Mistral Small 3

Today we’re introducing Mistral Small 3, a latency-optimized 24B-parameter model released under the Apache 2.0 license.

Mistral Small 3 is competitive with larger models such as Llama 3.3 70B or Qwen 32B, and is an excellent open replacement for opaque proprietary models like GPT4o-mini. Mistral Small 3 is on par with Llama 3.3 70B instruct, while being more than 3x faster on the same hardware.

Mistral Small 3 is a pre-trained and instructed model catered to the ‘80%’ of generative AI tasks—those that require robust language and instruction following performance, with very low latency.

We designed this new model to saturate performance at a size suitable for local deployment. Particularly, Mistral Small 3 has far fewer layers than competing models, substantially reducing the time per forward pass. At over 81% accuracy on MMLU and 150 tokens/s latency, Mistral Small is currently the most efficient model of its category.

We’re releasing both a pretrained and instruction-tuned checkpoint under Apache 2.0. The checkpoints can serve as a powerful base for accelerating progress. Note that Mistral Small 3 is neither trained with RL nor synthetic data, so is earlier in the model production pipeline than models like Deepseek R1 (a great and complementary piece of open-source technology!). It can serve as a great base model for building accrued reasoning capacities. We look forward to seeing how the open-source community adopts and customizes it.

Performance

Human Evaluations

We conducted side by side evaluations with an external third-party vendor, on a set of over 1k proprietary coding and generalist prompts. Evaluators were tasked with selecting their preferred model response from anonymized generations produced by Mistral Small 3 vs another model. We are aware that in some cases the benchmarks on human judgement starkly differ from publicly available benchmarks, but have taken extra caution in verifying a fair evaluation. We are confident that the above benchmarks are valid.