NVIDIA H100 80GB HBM3 vs NVIDIA RTX PRO 6000 Blackwell Workstation Edition, AI & Machine Learning Comparison
NVIDIA H100 80GB HBM3 wins 77 of 146 benchmarks, averaging 3.7% faster.
Both cards were measured first-party on our bench, same suite, same test rig.
What the numbers say
The gap is widest in Swin2SR 4x Upscaler, where NVIDIA RTX PRO 6000 Blackwell Workstation Edition leads by 107% (25.48 vs 52.83 images/min); the closest fight is gemma-3-270m (0% apart).
Benchmark results head-to-head
| Benchmark | NVIDIA H100 80GB HBM3 | NVIDIA RTX PRO 6000 Blackwell Workstation Edition | Difference |
|---|---|---|---|
| Qwen3 4B tok/s | 310.26 | 362.81 | -14% |
| Llama 3.1 8B tok/s | 261.83 | 258.37 | +1% |
| Qwen2.5-Coder 14B tok/s | 144.84 | 147.74 | -2% |
| Qwen3 32B tok/s | 74.07 | 70.13 | +6% |
| Llama 3.3 70B tok/s | 41 | 34.87 | +18% |
| Stable Diffusion XL images/min | 34.58 | 27.94 | +24% |
| Z-Image Turbo images/min | 22.125 | 15.6 | +42% |
| FLUX.1 dev images/min | 9.064 | 6.921 | +31% |
| FLUX.1 Kontext dev images/min | 4.264 | 3.086 | +38% |
| Qwen-Image-Edit images/min | 3.68 | 2.64 | +39% |
| LTX-Video (distilled) frames/s | 17.47 | 16.36 | +7% |
| DeepSeek-R1 Distill Llama 8B tok/s | 261.15 | 235.07 | +11% |
| DeepSeek-R1 Distill 1.5B tok/s | 537.32 | 635.1 | -15% |
| DeepSeek-R1 Distill 7B tok/s | 264.42 | 256.04 | +3% |
| Gemma 3 12B tok/s | 150.58 | 138.09 | +9% |
| Gemma 3 4B tok/s | 289.61 | 297.73 | -3% |
| Llama 3.2 1B tok/s | 880.64 | 892.74 | -1% |
| Llama 3.2 3B tok/s | 422.87 | 435.63 | -3% |
| Mistral 7B v0.3 tok/s | 275.85 | 247.33 | +12% |
| Phi-4 Mini 3.8B tok/s | 388.86 | 391.04 | -1% |
| Qwen2.5-Coder 7B tok/s | 263.91 | 256.11 | +3% |
| Qwen3 0.6B tok/s | 713.53 | 788.97 | -10% |
| Qwen3 1.7B tok/s | 556.48 | 575.77 | -3% |
| Qwen3 14B tok/s | 151.16 | 139.01 | +9% |
| Qwen3 8B tok/s | 244.22 | 225.95 | +8% |
| SmolLM3 3B tok/s | 397.99 | 406.45 | -2% |
| DeepSeek-R1 Distill 14B tok/s | 144.82 | 135.41 | +7% |
| Gemma 4 12B tok/s | 148.17 | 137.73 | +8% |
| Mistral Small 24B tok/s | 105.62 | 93.55 | +13% |
| Phi-4 14B tok/s | 165.17 | 142.68 | +16% |
| Qwen3 30B A3B tok/s | 283.78 | 308.74 | -8% |
| Codestral 22B tok/s | 110.05 | 92.7 | +19% |
| DeepSeek-R1 Distill 32B tok/s | 75.8 | 66.06 | +15% |
| Devstral Small 24B tok/s | 107.79 | 93.52 | +15% |
| Dolphin 2.9.1 Yi 1.5 34B tok/s | 76.76 | 63.74 | +20% |
| Dolphin Mistral 24B Venice tok/s | 109.13 | 93.67 | +17% |
| Dolphin X1 8B tok/s | 266 | 239.4 | +11% |
| Dolphin 3.0 Llama 3.1 8B tok/s | 266.19 | 239.28 | +11% |
| Dolphin 3.0 R1 Mistral 24B tok/s | 107.83 | 93.62 | +15% |
| Gemma 3 27B tok/s | 84.77 | 72.1 | +18% |
| Qwen2.5-Coder 32B tok/s | 75.81 | 66.07 | +15% |
| Qwen3-Coder 30B A3B tok/s | 296.22 | 317.68 | -7% |
| QwQ 32B tok/s | 75.82 | 66.07 | +15% |
| StarCoder2 15B tok/s | 134.92 | 122.09 | +11% |
