Mistral Small 3
Mistral's 24B latency-optimized open model — faster than Llama 3.3 70B, Apache 2.0
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mistral.ai/news/mistral-small-3About 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 Superseded by Mistral Small 3.1 (vision + 128k context) in March 2025.
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Key Features
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- −Superseded by Mistral Small 3.1 (March 2025), which adds vision and 128k context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
Who Is Mistral Small 3 Best For?
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Mistral Small 3.1
Mistral's 24B multimodal open-source model — beats GPT-4o Mini, Apache 2.0
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