Hardware
NVIDIA H100 SXM 80GB
NVIDIA H100 SXM 80GB has 80 GB HBM3 and 3350 GB/s. See which open models fit, at which quant, and roughly how fast. Figures below use the default memory (80 GB), 32 GB system RAM, and DDR5-5600 for anything that spills. Updated 2026-10-17.
Memory80 GB HBM3
Bandwidth3350 GB/s
Kindgpu
Year2022
SXM5 80GB HBM3, 3.35 TB/s. Source.
RSS for new models on this device
Models that fit
| Model | Verdict | Quant | Context | tok/s |
|---|---|---|---|---|
| Mistral Medium 3.5 128B 125B | Tight fit | UD-Q4_K_XL | 8K | 23–32 |
| Devstral 2 123B Instruct 2512 125B | Tight fit | UD-Q4_K_XL | 8K | 23–32 |
| gpt oss 120b 117B | Runs | UD-Q8_K_XL | 8K | 150–204 |
| Qwen3.5 122B A10B MTP 125B | Tight fit | UD-Q4_K_XL | 4K | 287–392 |
| Mistral Small 4 119B 2603 119B | Tight fit | UD-Q4_K_XL | 8K | 135–184 |
| Llama 4 Scout 17B 16E Instruct 108B | Tight fit | Q5_K_M | 8K | 103–141 |
| GLM 4.6V 107B | Tight fit | Q5_K_S | 8K | 104–142 |
| GLM 4.5 Air 110B | Tight fit | UD-Q4_K_XL | 8K | 116–158 |
| Qwen2.5 72B Instruct 72.7B | Tight fit | Q8_0 | 4K | 23–32 |
| Llama 3.3 70B Instruct 70.6B | Tight fit | Q8_0 | 8K | 24–32 |
| DeepSeek R1 Distill Llama 70B 70.6B | Tight fit | Q8_0 | 8K | 24–32 |
| Hermes 4 70B 70.6B | Tight fit | Q8_0 | 8K | 24–32 |
| NVIDIA Nemotron 3 Super 120B A12B 121B | Runs | IQ4_NL | 8K | 258–351 |
| Qwen3 Coder Next 79.7B | Tight fit | UD-Q6_K_XL | 8K | 140–190 |
| Qwen3 Next 80B A3B Instruct 79.7B | Tight fit | UD-Q6_K_XL | 8K | 544–742 |
| Qwen3 Next 80B A3B Thinking 79.7B | Tight fit | UD-Q6_K_XL | 8K | 544–742 |
| Step 3.7 Flash 197B | Tight fit | UD-Q2_K_XL | 8K | 77–106 |
| MiniMax M2 229B | Tight fit | UD-IQ2_XXS | 8K | 119–162 |
| Qwen3.8 Flash Next 177B | Tight fit | UD-IQ1_M | 8K | 144–196 |
| Qwen2.5 Coder 32B Instruct 32.8B | Runs great | Q8_0 | 8K | 50–68 |
| Qwen2.5 32B Instruct 32.8B | Runs | F16 | 8K | 27–37 |
| Qwen3 32B 32.8B | Runs | BF16 | 8K | 27–37 |
| DeepSeek R1 Distill Qwen 32B 32.8B | Runs | F16 | 8K | 27–37 |
| Qwen3 VL 32B Instruct 32.8B | Runs | BF16 | 8K | 27–37 |
| GLM 4 32B 0414 32.6B | Runs | BF16 | 8K | 28–38 |
| gemma 4 31B it 30.7B | Runs | BF16 | 8K | 27–36 |
| Qwen3.8 27B 27.3B | Runs | BF16 | 8K | 33–46 |
| gemma 3 27b it 27.0B | Runs | BF16 | 8K | 32–43 |
| medgemma 27b text it 27.0B | Runs | BF16 | 8K | 32–43 |
| Qwen3.6 27B 26.9B | Runs | BF16 | 8K | 34–46 |
| Qwen3.5 27B 26.9B | Runs | BF16 | 8K | 34–46 |
| Kwaipilot KAT Coder V2.5 Dev 34.7B | Tight fit | BF16 | 8K | 145–197 |
| Qwen3.8 35B A3B Distill 35.5B | Tight fit | BF16 | 8K | 298–407 |
| Qwen3.6 35B A3B 34.7B | Tight fit | BF16 | 8K | 299–407 |
| Qwen3.5 35B A3B 34.7B | Tight fit | BF16 | 8K | 299–407 |
| NVIDIA Nemotron 3.5 Lightning 30B A3B 32.9B | Runs | BF16 | 8K | 286–390 |
| Devstral Small 2 24B Instruct 2512 23.6B | Runs | BF16 | 8K | 38–52 |
| Mistral Small 3.2 24B Instruct 2506 23.6B | Runs | BF16 | 8K | 38–52 |
| Magistral Small 2509 23.6B | Runs | BF16 | 8K | 38–52 |
| NVIDIA Nemotron 3 Nano Omni 30B A3B Reasoning 31.6B | Runs great | UD-Q8_K_XL | 8K | 485–661 |
90 more models in the catalog do not fit this default profile, or ranked below the first 40 that do.
Example: Tight fit fully on your NVIDIA H100 SXM 80GB at UD-Q4_K_XL, 8K context, about 23–32 tok/s. Weights 70.5 GB plus 2.75 GB of KV cache — 74.2 GB of 76.0 GB usable. Weights shown in the verdict use GiB (the same 1024³ counting as GPU memory).