NVIDIA H100 80GB vs NVIDIA A100 80GB
Side-by-side local AI comparison — VRAM, memory bandwidth, model compatibility, and estimated tokens per second across 70 open-weight models.
Quick verdict
NVIDIA H100 80GB wins for local AI inference. It has 64% more memory bandwidth, runs 54 models natively (vs 54), and exclusively fits 0 models the other cannot.
Specs comparison
| Spec | NVIDIA H100 80GB | NVIDIA A100 80GB |
|---|---|---|
| VRAM | 80 GB | 80 GB |
| Memory type | HBM3 | HBM2e |
| Bandwidth | 3350 GB/s(+64%) | 2039 GB/s |
| Architecture | Hopper | Ampere |
| Backend | CUDA | CUDA |
| Tier | Datacenter | Datacenter |
| Released | 2022 | 2020 |
| Models (native) | 54 | 54 |
Estimated tokens per second
Computed from memory bandwidth and model active-parameter weight. Assumes model fits natively in VRAM.
| Model | NVIDIA H100 80GB | NVIDIA A100 80GB | Delta |
|---|---|---|---|
| Llama 3.3 70B Instruct(70B) | 63.8 t/s(Q6_K) | 38.8 t/s(Q6_K) | +64% |
| Qwen 3.6 27B(27B) | 62 t/s(FP16) | 37.8 t/s(FP16) | +64% |
| Llama 3.1 8B Instruct(8B) | 209.4 t/s(FP16) | 127.4 t/s(FP16) | +64% |
| Qwen 2.5 7B Instruct(7.6B) | 220.4 t/s(FP16) | 134.1 t/s(FP16) | +64% |
Delta is NVIDIA H100 80GB relative to NVIDIA A100 80GB.
Only NVIDIA H100 80GB can run(0)
No exclusive models — NVIDIA A100 80GB can run everything NVIDIA H100 80GB can.
Only NVIDIA A100 80GB can run(0)
No exclusive models — NVIDIA H100 80GB can run everything NVIDIA A100 80GB can.
Both run natively(54)
These models fit in VRAM on both GPUs. Bandwidth determines which runs them faster.
- Mixtral 8x22B Instruct v0.1236.2 t/svs143.8 t/s
- Qwen 3.5 122B-A10B (MoE)737 t/svs448.6 t/s
- Nemotron 3 Super 120B614.2 t/svs373.8 t/s
- GPT-OSS 120B1474 t/svs897.2 t/s
- Llama 4 Scout 109B433.5 t/svs263.9 t/s
- GLM-4.5 Air 106B491.3 t/svs299.1 t/s
- GLM-4.6V 106B491.3 t/svs299.1 t/s
- Qwen 2.5 72B Instruct62 t/svs37.8 t/s
- Llama 3.3 70B Instruct63.8 t/svs38.8 t/s
- DeepSeek R1 Distill Llama 70B63.8 t/svs38.8 t/s
- Llama 3.1 70B Instruct63.8 t/svs38.8 t/s
- Mixtral 8x7B Instruct v0.1285.7 t/svs173.9 t/s
- Command-R 35B95.7 t/svs58.3 t/s
- Qwen 3.5 35B-A3B (MoE)1228.3 t/svs747.6 t/s
- Qwen 3.6 35B95.7 t/svs58.3 t/s
- Yi 1.5 34B Chat97.4 t/svs59.3 t/s
- +38 more on both
Which should you choose?
Choose NVIDIA H100 80GB if:
- • Faster token generation is the priority
- • You want the newer architecture and longer driver support lifecycle
Choose NVIDIA A100 80GB if:
Frequently asked questions
- Which is better for local AI, the NVIDIA H100 80GB or NVIDIA A100 80GB?
- For local AI inference, the NVIDIA H100 80GB has the edge. It offers 80 GB VRAM (vs 80 GB) and 3350 GB/s bandwidth (vs 2039 GB/s), letting it run 54 models natively in VRAM vs 54 for its rival.
- How much VRAM does the NVIDIA H100 80GB have vs the NVIDIA A100 80GB?
- The NVIDIA H100 80GB has 80 GB of HBM3 at 3350 GB/s. The NVIDIA A100 80GB has 80 GB of HBM2e at 2039 GB/s. Both GPUs have the same VRAM amount; bandwidth determines which generates tokens faster.
- Can the NVIDIA H100 80GB run Llama 3.3 70B?
- Yes. The NVIDIA H100 80GB runs Llama 3.3 70B natively at Q6_K quantization at approximately 63.8 tokens per second.
- Can the NVIDIA A100 80GB run Llama 3.3 70B?
- Yes. The NVIDIA A100 80GB runs Llama 3.3 70B natively at Q6_K quantization at approximately 38.8 tokens per second.
- What is the difference between the NVIDIA H100 80GB and NVIDIA A100 80GB for AI?
- The key difference for AI inference is VRAM and memory bandwidth. The NVIDIA H100 80GB has 80 GB VRAM at 3350 GB/s (CUDA backend). The NVIDIA A100 80GB has 80 GB VRAM at 2039 GB/s (CUDA backend). VRAM determines which models fit; bandwidth determines tokens per second. The NVIDIA H100 80GB runs 54 models natively vs 54 for the NVIDIA A100 80GB.