NVIDIA GeForce RTX 5080 vs NVIDIA RTX PRO 6000 Blackwell
For running models locally, priced in Canada. At 128k context the first runs 22 models fully in memory, the second 70.
In short
The NVIDIA RTX PRO 6000 Blackwell has more memory for models: 96 GB against 16 GB. At 128k context the NVIDIA RTX PRO 6000 Blackwell runs 70 of the models we track fully in memory and the NVIDIA GeForce RTX 5080 22; only the NVIDIA RTX PRO 6000 Blackwell holds Qwen 3.8 Flash Next. On the models both run fully in memory, the NVIDIA RTX PRO 6000 Blackwell is about 1.9× as fast as the NVIDIA GeForce RTX 5080 (estimated, median across models). In Canada the NVIDIA GeForce RTX 5080 costs $2,570 at eBay and the NVIDIA RTX PRO 6000 Blackwell $3,258 at Amazon: the NVIDIA GeForce RTX 5080 is $688 cheaper.
Updated . Speeds are estimates; how they are worked out.
Specifications
| Spec | NVIDIA GeForce RTX 5080 | NVIDIA RTX PRO 6000 Blackwell |
|---|---|---|
| GPU | GeForce RTX 5080 | RTX PRO 6000 Blackwell |
| Memory | 16 GB GDDR7 | 96 GB GDDR7 |
| Memory bus | 256-bit | 512-bit |
| Memory bandwidth | 960 GB/s | 1,792 GB/s |
| FP16 compute | 113 TFLOPS | 504 TFLOPS |
| Software | CUDA | CUDA |
| Board power | 360 W | 600 W |
| PCIe generation | Gen 5 | Gen 5 |
| PCIe lanes | x16 | x16 |
What each runs
Estimated decode speed with the most precise quant that fits each one est.
| Model | NVIDIA GeForce RTX 5080 | NVIDIA RTX PRO 6000 Blackwell |
|---|---|---|
| Qwen 3.8 Flash Next | won't run | 20tok/sUD-Q3_K_XL |
| Qwen 3.8 27B | offload | 29tok/sQ8_0 |
| Qwen 3.5 122B-A10B | won't run | 62tok/sQ5_K_M |
| Qwen 3.6 27B | offload | 30tok/sQ8_0 |
| Gemma 4 31B | offload | 25tok/sQ8_0 |
| Nemotron 3 Super 120B-A12B | won't run | 63tok/sQ5_K_M |
| Qwen3 Coder Next | won't run | 90tok/sQ8_0 |
| gpt-oss 120B | won't run | 84tok/sMXFP4 |
| Mistral Small 4 119B | won't run | 76tok/sQ6_K |
| Qwen 3.6 35B-A3B | offload | 114tok/sQ8_0 |
| Qwen 3.5 27B | offload | 30tok/sQ8_0 |
| Gemma 4 26B-A4B | offload | 95tok/sQ8_0 |
| GLM 4.5 Air | won't run | 20tok/sQ4_K_M |
| Qwen 3.5 35B-A3B | offload | 114tok/sQ8_0 |
| GLM 4.7 Flash | offload | 54tok/sQ8_0 |
| Devstral Small 2 24B | offload | 24tok/sQ8_0 |
| Qwen3 Next 80B-A3B | won't run | 104tok/sQ8_0 |
| Nemotron 3.5 Lightning 30B-A3B | offload | 160tok/sUD-Q6_K_XL |
| gpt-oss 20B | 64tok/sQ4_K_M | 118tok/sMXFP4 |
| Kimi Linear 48B-A3B | offload | 155tok/sQ8_0 |
| Qwen3 Coder 30B-A3B | offload | 42tok/sQ8_0 |
| Qwen3 32B | won't run | 16tok/sQ8_0 |
| Gemma 4 12B | 49tok/sQ6_K | 73tok/sQ8_0 |
| Qwen 3.5 9B | 43tok/sQ8_0 | 80tok/sQ8_0 |
| Gemma 3 27B | offload | 28tok/sQ8_0 |
| Mistral Small 3.2 24B | offload | 24tok/sQ8_0 |
| DeepSeek R1 Distill Qwen 32B | won't run | 16tok/sQ8_0 |
| Llama 3.3 70B | won't run | 12tok/sQ5_K_M |
| Ministral 3 14B | offload | 31tok/sQ8_0 |
| Qwen3 14B | offload | 30tok/sQ8_0 |
| DeepSeek R1 0528 Qwen3 8B | offload | 40tok/sQ8_0 |
| Qwen3 8B | offload | 40tok/sQ8_0 |
| Phi-4 14B | offload | 26tok/sQ8_0 |
| Qwen 3.5 4B | 67tok/sQ8_0 | 126tok/sQ8_0 |
| Ministral 3 8B | offload | 41tok/sQ8_0 |
| Granite 4.2 8B | offload | 36tok/sQ8_0 |
| Gemma 4 E4B | 50tok/sQ8_0 | 93tok/sQ8_0 |
| LFM2.5 8B-A1B | 49tok/sUD-Q6_K | 89tok/sQ8_0 |
| Llama 3.1 8B | offload | 47tok/sQ6_K |
| Qwen2.5 0.5B | 278tok/sQ8_0 | 519tok/sQ8_0 |
| Qwen3.5 0.8B | 244tok/sQ8_0 | 455tok/sQ8_0 |
| Qwen3.5 2B | 194tok/sQ5_K_M | 363tok/sQ5_K_M |
| DeepSeek R1 Distill Qwen 1.5B | 105tok/sQ8_0 | 197tok/sQ8_0 |
| Mellum2.1 12B A2.5B Thinking | 78tok/sQ8_0 | 146tok/sQ8_0 |
| Spark X2.5 4B | 75tok/smlx-4bit | 140tok/smlx-4bit |
| MiniCPM5 2B | 72tok/sQ8_0 | 134tok/sQ8_0 |
