New model releases, open-sourcing, and iterations: first-hand records of flagship updates from major model vendors, open weight releases, and performance and price changes.
Mistral AI released Mistral Small 4, the first small model to unify Magistral reasoning, Pixtral multimodal and Devstral agentic coding capabilities into a single model, open sourced under the Apache 2.0 license.
Why it matters: The official release provides full architecture parameters, benchmark comparisons and deployment requirements, letting readers assess whether it can replace a multi-model stack.
Mistral AI has released Voxtral Transcribe 2, comprising two speech transcription models, Voxtral Mini Transcribe V2 and Voxtral Realtime, supporting 13 languages, speaker diarization, and word-level timestamps.
Why it matters: The official post provides latency, error rate, and pricing data for both transcription models and releases the Realtime weights, so readers can compare against their current speech solutions.
Mistral AI has released the open source coding model family Devstral 2, comprising the 123B Devstral 2 (modified MIT license) and the 24B Devstral Small 2 (Apache 2.0). Both support 256K context windows and score 72.2% and 68.0% on SWE-bench Verified respectively.
Why it matters: The official post covers both models' open source licenses, SWE-bench Verified scores, API pricing, and hardware requirements, so readers can assess local or on-device deployment feasibility.
Mistral has released its new Mistral 3 model series, including the MoE-architecture Mistral Large 3 (41B active, 675B total parameters) and Ministral 3 models in 3B, 8B, and 14B sizes, all open sourced under Apache 2.0.
Why it matters: The official announcement fully lists model specs, open source licenses, deployment options, and available platforms, so readers can assess feasibility of running them in their own environments.
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 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.