Won't fitfp16 · 4K ctx · batch 1

Does A100 40GB run DeepSeek-V3 671B? No at fp16.

At fp16 precision, DeepSeek-V3 671B (671 B MoE parameters) needs roughly 1428.9 GB of VRAM. A100 40GB only has 40 GB, short by 1388.9 GB. INT4 quantization brings it down to 359.2 GB.

>999%
VRAM
Won't fit
Estimated VRAM (fp16)
1428.9 GB
of 40 GB on A100 40GB· 1388.9 GB short
Tok/sec
13
TFTT
7495ms
Power
400W
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Memory breakdown (fp16)

Shared Weights
74.00 GB
Expert Weights
1342.00 GB
KV Cache
1.67 GB
Activations
6.67 GB
Framework Overhead
4.54 GB

Quantization comparison

Lower precision = less VRAM with a small quality trade-off. Quality order: FP16 > INT8 > INT4.

PrecisionVRAMUtilisationFits on A100 40GB?
FP16 (full precision)1428.9 GB3572%Won't fit
INT8 (8-bit)715.8 GB1789%Won't fit
INT4 / Q4 (4-bit)359.2 GB898%Won't fit

Frequently asked

Can A100 40GB run DeepSeek-V3 671B?
Not at fp16 — DeepSeek-V3 671B needs about 1428.9 GB while A100 40GB has 40 GB. It fits at INT4 quantization (359.2 GB) with some accuracy trade-off.
How much VRAM does DeepSeek-V3 671B use?
About 1428.9 GB at fp16, 359.2 GB at INT4 (for a 4K context, batch size 1). Longer contexts add to KV cache size; larger batches increase activations.
What's the fastest way to run DeepSeek-V3 671B on A100 40GB?
Use a production inference engine like vLLM, SGLang, or TensorRT-LLM with paged attention — they cut KV cache 2–3× vs the naive estimate and batch multiple requests efficiently. For A100 40GB, enable Flash Attention 2.
Where can I rent a A100 40GB?
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None of the common quantization levels fit this model on A100 40GB. Consider multi-GPU deployment or a larger card.