| FrogNano 4B 2609 | 66tok/sQ8_0 | 124tok/sQ8_0 |
| Kimi VL A3B Thinking 2506 | 60tok/sQ4_K_M | 93tok/sQ8_0 |
| LFM2.5 2.6B | 55tok/sQ8_0 | 102tok/sQ8_0 |
| LFM2.5 VL 3B | 55tok/sQ8_0 | 102tok/sQ8_0 |
| GLM 4.6V Flash | 52tok/sQ4_K_M | 72tok/sQ8_0 |
| GLM 4 9B 0414 | 44tok/smlx-5bit | 82tok/smlx-5bit |
| DeepSeek R1 Distill Qwen 7B | 43tok/sQ6_K | 71tok/sQ8_0 |
| granite vision 4.1 4b | 42tok/sQ8_0 | 77tok/sQ8_0 |
| granite 4.2 3b | 41tok/sQ8_0 | 76tok/sQ8_0 |
| Kimi VL A3B | offload | 91tok/smlx-8bit |
| GLM 4.1V 9B Thinking | offload | 65tok/smlx-8bit |
| DeepSeek R1 Distill Llama 8B | offload | 43tok/sQ8_0 |
| LFM2.5 24B A2B | offload | 52tok/sQ8_0 |
| Ministral 3 8B Reasoning 2512 | offload | 41tok/sQ8_0 |
| Qwen3.8 27B OBLITERATED | offload | 38tok/smlx-4bit |
| DeepSeek R1 Distill Qwen 14B | offload | 27tok/sQ8_0 |
| Devstral Small 2507 | offload | 24tok/sQ8_0 |
| Magistral Small 2506 | offload | 24tok/sQ8_0 |
| Magistral Small 2507 | offload | 24tok/sQ8_0 |
| Magistral Small 2509 | offload | 24tok/sQ8_0 |
| DeepSeek R1 Distill Llama 70B | won't run | 12tok/sQ5_K_M |
| GLM 4.5V | won't run | 20tok/sQ4_K_M |
| GLM 4.6V | won't run | 20tok/sQ4_K_M |
| granite 4.2 30b | won't run | 17tok/sQ8_0 |
| DeepSeek V4 Flash | won't run | offload |
| GLM 5.3 Flash | won't run | offload |
| MiniMax M2.7 | won't run | offload |
| Devstral 2 123B Instruct 2512 | won't run | offload |
| Kimi Dev 72B | won't run | offload |
| Mistral Medium 3.5 128B | won't run | offload |
| DeepSeek R1 | won't run | won't run |
| DeepSeek R1 0528 | won't run | won't run |
| DeepSeek R1 Zero | won't run | won't run |
| DeepSeek V3 0324 | won't run | won't run |
| DeepSeek V3.1 | won't run | won't run |
| DeepSeek V3.1 Terminus | won't run | won't run |
| DeepSeek V3.2 | won't run | won't run |
| DeepSeek V4 Flash 0731 | won't run | won't run |
| DeepSeek V4 Flash Vision Exp | won't run | won't run |
| GLM 4.5 | won't run | won't run |
| GLM 4.6 | won't run | won't run |
| GLM 4.7 | won't run | won't run |
| GLM 5 | won't run | won't run |
| GLM 5.1 | won't run | won't run |
| GLM 5.2 | won't run | won't run |
| GLM 5.3 | won't run | won't run |
| Kimi K2 | won't run | won't run |
| Kimi K2 Instruct 0905 | won't run | won't run |
| Kimi K2 Thinking | won't run | won't run |
| Kimi K2.5 | won't run | won't run |
| MiniMax M2 | won't run | won't run |
| MiniMax M2.1 | won't run | won't run |
| MiniMax M2.5 | won't run | won't run |
| MiniMax M3 | won't run | won't run |
Questions
- Which is better for local AI, the NVIDIA GeForce RTX 5080 or the NVIDIA RTX PRO 6000 Blackwell?
- Choose the NVIDIA RTX PRO 6000 Blackwell to run bigger models. Choose the NVIDIA RTX PRO 6000 Blackwell for speed. Choose the NVIDIA GeForce RTX 5080 to spend less.
- Which can run bigger models, the NVIDIA GeForce RTX 5080 or the NVIDIA RTX PRO 6000 Blackwell?
- At 128k context the NVIDIA RTX PRO 6000 Blackwell runs 70 of the models we track fully in memory and the NVIDIA GeForce RTX 5080 22; only the NVIDIA RTX PRO 6000 Blackwell holds Qwen 3.8 Flash Next.
- Which is faster for local AI, the NVIDIA GeForce RTX 5080 or the NVIDIA RTX PRO 6000 Blackwell?
- On the models both run fully in memory, the NVIDIA RTX PRO 6000 Blackwell is about 1.9× as fast as the NVIDIA GeForce RTX 5080 (estimated, median across models).
- What is the price difference between the NVIDIA GeForce RTX 5080 and the NVIDIA RTX PRO 6000 Blackwell?
- In Canada the NVIDIA GeForce RTX 5080 costs $2,570 at eBay and the NVIDIA RTX PRO 6000 Blackwell $3,258 at Amazon: the NVIDIA GeForce RTX 5080 is $688 cheaper.
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