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Mistral Small 3 24B needs 14 GB VRAM at Q4. The Radeon RX 7900 XTX 24GB has 24 GB.
🌀 Mistral Small 3 24B (Mistral) is a 24B-parameter model for fast general chat, low-latency assistants. Near-large-model quality with fast, efficient inference. The question is whether the Radeon RX 7900 XTX 24GB’s 24 GB of VRAM can hold it — here’s the exact math.
VRAM requirements
| Quantization | VRAM needed | Radeon RX 7900 XTX 24GB |
|---|---|---|
| Q4_K_M (recommended) | 14 GB | ✅ |
| Q8_0 (near-lossless) | 25 GB | ❌ |
Expected performance
Running Mistral Small 3 24B at Q4 on the Radeon RX 7900 XTX 24GB, expect roughly ~19 tokens/sec in Ollama or llama.cpp — comfortably faster than reading speed, so chat feels responsive.
Headroom: 14 GB used of 24 GB leaves about 10 GB free for KV cache (context). That’s fine for 4-8K context; for 32K+ you may need a smaller batch or a lower quant.
About the Radeon RX 7900 XTX 24GB
Architecture: RDNA 3 · VRAM: 24 GB · Price: ~$900.
Good: 24GB at a good price; works with llama.cpp + ROCm/Vulkan
Watch out: AMD software stack is less plug-and-play than CUDA
Check current Radeon RX 7900 XTX 24GB price on Amazon →
Related checks
Other models on the Radeon RX 7900 XTX 24GB
🎯 LLM Hardware Checker
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💾 VRAM Requirements
Exact VRAM per model at Q4/Q5/Q8/FP16 with context scaling.
Frequently asked questions
Can the Radeon RX 7900 XTX 24GB run Mistral Small 3 24B?
Yes — runs great at Q4 (recommended). Mistral Small 3 24B needs 14 GB VRAM at Q4_K_M; the Radeon RX 7900 XTX 24GB has 24 GB.
How much VRAM does Mistral Small 3 24B need?
Mistral Small 3 24B needs about 14 GB at Q4_K_M (recommended) and 25 GB at Q8_0.
How many tokens per second will the Radeon RX 7900 XTX 24GB get on Mistral Small 3 24B?
Roughly ~19 tokens/sec at Q4 in Ollama or llama.cpp.