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NVIDIA H100 80 GB
80 GB advertised VRAM. Usable memory for calculations is 90% of advertised capacity. This page is the chip + VRAM entity — not a single cooler SKU.
No fresh matched Amazon price is currently available for this canonical GPU.
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What AI models can it run?
Calculated memory fit for catalog models on this chip. Defaults are Q4 and 8K when you do not change the controls. This is not a speed ranking.
- GPU
- NVIDIA H100 80 GB · 80 GB advertised
- Usable VRAM
- 72.0 GB (advertised × 0.90)
- Quantization
- Q4 (default for this form)
- Context
- 8K (default for this form)
77 of 82 catalog models calculate as a full VRAM fit under these assumptions.
Runs fully in GPU VRAM
77 models at the selected quantization and context. Memory fit only — not a speed ranking.
Qwen2.5 72B Instruct
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 49.3 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 22.7 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Offload BF16 Offload Q8 Offload Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 16K Fits 2K Fits 32K Fits 4K Fits 8K Fits
DeepSeek R1 Distill Llama 70B
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 48.0 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 24.0 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Offload BF16 Offload Q8 Offload Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 128K Limited context 16K Fits 2K Fits 32K Fits 4K Fits 64K Fits 8K Fits
Hermes 3 Llama 3.1 70B
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 48.0 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 24.0 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Offload BF16 Offload Q8 Offload Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 128K Limited context 16K Fits 2K Fits 32K Fits 4K Fits 64K Fits 8K Fits
Llama 3.1 70B Instruct
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 48.0 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 24.0 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Offload BF16 Offload Q8 Offload Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 128K Limited context 16K Fits 2K Fits 32K Fits 4K Fits 64K Fits 8K Fits
Llama 3.3 70B Instruct
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 48.0 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 24.0 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Offload BF16 Offload Q8 Offload Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 128K Limited context 16K Fits 2K Fits 32K Fits 4K Fits 64K Fits 8K Fits
Mixtral 8x7B Instruct
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 31.3 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 40.7 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Offload BF16 Offload Q8 Fits Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 16K Fits 2K Fits 32K Fits 4K Fits 8K Fits
Code Llama 34B Instruct
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 23.6 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 48.4 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Fits BF16 Fits Q8 Fits Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 16K Fits 2K Fits 4K Fits 8K Fits
DeepSeek Coder 33B Instruct
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 23.8 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 48.2 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Fits BF16 Fits Q8 Fits Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 16K Fits 2K Fits 4K Fits 8K Fits
Qwen3 32B
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 23.5 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 48.5 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Fits BF16 Fits Q8 Fits Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 16K Fits 2K Fits 32K Fits 4K Fits 40K Fits 8K Fits
DeepSeek R1 Distill Qwen 32B
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 23.3 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 48.7 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Fits BF16 Fits Q8 Fits Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 128K Fits 16K Fits 2K Fits 32K Fits 4K Fits 64K Fits 8K Fits
Qwen2.5 32B Instruct
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 23.3 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 48.7 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Fits BF16 Fits Q8 Fits Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 16K Fits 2K Fits 32K Fits 4K Fits 8K Fits
Qwen2.5-Coder 32B Instruct
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 23.3 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 48.7 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Fits BF16 Fits Q8 Fits Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 16K Fits 2K Fits 32K Fits 4K Fits 8K Fits
QwQ 32B
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 23.3 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 48.7 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Fits BF16 Fits Q8 Fits Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 16K Fits 2K Fits 32K Fits 4K Fits 40K Fits 8K Fits
