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Can NVIDIA A100 80GB SXM4 run context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16?

Runs Q480GB VRAM availableRequires 2GB+

NVIDIA A100 80GB SXM4 meets the minimum VRAM requirement for Q4 inference of context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.

What this means for you

NVIDIA A100 80GB SXM4 can run context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 with Q4 quantization. At approximately 379 tokens/second, you can expect Excellent speed - conversational response times under 1 second.

You have 78GB headroom, which is sufficient for system overhead and smooth operation.

Quantization breakdown

QuantizationVRAM neededVRAM availableEstimated speedVerdict
Q42GB80GB379.40 tok/s✅ Fits comfortably
Q83GB80GB253.74 tok/s✅ Fits comfortably
FP166GB80GB122.12 tok/s✅ Fits comfortably

Suitable alternatives

AMD Instinct MI300X
192GB
923.44 tok/s
Price: —
NVIDIA H200 SXM 141GB
141GB
745.55 tok/s
Price: —
AMD Instinct MI300X
192GB
638.78 tok/s
Price: —
NVIDIA H100 SXM5 80GB
80GB
573.48 tok/s
Price: —
NVIDIA H200 SXM 141GB
141GB
540.74 tok/s
Price: —

More questions

NVIDIA A100 80GB SXM4 specs & pricingFull guide for context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 speed on NVIDIA A100 80GB SXM4context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 Q4 requirements