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8Mistral AI News·1mo ago

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.

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8Mistral Ai News·1mo ago·source ↗

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.

8Mistral Ai News·1mo ago·source ↗

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.

7Mistral Ai News·20d ago·source ↗

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.

8Mistral Ai News·20d ago·source ↗

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.

7Mistral Ai News·20d ago·source ↗

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.

7Mistral Ai News·20d ago·source ↗

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.

7Mistral Ai News·20d ago·source ↗

Mistral Small 3: 24B Latency-Optimized Open-Weight Model Released Under Apache 2.0

Mistral AI has released Mistral Small 3, a 24B-parameter instruction-tuned model optimized for low latency, achieving over 81% on MMLU at 150 tokens/s on a single GPU. The model is competitive with Llama 3.3 70B and Qwen 32B while being more than 3x faster on equivalent hardware, and is released under Apache 2.0 for both pretrained and instruction-tuned checkpoints. It is explicitly not trained with RL or synthetic data, positioning it as a base model for community fine-tuning and reasoning capability development. Deployment targets include local inference on consumer hardware (RTX 4090, MacBook 32GB RAM), agentic function calling, and domain-specific fine-tuning.

7Mistral Ai News·20d ago·source ↗

Mistral AI Releases Mistral Small v24.09, Free API Tier, and Pixtral 12B Vision on le Chat with Broad Price Cuts

Mistral AI announced a multi-part release on September 17, 2024: a free tier for la Plateforme API, significant price reductions across its model family (up to 80% for Mistral Small and Codestral), an updated Mistral Small v24.09 (22B parameters, improved alignment and reasoning), and the availability of Pixtral 12B vision capabilities on le Chat. Pixtral 12B, released under Apache 2.0, supports images of any size without text performance degradation and is now accessible for free on le Chat. The pricing updates also apply to cloud partner deployments on Azure AI Studio, Amazon Bedrock, and Google Vertex AI.