Mistral Small 3 24B (2501) on AMD Radeon RX 9060 XT 8GB
Can the AMD Radeon RX 9060 XT 8GB run Mistral Small 3 24B (2501)?
Barely: most of the model spills into system RAM
Heavy offload. At Q6_K it needs about 21.7 GB of 8.0 GB usable, with an estimated speed of 3.1 tok/s.
- Best quant
Q6_K- Generation speed
- 3.1 tok/s
- Prompt processing
- 680 tok/s
- First token (1K prompt)
- 1.5 s
- Largest safe context
- —
Download Mistral Small 3 24B (2501)
Recommended for the AMD Radeon RX 9060 XT 8GB: Q6_K. Every other quantization has its own download link in the table below.
Quickest · Ollama
One command downloads a ready-to-run version and starts a chat.
ollama run mistral-small:24bQuantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
Download the Q6_K file (opens in a new tab)
huggingface.co/unsloth/Mistral-Small-24B-Instruct-2501-GGUF (opens in a new tab)
ollama run hf.co/unsloth/Mistral-Small-24B-Instruct-2501-GGUF:Q6_KOriginal weights · Hugging Face
Full-precision files from Mistral AI, for fine-tuning, vLLM, Transformers.
huggingface.co/mistralai/Mistral-Small-24B-Instruct-2501 (opens in a new tab)
How the C grade is scored
Every result gets up to 100 points from four parts. The points decide the letter grade.
| Model quality | 28.5 / 45 | |
|---|---|---|
| Memory fit | 4.0 / 25 | |
| Speed | 4.2 / 15 | |
| Memory use | 15.0 / 15 | |
| Total | 51.7 / 100 | 51 ptsUsable (C) · 51 of 100 points: Model quality 28.5/45, Memory fit 4.0/25, Speed 4.2/15, Memory use 15.0/15 |
Every quantization on the AMD Radeon RX 9060 XT 8GB
| Quant | Memory needed | Available | Speed | Fit | Grade · points | Download |
|---|---|---|---|---|---|---|
Q2_K | 11.8 GB | 8.0 GB | 10.5 tok/s | Heavy offload | 46 ptsUsable (C) · 46 of 100 points: Model quality 20.2/45, Memory fit 4.0/25, Speed 7.7/15, Memory use 15.0/15 | GGUF (opens in a new tab) |
Q3_K_M | 13.9 GB | 8.0 GB | 7.1 tok/s | Heavy offload | 49 ptsUsable (C) · 49 of 100 points: Model quality 24.2/45, Memory fit 4.0/25, Speed 6.3/15, Memory use 15.0/15 | GGUF (opens in a new tab) |
Q4_K_M | 16.7 GB | 8.0 GB | 4.9 tok/s | Heavy offload | 51 ptsUsable (C) · 51 of 100 points: Model quality 27.4/45, Memory fit 4.0/25, Speed 5.3/15, Memory use 15.0/15 | GGUF (opens in a new tab) |
Q5_K_M | 19.1 GB | 8.0 GB | 3.9 tok/s | Heavy offload | 51 ptsUsable (C) · 51 of 100 points: Model quality 27.9/45, Memory fit 4.0/25, Speed 4.7/15, Memory use 15.0/15 | GGUF files (opens in a new tab) |
Q6_K | 21.7 GB | 8.0 GB | 3.1 tok/s | Heavy offload | 51 ptsUsable (C) · 51 of 100 points: Model quality 28.5/45, Memory fit 4.0/25, Speed 4.2/15, Memory use 15.0/15 | GGUF (opens in a new tab) |
Q8_0 | 27.3 GB | 8.0 GB | — | Won't run | 8 ptsWon't run (F) · 8 of 100 points: Model quality 8.6/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 | GGUF (opens in a new tab) |
F16 | 49.5 GB | 8.0 GB | — | Won't run | 8 ptsWon't run (F) · 8 of 100 points: Model quality 8.6/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 | GGUF (opens in a new tab) Original weights (opens in a new tab) |
Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.
Other hardware that runs it
- 83 ptsGreat (A) · 83 of 100 points: Model quality 28.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5090
- 82 ptsGreat (A) · 82 of 100 points: Model quality 27.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 3090
- 82 ptsGreat (A) · 82 of 100 points: Model quality 27.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4090
- 82 ptsGreat (A) · 82 of 100 points: Model quality 27.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 AMD Radeon RX 7900 XTX
- 78 ptsGreat (A) · 78 of 100 points: Model quality 24.2/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4070 Ti SUPER
- 78 ptsGreat (A) · 78 of 100 points: Model quality 24.2/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4080 SUPER
Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.