Gemma 4 31B Instruct
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 28.1 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 43.9 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Limited context BF16 Limited context Q8 Fits Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 128K Limited context 16K Fits 2K Fits 256K Limited context 32K Fits 4K Fits 64K Limited context 8K Fits
Qwen3 30B-A3B
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 20.8 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 51.2 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Fits BF16 Fits Q8 Fits Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 16K Fits 2K Fits 32K Fits 4K Fits 40K Fits 8K Fits
Qwen3-Coder 30B-A3B Instruct
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 20.8 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 51.2 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Fits BF16 Fits Q8 Fits Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 128K Fits 16K Fits 2K Fits 256K Fits 32K Fits 4K Fits 64K Fits 8K Fits
Gemma 3 27B Instruct
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 22.0 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 50.0 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Fits BF16 Fits Q8 Fits Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 128K Limited context 16K Fits 2K Fits 32K Fits 4K Fits 64K Fits 8K Fits
Gemma 2 27B Instruct
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 20.9 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 51.1 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Fits BF16 Fits Q8 Fits Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 2K Fits 4K Fits 8K Fits
Gemma 4 26B-A4B Instruct
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 19.4 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 52.6 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Fits BF16 Fits Q8 Fits Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 128K Fits 16K Fits 2K Fits 256K Limited context 32K Fits 4K Fits 64K Fits 8K Fits
Mistral Small 3.2 24B Instruct
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 17.2 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 54.8 GB leftover after the calculated requirement
- Fit
- Fits Runs fully in GPU VRAM
At 8K: FP16 Fits BF16 Fits Q8 Fits Q6 Fits Q5 Fits Q4 Fits Q3 Fits
Q4: 128K Fits 16K Fits 2K Fits 32K Fits 4K Fits 64K Fits 8K Fits
Fits with a shorter context
1 model at the selected quantization and context. Memory fit only — not a speed ranking.
GLM-4.5 Air
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 72.2 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 0.2 GB over usable VRAM
- Fit
- Limited context Fits with a shorter context
At 8K: FP16 No BF16 No Q8 Offload Q6 Offload Q5 Offload Q4 Limited context Q3 Fits
Q4: 128K Limited context 16K Limited context 2K Fits 32K Limited context 4K Fits 64K Limited context 8K Limited context
Requires CPU/RAM offload
3 models at the selected quantization and context. Memory fit only — not a speed ranking.
Qwen3 235B-A22B
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 151.2 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 79.2 GB over usable VRAM
- Fit
- Offload Requires CPU/RAM offload
At 8K: FP16 No BF16 No Q8 No Q6 No Q5 Offload Q4 Offload Q3 Offload
Q4: 16K Offload 2K Offload 32K Offload 4K Offload 40K Offload 8K Offload
Mixtral 8x22B Instruct
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 91.8 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 19.8 GB over usable VRAM
- Fit
- Offload Requires CPU/RAM offload
At 8K: FP16 No BF16 No Q8 Offload Q6 Offload Q5 Offload Q4 Offload Q3 Offload
Q4: 16K Offload 2K Offload 32K Offload 4K Offload 64K Offload 8K Offload
GPT-OSS 120B
- Quantization
- Q4
- Context
- 8K
- Required VRAM
- 75.5 GB
- Usable GPU VRAM
- 72.0 GB
- VRAM headroom
- 3.5 GB over usable VRAM
- Fit
- Offload Requires CPU/RAM offload
At 8K: FP16 No BF16 No Q8 Offload Q6 Offload Q5 Offload Q4 Offload Q3 Fits
Q4: 128K Offload 16K Offload 2K Offload 32K Offload 4K Offload 64K Offload 8K Offload
Does not fit
| Model | Required VRAM | Usable VRAM | Status |
|---|---|---|---|
| GLM-4.5 | 230.7 GB | 72.0 GB | No |
Q4 / Q8 / FP16 overview
Status below is the best calculated result across evaluated context lengths for each quantization. Open a model for the full table.
| Model | Params | Q4 | Q8 | FP16 | Max context in VRAM |
|---|
Available graphics cards
These are Icecat product SKUs mapped to this chip. Different board-partner cards are not assumed to share a price. Amazon CTAs appear only for EXACT/HIGH matches that are not bundled accessories.
No mapped product SKUs yet.
Sources
GPU identity and VRAM: Icecat structured specifications. Compatibility: RigForAI calculated estimate. Amazon: live affiliate match on individual SKUs, via /go/amazon/.