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).
Related guides (5)
Enterprise Deployment PatternsTopic guide
Enterprise Deployment Patterns: From LLM Demo to Production Reality
Related events (8)
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 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 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 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 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.
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 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 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.