| FLUX.1 Schnell images/min | 58.36 | 42.41 | +38% |
| Z-Image Turbo (1024px) images/min | 39.42 | 31.43 | +25% |
| Krea 2 Turbo images/min | 6.85 | 4.71 | +45% |
| BiRefNet images/min | 1310.97 | 1445.92 | -9% |
| Depth Anything V2 Large images/min | 918.71 | 1328.11 | -31% |
| Depth Anything V2 Small images/min | 1081.54 | 1374.58 | -21% |
| SAM ViT-Base images/min | 1431.27 | 1079.89 | +33% |
| SAM ViT-Huge images/min | 320.64 | 193.47 | +66% |
| Swin2SR 4x Upscaler images/min | 25.48 | 52.83 | -52% |
| Qwen2.5 1.5B LoRA train tok/s | 16034.9 | 15753.9 | +2% |
| Qwen2.5 7B LoRA train tok/s | 8514.3 | 6041.8 | +41% |
| SmolLM2 1.7B LoRA train tok/s | 18910.3 | 16255.4 | +16% |
| TinyLlama 1.1B LoRA train tok/s | 17522 | 18556.4 | -6% |
| Qwen2.5 1.5B served serve tok/s | 6794.8 | 5786.7 | +17% |
| Qwen2.5 7B served serve tok/s | 3601.1 | 2282.8 | +58% |
| SmolLM2 1.7B served serve tok/s | 6509.9 | 5642 | +15% |
| TinyLlama 1.1B served serve tok/s | 8336.7 | 7678.7 | +9% |
| AI21-Jamba-Reasoning-3B tok/s | 363.09 | 400.02 | -9% |
| Olmo-3.1-32B-Think tok/s | 75.53 | 65.71 | +15% |
| Codestral 22B (Q3_K_M) tok/s | 87.21 | 107.67 | -19% |
| Dolphin-Mistral-24B-Venice-Edition tok/s | 105.63 | 93.71 | +13% |
| DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored tok/s | 262.76 | 239.45 | +10% |
| DeepSeek-Coder-V2-Lite tok/s | 309.14 | 352.52 | -12% |
| DeepSeek-R1-0528-Qwen3-8B tok/s | 245.26 | 226.85 | +8% |
| DeepSeek-R1-Distill-Llama-70B tok/s | 41.17 | 32.52 | +27% |
| DeepSeek-R1 Distill 14B (Q3_K_M) tok/s | 118.43 | 149.81 | -21% |
| DeepSeek-R1-Distill-Qwen-32B-abliterated tok/s | 73.48 | 66.03 | +11% |
| dolphin-2.9-llama3-8b tok/s | 262.47 | 239.29 | +10% |
| Dolphin X1 Trinity Nano 6B tok/s | 247.94 | 282.02 | -12% |
| EVA-Qwen2.5-14B-v0.2 tok/s | 145.15 | 135.83 | +7% |
| gemma-2-2b-it-abliterated tok/s | 392.65 | 416.68 | -6% |
| gemma-2-2b tok/s | 392.26 | 417.07 | -6% |
| gemma-2-9b tok/s | 174.7 | 156.29 | +12% |
| Gemma 3 12B (Q3_K_M) tok/s | 125.92 | 153.93 | -18% |
| gemma-3-1b tok/s | 504.17 | 567.1 | -11% |
| gemma-3-270m tok/s | 961.29 | 965 | -0% |
| GLM-4.7-Flash-REAP-23B-A3B tok/s | 168.41 | 199.14 | -15% |
| GLM-4.7-Flash tok/s | 186.05 | 215.61 | -14% |
| Josiefied-Qwen3-8B-abliterated-v1 tok/s | 245 | 227.15 | +8% |
| gpt-oss-20b tok/s | 346.8 | 375.09 | -8% |
| Hermes-3-Llama-3.2-3B tok/s | 423.72 | 439.65 | -4% |
| Hermes-4-70B tok/s | 41.2 | 32.51 | +27% |
| SmolLM3-3B tok/s | 399.14 | 409.73 | -3% |
| Qwen3-Coder-Next-abliterated tok/s | 190.32 | 210.47 | -10% |
| KAT-Coder-V2.5-Dev tok/s | 231.83 | 253.35 | -8% |
| L3-8B-Stheno-v3.2 tok/s | 261.83 | 239.84 | +9% |
| Laguna-XS-2.1 tok/s | 0 | 0 | n/a |
| LFM2.5-1.2B tok/s | 926.61 | 989.91 | -6% |
| LFM2.5-8B-A1B tok/s | 581.98 | 617.09 | -6% |
| Llama-2-7B tok/s | 284.62 | 263.84 | +8% |
| Llama-3.2-3B-Instruct-uncensored tok/s | 424.25 | 440.15 | -4% |
