❌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 1347.0 GB of VRAM. A100 40GB only has 40 GB, short by 1307.0 GB. INT4 quantization brings it down to 343.2 GB.
>999%
VRAM
Won't fit
Estimated VRAM (fp16)
1347.0 GB
of 40 GB on A100 40GB· 1307.0 GB short
Tok/sec
19
TFTT
2849ms
Power
301W
Rent on GPUniq marketplace
A100 40GB
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Memory breakdown (fp16)
Quantization comparison
Lower precision = less VRAM with a small quality trade-off. Quality order: FP16 > INT8 > INT4.
| Precision | VRAM | Utilisation | Fits on A100 40GB? |
|---|---|---|---|
| FP16 (full precision) | 1347.0 GB | 3368% | ❌Won't fit |
| INT8 (8-bit) | 677.8 GB | 1694% | ❌Won't fit |
| INT4 / Q4 (4-bit) | 343.2 GB | 858% | ❌Won't fit |
Frequently asked
- Can A100 40GB run DeepSeek-V3 671B?
- Not at fp16 — DeepSeek-V3 671B needs about 1347.0 GB while A100 40GB has 40 GB. It fits at INT4 quantization (343.2 GB) with some accuracy trade-off.
- How much VRAM does DeepSeek-V3 671B use?
- About 1347.0 GB at fp16, 343.2 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?
- GPUniq aggregates live A100 40GB offers from verified providers. You can deploy an instance in about a minute and pay hourly with no commitment.
Other GPUs for DeepSeek-V3 671B
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None of the common quantization levels fit this model on A100 40GB. Consider multi-GPU deployment or a larger card.