-facing demo of Mistral's capabilities and a business offering via Le Chat Enterprise, which includes self-deployment and fine-grained moderation. The assistant is currently in beta and lacks internet access. A tunable moderation mechanism is included to flag sensitive content.
Mistral AI Releases Magistral: First Reasoning Model in Open and Enterprise Variants
Mistral AI announces Magistral, its first reasoning model, released in two variants: Magistral Small (24B parameters, open-weight, Apache 2.0) and Magistral Medium (enterprise, closed). Magistral Medium scores 73.6% on AIME2024 (90% with majority voting @64), while Magistral Small scores 70.7% (83.3% respectively). Key differentiators include native multilingual chain-of-thought reasoning across eight major languages, transparent traceable reasoning steps, and up to 10x faster token throughput in Le Chat via Flash Answers. The release is accompanied by a research paper covering training infrastructure, reinforcement learning algorithm, and novel observations for training reasoning models.
Mistral AI Releases Ministral 3B and 8B Edge Models
Mistral AI has introduced two new small language models, Ministral 3B and Ministral 8B, targeting on-device and edge computing use cases. Both models support up to 128k context length and claim state-of-the-art performance in the sub-10B parameter category, outperforming comparable models from Google and Meta on internal benchmarks. Ministral 8B features an interleaved sliding-window attention mechanism for memory-efficient inference and is priced at $0.1/M tokens via API, while Ministral 3B is priced at $0.04/M tokens. Weights for Ministral 8B Instruct are available for research use, with commercial licensing available on request.
Mistral AI Introduces Non-Production License (MNPL) for Codestral and Future Models
Mistral AI has announced the Mistral AI Non-Production License (MNPL), a new licensing framework that permits non-commercial and research use but restricts commercial deployment without a separate agreement. The license debuts with Codestral, Mistral's code-focused model released the same day. Mistral frames this as balancing openness principles with commercial sustainability, while affirming continued Apache 2.0 releases for a separate product family. The move signals a bifurcated licensing strategy as Mistral seeks to monetize high-capability models while maintaining a developer-friendly reputation.
Mistral AI Raises €1.7B Series C at €11.7B Valuation, Led by ASML
Mistral AI has closed a €1.7 billion Series C funding round at an €11.7 billion post-money valuation, led by semiconductor equipment giant ASML Holding NV. The round includes participation from existing investors DST Global, Andreessen Horowitz, Bpifrance, General Catalyst, Index Ventures, Lightspeed, and NVIDIA. The partnership with ASML is framed around developing AI solutions for semiconductor and industrial engineering challenges. Mistral emphasizes continued independence and focus on custom, decentralized frontier AI for strategic industries.
Mistral AI Launches Major le Chat Update with Web Search, Canvas, Pixtral Large, and Image Generation
Mistral AI has announced a significant expansion of its le Chat assistant with several new capabilities in beta: web search with citations, a Canvas interface for collaborative document and code creation, multimodal document and image understanding powered by the new Pixtral Large model, and image generation via a partnership with Black Forest Labs (Flux Pro). The update also introduces shareable task agents for workflow automation and speculative editing for faster responses. All new features are currently offered on a free tier, positioning le Chat as a direct competitor to ChatGPT, Claude, and Perplexity.
Mistral Large 2 (123B): New Frontier Model with 128k Context, Multilingual and Code Capabilities
Mistral AI releases Mistral Large 2, a 123-billion-parameter model with a 128k context window, supporting 80+ coding languages and over a dozen natural languages. The model claims competitive performance with GPT-4o, Claude 3 Opus, and Llama 3 405B on code generation, reasoning, and multilingual benchmarks, while targeting cost-efficient single-node inference. Weights are available under a Mistral Research License for non-commercial use, with a commercial license required for self-deployment. The model is accessible via Mistral's la Plateforme API (mistral-large-2407), HuggingFace, and Google Cloud Vertex AI.
Mistral AI Releases Mistral Large, Claims Second-Best API Model After GPT-4
Mistral AI has released Mistral Large, its most capable model to date, claiming second place among API-accessible models behind GPT-4 on standard benchmarks including MMLU, HellaSwag, and coding/math evals. The model features a 32K context window, native fluency in five European languages, function calling, and constrained output mode. Simultaneously, Mistral is launching a new Mistral Small optimized for latency, restructuring its endpoint lineup, and announcing Microsoft Azure as its first major distribution partner. This marks Mistral's first significant commercial partnership and expansion beyond its own infrastructure.
Mistral Medium 3: Frontier-Class Performance at 8x Lower Cost
Mistral AI has released Mistral Medium 3, a new enterprise-focused language model priced at $0.4/$2 per million input/output tokens. The model claims to achieve 90%+ of Claude Sonnet 3.7's benchmark performance while undercutting cost leaders like DeepSeek v3, and outperforming open models including Llama 4 Maverick. It supports hybrid, on-premises, and in-VPC deployment on as few as four GPUs, and is available immediately on Mistral La Plateforme and Amazon SageMaker, with additional cloud platforms coming soon. The announcement also teases an upcoming large open-weights model release.
Mistral AI Releases Content Moderation API
Mistral AI has launched a dedicated content moderation API that classifies text inputs into 9 policy categories, including model-generated harms such as unqualified advice and PII. The API offers two endpoints—one for raw text and one for conversational content—and is natively multilingual across 11 languages. It is the same moderation system powering Mistral's Le Chat product, now made available to external developers. The classifier is LLM-based and designed to be customizable to application-specific safety standards.
Mistral AI Launches Mistral Code: Enterprise AI Coding Assistant with On-Prem Deployment
Mistral AI has announced Mistral Code, an enterprise-grade AI coding assistant currently in private beta for JetBrains IDEs and VSCode. The product bundles four specialized models (Codestral, Codestral Embed, Devstral, Mistral Medium) with an IDE plugin, admin controls, and deployment options ranging from serverless to air-gapped on-premises GPUs. It is built on a fork of the open-source Continue project with enterprise additions including RBAC, audit logging, and fine-tuning on private repositories. Early enterprise adopters include Abanca, SNCF (4,000 developers), and Capgemini (1,500+ developers).
Mistral AI Launches Mistral Compute: Sovereign AI Infrastructure Offering
Mistral AI has announced Mistral Compute, a new AI infrastructure product offering customers a private, integrated stack spanning bare-metal GPUs, orchestration, APIs, and managed PaaS services. Positioned as a European alternative to US and Chinese cloud providers, it targets nation-states, enterprises, and research institutions seeking data sovereignty and independent AI infrastructure. The offering is built on NVIDIA hardware with tens of thousands of GPUs available, and includes Mistral's training suite for domain-specific model development. Launch partners include BNP Paribas, Orange, Thales, and several other European enterprises.
Mistral Small 3.1: Multimodal, 128k Context, Apache 2.0 Open-Weight Model
Mistral AI releases Mistral Small 3.1, a ~24B parameter model with multimodal understanding, 128k token context window, and claimed best-in-class performance among small models, outperforming Gemma 3 and GPT-4o Mini on text, multimodal, and multilingual benchmarks. The model runs on a single RTX 4090 or 32GB RAM Mac at 150 tokens/second and is released under Apache 2.0 license with both base and instruct checkpoints. It is available on HuggingFace, Mistral's La Plateforme API, and Google Cloud Vertex AI, with NVIDIA NIM and Azure AI Foundry support coming soon. The release targets enterprise and on-device use cases including document verification, agentic workflows, and domain fine-tuning.