| Llama-3.3-70B-Instruct-abliterated tok/s | 41.15 | 32.53 | +26% |
| Meta-Llama-3.1-70B tok/s | 41.19 | 32.52 | +27% |
| Meta-Llama-3.1-8B tok/s | 261.7 | 237.69 | +10% |
| Phi-4-mini tok/s | 381.52 | 393.81 | -3% |
| Mistral-7B-Instruct-v0.1 tok/s | 276.29 | 252.55 | +9% |
| Mistral-7B-Instruct-v0.2 tok/s | 276.73 | 253.34 | +9% |
| Mistral-7B-Instruct-v0.3 tok/s | 276.61 | 253.2 | +9% |
| Mistral-Nemo-Instruct-2407 tok/s | 177.38 | 164.28 | +8% |
| Mistral Small 24B (Q3_K_M) tok/s | 84 | 108.88 | -23% |
| Nanbeige4.2-3B tok/s | 0 | 0 | n/a |
| NemoMix-Unleashed-12B tok/s | 177.28 | 164.21 | +8% |
| Nemotron-3-Nano-30B-A3B tok/s | 316.51 | 325.43 | -3% |
| Hermes-4-14B tok/s | 152 | 139.56 | +9% |
| Ornith-1.0-35B tok/s | 221.65 | 237.7 | -7% |
| Ornith-1.0-9B tok/s | 216.89 | 201.69 | +8% |
| phi-2 tok/s | 340.09 | 410.12 | -17% |
| Phi-3.5-mini tok/s | 345.07 | 362.79 | -5% |
| Phi-4 14B (Q3_K_M) tok/s | 138.87 | 165.43 | -16% |
| Qwen-AgentWorld-35B-A3B tok/s | 219.1 | 234.82 | -7% |
| Qwen3-0.6B tok/s | 710.97 | 806.77 | -12% |
| Qwen3-1.7B tok/s | 557.09 | 593.5 | -6% |
| Qwen3-14B tok/s | 152.2 | 139.45 | +9% |
| Qwen3-30B-A3B tok/s | 285.44 | 311.76 | -8% |
| Qwen3-4B-Instruct-2507 tok/s | 310.58 | 333.54 | -7% |
| Qwen3-8B tok/s | 244.2 | 226.88 | +8% |
| Qwen3-Coder-Next tok/s | 188.21 | 205.69 | -8% |
| Qwen3-Next-80B-A3B-Thinking tok/s | 188.14 | 203.29 | -7% |
| Qwen1.5-0.5B tok/s | 847.02 | 1025.58 | -17% |
| Qwen2-1.5B tok/s | 536.52 | 648.49 | -17% |
| Qwen2.5-0.5B tok/s | 890 | 905.27 | -2% |
| Qwen2.5-1.5B tok/s | 537.24 | 636.39 | -16% |
| Uncensored tok/s | 144.92 | 135.68 | +7% |
| Qwen2.5-14B tok/s | 144.7 | 135.66 | +7% |
| Qwen2.5-32B tok/s | 73.5 | 66 | +11% |
| Qwen2.5-3B tok/s | 395.52 | 398.72 | -1% |
| Qwen2.5-72B tok/s | 40.78 | 29.65 | +38% |
| Qwen2.5-7B tok/s | 264.17 | 256.63 | +3% |
| Qwen2.5-Coder-0.5B tok/s | 892.81 | 910.13 | -2% |
| Qwen2.5-Coder-1.5B tok/s | 538.44 | 650.4 | -17% |
| Qwen2.5-Coder-14B-Instruct-abliterated tok/s | 145.01 | 135.88 | +7% |
| Qwen2.5-Coder 32B (Q3_K_M) tok/s | 58.05 | 75.78 | -23% |
| Qwen2.5-Coder-3B tok/s | 394 | 401.24 | -2% |
| Qwen2.5-Coder-7B-Instruct-abliterated tok/s | 264.24 | 257.07 | +3% |
| Qwen3 30B A3B (Q3_K_M) tok/s | 242.6 | 309.61 | -22% |
| Qwen3-4B-Instruct-2507 tok/s | 311.47 | 334.71 | -7% |
| Qwen3-4B-Thinking-2507 tok/s | 310.84 | 334.65 | -7% |
| Qwen3-Coder-Next tok/s | 193.79 | 211.5 | -8% |
| Qwen3-Next-80B-A3B-Thinking tok/s | 191.08 | 214.04 | -11% |
| Qwen3-Next-80B-A3B tok/s | 186.22 | 210.17 | -11% |
| SmolLM2-135M tok/s | 898.53 | 1252.77 | -28% |
| Cydonia-24B-v4.3 tok/s | 105.49 | 93.76 | +13% |
Whole-job comparison
How long each card takes to finish a complete pipeline, not just one model. NVIDIA H100 80GB HBM3 is faster on 10 of 13; NVIDIA RTX PRO 6000 Blackwell Workstation Edition on 3.
