Mistral released Voxtral, an open-source speech understanding model available in a 24B Voxtral Small and a 3B Voxtral Mini, both under the Apache 2.0 license and callable via its API at prices as low as $0.001 per minute.
Why it matters: Official benchmarks and API pricing for two open-source speech understanding model sizes let readers assess whether Voxtral can replace their current ASR solutions.
Mistral AI, in partnership with All Hands AI, released Devstral Medium and upgraded Devstral Small to 1.1.
Why it matters: Official SWE-Bench Verified scores, pricing and licensing for both new models are provided, helping developers evaluate coding agent options.
Mistral AI released its first reasoning model, Magistral, in two versions: the open-source Magistral Small (24B, Apache 2.0) and the enterprise Magistral Medium.
Why it matters: With both open-source and commercial versions, official AIME2024 scores, open licensing and deployment channels, readers can use this to evaluate model selection.
Mistral AI has released Codestral Embed, its first code-specific embedding model, claiming it outperforms Voyage Code 3, Cohere Embed v4.0, and OpenAI's large embedding model on real-world code retrieval.
Mistral AI and All Hands AI have launched Devstral, an agentic large language model for software engineering tasks, released as open source under the Apache 2.0 license.
Why it matters: The official release includes model weights, API pricing, specific SWE-Bench Verified scores and deployment requirements, letting readers assess fit for local or enterprise coding scenarios.
Mistral AI released Mistral Medium 3, positioned as a new class of model with SOTA performance at 8x lower cost. It reaches or exceeds 90% of Claude Sonnet 3.7 on benchmarks, is priced at $0.4 input / $2 output per M token, surpasses Llama 4 Maverick and Cohere Command A, and can be self-deployed on 4 or more GPUs.
Why it matters: The official release provides benchmarks against Claude Sonnet 3.7, pricing, and deployment requirements, letting readers evaluate its cost-effectiveness for enterprise adoption.
Mistral AI released Mistral Small 3.1, which improves text performance over Mistral Small 3, adds multimodal understanding, extends the context window to 128k tokens, and runs at 150 tokens per second.
Why it matters: Coming from the official release, it includes benchmark comparisons, the open-source license, and hardware requirements, so readers can assess its fit for lightweight deployments.