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freemiumDR 86Open weights under Apache 2.0 license — free to download, self-host, fine-tune, and use commercially. Available via Mistral API (La Plateforme) at Mistral Small tier pricing.View full pricing →

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About Mistral Small 3

Mistral Small 3 is a latency-optimized 24B parameter open-source model released January 30, 2025 under Apache 2.0. At 150 tokens/second and over 81% MMLU accuracy, it outperforms Llama 3.3 70B and Qwen 32B while running more than 3× faster on the same hardware. Designed to handle 80% of generative AI tasks — conversational assistance, function calling, and fine-tuning — on a single RTX 4090 or MacBook with 32GB RAM. Superseded by Mistral Small 3.1 (vision + 128k context) in March 2025.

Key Features

✓24B parameter model — efficient size for local and cloud deployment

✓150+ tokens/second inference speed

✓Over 81% accuracy on MMLU benchmark

✓3× faster than Llama 3.3 70B on identical hardware

✓Apache 2.0 license — permissive commercial and self-hosted use

✓Runs on a single RTX 4090 or Mac with 32GB RAM

✓Both pretrained base and instruction-tuned checkpoints released

✓Low-latency function calling for agentic workflows

✓Not trained with RL or synthetic data — clean base for fine-tuning

Mistral Small 3 Pros & Cons

✅ Pros

+Outperforms Llama 3.3 70B and Qwen 32B while running 3× faster on the same hardware
+Apache 2.0 license — no commercial restrictions, fully permissive for fine-tuning and redistribution
+Runs on consumer hardware (RTX 4090 or 32GB Mac) — no GPU cluster required
+150+ tok/s inference enables real-time conversational applications
+Clean training pipeline (no RL/synthetic data) makes it a strong fine-tuning base
+Both base and instruct checkpoints available for specialized domain adaptation

⚠️ Cons

−Superseded by Mistral Small 3.1 (March 2025), which adds vision and 128k context
−Text-only — no image or multimodal input support
−32k context window is limited compared to 128k in Small 3.1 or 256k in Small 4
−No RL training means reasoning on hard math and logic tasks lags behind o1-class models