Can I Run / Devstral Small 2 24B Instruct 2512 / on AMD Ryzen AI Max+ 395 (128GB)

Can I Run Devstral Small 2 24B Instruct 2512 on a AMD Ryzen AI Max+ 395 (128GB)?

Yes

Runs at full precision (fp16). Zero quality loss.

Model size
24.0B
GPU memory
96.0GB
Smallest quant
Q2_K
Best fit
fp16

13 quantizations fit your 96.0GB

QuantMin VRAMRecommendedFile sizeHeadroom
fp16BEST49.0 GB50.5 GB0.9 GB+47.0 GB
Q8_026.5 GB28.0 GB25.1 GB+69.5 GB
Q6_K20.8 GB22.3 GB19.4 GB+75.2 GB
Q5_K_M18.0 GB19.5 GB16.8 GB+78.0 GB
Q5_K_S17.6 GB19.1 GB16.3 GB+78.4 GB
Q4_116.0 GB17.5 GB14.9 GB+80.0 GB
Q4_K_M15.6 GB17.1 GB14.3 GB+80.5 GB
Q4_K_S14.7 GB16.2 GB13.6 GB+81.3 GB
Q4_014.5 GB16.0 GB13.5 GB+81.5 GB
Q3_K_L11.7 GB13.2 GB12.4 GB+84.3 GB
Q3_K_M11.1 GB12.6 GB11.5 GB+85.0 GB
Q3_K_S10.2 GB11.7 GB10.4 GB+85.8 GB
Q2_K8.9 GB10.4 GB8.9 GB+87.1 GB

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Full model details
Devstral Small 2 24B Instruct 2512

All quant variants, benchmark scores, and use-case tags.

Best models for this GPU
AMD Ryzen AI Max+ 395 (128GB)

Top-ranked open-source models that fit in 96.0GB.

FAQ

Can the AMD Ryzen AI Max+ 395 (128GB) run Devstral Small 2 24B Instruct 2512?

Yes. The AMD Ryzen AI Max+ 395 (128GB)'s 96.0GB of unified memory is enough to run Devstral Small 2 24B Instruct 2512 at fp16 quantization (49.0GB required).

What's the best quantization to use?

fp16 is the highest-precision quantization that fits in your 96.0GB. It uses about 49.0GB of memory and 50.5GB recommended for comfortable inference.

What if I need more headroom for context length?

KV cache memory grows with context length. The numbers above assume a baseline 2K-4K context. For long-context use (32K+), add another 2-6GB depending on the model architecture.