| Workflow | NVIDIA H100 80GB HBM3 | NVIDIA RTX PRO 6000 Blackwell Workstation Edition | Difference |
|---|---|---|---|
| 50-image depth pass | 5 s | 4 s | NVIDIA RTX PRO 6000 Blackwell Workstation Edition 1.32x faster |
| 500-image masking run | 1.6 min | 2.6 min | NVIDIA H100 80GB HBM3 1.63x faster |
| 24-frame storyboard | 1.8 min | 3.6 min | NVIDIA H100 80GB HBM3 2.01x faster |
| 60-second AI short film | 2.5 min | 4.5 min | NVIDIA H100 80GB HBM3 1.82x faster |
| 6-panel comic page | 3 min | 5.1 min | NVIDIA H100 80GB HBM3 1.71x faster |
| Character sheet, 12 poses | 3.7 min | 6.1 min | NVIDIA H100 80GB HBM3 1.67x faster |
| Full codebase review | 6.9 min | 6.8 min | NVIDIA RTX PRO 6000 Blackwell Workstation Edition 1.02x faster |
| 200-product catalogue cutout | 8.1 min | 4 min | NVIDIA RTX PRO 6000 Blackwell Workstation Edition 2.02x faster |
| 40-product photo shoot | 11.1 min | 16.7 min | NVIDIA H100 80GB HBM3 1.50x faster |
| 20 long-form articles | 11.4 min | 13.4 min | NVIDIA H100 80GB HBM3 1.18x faster |
| 40-product shoot, start to finish | 12.9 min | 17.6 min | NVIDIA H100 80GB HBM3 1.36x faster |
| 100-photo restoration batch | 23.8 min | 33.4 min | NVIDIA H100 80GB HBM3 1.40x faster |
| 100-photo restore and enlarge | 27.8 min | 35.3 min | NVIDIA H100 80GB HBM3 1.27x faster |
Specifications compared
| NVIDIA H100 80GB HBM3 | NVIDIA RTX PRO 6000 Blackwell Workstation Edition | |
|---|---|---|
| VRAM | 80GB | 96GB |
| Architecture | Hopper | Blackwell |
| Memory bandwidth | 3350 GB/s | 1792 GB/s |
| Boost clock | 1,980 MHz | 2,617 MHz |
| TDP | 700 W | 600 W |
| Launch MSRP | $30,000 | $8,565 |
| Release | 2022-09-20 | 2025-03-18 |
FAQ
- Which is better for ai & machine learning: NVIDIA H100 80GB HBM3 or NVIDIA RTX PRO 6000 Blackwell Workstation Edition?
- NVIDIA H100 80GB HBM3 performs better for ai & machine learning, winning 77 of 146 benchmarks in our suite with an average 3.7% advantage.
- What are the main hardware differences between NVIDIA H100 80GB HBM3 and NVIDIA RTX PRO 6000 Blackwell Workstation Edition?
- NVIDIA H100 80GB HBM3 has 80GB VRAM and a 700W TDP, while NVIDIA RTX PRO 6000 Blackwell Workstation Edition has 96GB VRAM and a 600W TDP.
- Where is the biggest performance difference between NVIDIA H100 80GB HBM3 and NVIDIA RTX PRO 6000 Blackwell Workstation Edition?
- Swin2SR 4x Upscaler: NVIDIA RTX PRO 6000 Blackwell Workstation Edition leads by roughly 107% (25.48 vs 52.83 images/min) in our testing.
NVIDIA H100 80GB HBM3 full review · NVIDIA RTX PRO 6000 Blackwell Workstation Edition full review · All AI & Machine Learning rankings