What can NVIDIA RTX PRO 6000 Blackwell run for long context?
Build: NVIDIA RTX PRO 6000 Blackwell + — + 32 GB RAM (windows)
Runs comfortably223 models
Ranked by fit for long context use case + predicted speed. Click a row for VRAM breakdown.
Quant: Q8_0Context: 8,192VRAM: 14.4 GBHeadroom: 81.6 GBollama run qwen3:8b137tok/sEstimated
ollama run qwen3:8bQuant: Q8_0Context: 8,192VRAM: 10.8 GBHeadroom: 85.2 GBollama run qwen2.5:7b157tok/sEstimated
ollama run qwen2.5:7bQuant: Q8_0Context: 8,192VRAM: 8.4 GBHeadroom: 87.6 GBollama run gemma4:e4b274tok/sEstimated
ollama run gemma4:e4bQuant: Q8_0Context: 8,192VRAM: 8.0 GBHeadroom: 88.0 GBollama run phi3.5:3.8b288tok/sEstimated
ollama run phi3.5:3.8bQuant: Q4_K_MContext: 8,192VRAM: 10.4 GBHeadroom: 85.6 GB241tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 9.7 GBHeadroom: 86.3 GB276tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 59.3 GBHeadroom: 36.7 GB161tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 9.7 GBHeadroom: 86.3 GB276tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 5.3 GBHeadroom: 90.7 GB643tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 11.1 GBHeadroom: 84.9 GB241tok/sEstimated
Quant: Q8_0Context: 8,192VRAM: 50.4 GBHeadroom: 45.6 GBollama run nemotron3:nano37tok/sEstimated
ollama run nemotron3:nanoQuant: Q8_0Context: 8,192VRAM: 21.5 GBHeadroom: 74.5 GBollama run mistral-nemo:12b91tok/sEstimated
ollama run mistral-nemo:12bRuns with tradeoffs7 models
Tight VRAM, partial CPU offload, or context-limited.
Quant: Q4_K_MContext: 2,048VRAM: 92.4 GBHeadroom: 3.6 GB- • Tight VRAM fit — only 3.6 GB headroom left for context growth
ollama run nemotron3:super16tok/sEstimated
- • Tight VRAM fit — only 3.6 GB headroom left for context growth
ollama run nemotron3:superQuant: AWQ-INT4Context: 2,048VRAM: 105.9 GBHeadroom: 9.3 GB- • Partial CPU offload: ~9% of layers run on CPU
73tok/sEstimated
- • Partial CPU offload: ~9% of layers run on CPU
Quant: Q4_K_MContext: 2,048VRAM: 97.1 GBHeadroom: 18.1 GB- • Partial CPU offload: ~1% of layers run on CPU
54tok/sEstimated
- • Partial CPU offload: ~1% of layers run on CPU
Quant: Q4_K_MContext: 2,048VRAM: 93.8 GBHeadroom: 2.2 GB- • Tight VRAM fit — only 2.2 GB headroom left for context growth
ollama run mistral-large:123b16tok/sEstimated
- • Tight VRAM fit — only 2.2 GB headroom left for context growth
ollama run mistral-large:123bQuant: AWQ-INT4Context: 2,048VRAM: 97.1 GBHeadroom: 18.1 GB- • Partial CPU offload: ~1% of layers run on CPU
32tok/sEstimated
- • Partial CPU offload: ~1% of layers run on CPU
Quant: Q4_K_MContext: 2,048VRAM: 107.6 GBHeadroom: 7.6 GB- • Partial CPU offload: ~11% of layers run on CPU
ollama run mixtral:8x22b14tok/sEstimated
- • Partial CPU offload: ~11% of layers run on CPU
ollama run mixtral:8x22bQuant: Q4_K_MContext: 2,048VRAM: 107.6 GBHeadroom: 7.6 GB- • Partial CPU offload: ~11% of layers run on CPU
14tok/sEstimated
- • Partial CPU offload: ~11% of layers run on CPU
What if you upgraded?
Hypothetical scenarios. We re-ran the compatibility engine for each.
+32 GB system RAM
~$80–150
Doubles your CPU-offload working set. Helps when models don't quite fit in VRAM.
Unlocks: 41 new comfortable, 7 new tradeoff
- • Qwen 3 0.6B
- • Qwen 3 1.7B
- • Gemma 3 270M
- • SmolLM2 135M Instruct
Upgrade to NVIDIA H200 NVL (PCIe)
~$32000
141 GB VRAM (vs your 96 GB) plus a bandwidth jump from ~1792 GB/s to ~4800 GB/s.
Unlocks: 46 new comfortable
- • Qwen 3 0.6B
- • Qwen 3 1.7B
- • Gemma 3 270M
- • SmolLM2 135M Instruct
Add a second NVIDIA RTX PRO 6000 Blackwell
~$8999
Tensor parallelism splits the model across both cards, effectively doubling VRAM. Bandwidth doesn't double — runs ~1.5× the single-card speed in practice.
Unlocks: 55 new comfortable
- • Qwen 3 235B-A22B
- • Qwen 3 0.6B
- • GLM-5
- • Qwen 3 1.7B
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Won't runtop 5 popular models
Need more memory than you have. Shown for orientation.
Even with CPU offload, needs more memory than your VRAM (96 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (96 GB) + 60% of system RAM (19 GB) combined.
Even with CPU offload, needs more memory than your VRAM (96 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (96 GB) + 60% of system RAM (19 GB) combined.
Even with CPU offload, needs more memory than your VRAM (96 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (96 GB) + 60% of system RAM (19 GB) combined.
Even with CPU offload, needs more memory than your VRAM (96 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (96 GB) + 60% of system RAM (19 GB) combined.
Even with CPU offload, needs more memory than your VRAM (96 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (96 GB) + 60% of system RAM (19 GB) combined.
How to read these numbers
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