Can I Run Llama 4 on NVIDIA RTX PRO 6000 Blackwell?
Written by Jakub Rusinowski · Last updated July 21, 2026
Yes, comfortably — Llama 4 Scout 17B at Q4_K_M needs 68.2 GB at 8K context (65.8 GB weights + 2.4 GB KV cache/overhead), leaving ~27.8 GB of the NVIDIA RTX PRO 6000 Blackwell's 96 GB, at ~105 tok/s (est.), with room for up to 128K context.
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NVIDIA RTX PRO 6000 Blackwell Specs
| VRAM | 96 GB |
| Memory Bandwidth | 1792 GB/s |
Llama 4 Scout 17B on the NVIDIA RTX PRO 6000 Blackwell: VRAM by quantization
| Quant | VRAM needed | Fits 96 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 220.4 GB | ✗ No | — | — |
| Q8_0 | 118.2 GB | ✗ No | — | — |
| Q6_K | 91.8 GB | ✓ Yes | 16K | — |
| Q5_K_M | 79.7 GB | ✓ Yes | 64K | — |
| Q4_K_M | 68.2 GB | ✓ Yes | 128K | — |
| Q3_K_M | 48.9 GB | ✓ Yes | 128K | — |
| Q2_K | 38.2 GB | ✓ Yes | 256K | — |
Assumes an 8K-token context with an f16 KV cache. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 96 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
Context costs VRAM too. At Q4_K_M on the NVIDIA RTX PRO 6000 Blackwell: 8K 68.2 GB · 32K 73.1 GB · 128K 92.4 GB. Every window this model publishes still fits 96 GB.
No compatible GPU? Llama 4 Scout 17B on 48 GB of system RAM, CPU only: runs, but it is tight.
Llama 4 Sizes That Fit the NVIDIA RTX PRO 6000 Blackwell (at 8K context)
| Llama 4 Scout 17B | Q4_K_M · 68.2 GB at 8K context · ~105 tok/s (est.) |
At 2 hrs/day, buying (~$8,565) beats renting at $0.77/hr after about 15.4 years.
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FAQ
Can I run Llama 4 on the NVIDIA RTX PRO 6000 Blackwell?
Yes, comfortably — Llama 4 Scout 17B at Q4_K_M needs 68.2 GB at 8K context (65.8 GB weights + 2.4 GB KV cache/overhead), leaving ~27.8 GB of the NVIDIA RTX PRO 6000 Blackwell's 96 GB, at ~105 tok/s (est.), with room for up to 128K context.
What's the best Llama 4 size for the NVIDIA RTX PRO 6000 Blackwell?
Llama 4 Scout 17B at Q4_K_M quantization needs 68.2 GB at 8K context (65.8 GB weights + 2.4 GB KV cache/overhead), estimated ~105 tokens/sec, up to 128K context.
Every Llama 4 size on the NVIDIA RTX PRO 6000 Blackwell
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| Llama 4 Maverick 17B | 243.9 GB | Does not fit | — |
| Llama 4 Scout 17B | 68.2 GB | Runs | ~105 tok/s |
Llama 4 on Other GPUs
- Llama 4 on Apple M2 Max
- Llama 4 on NVIDIA A100 80GB (PCIe)
- Llama 4 on NVIDIA H100 80GB (PCIe)
- Llama 4 on Apple M4 Max
- Llama 4 on Apple M3 Max
Popular Models on the NVIDIA RTX PRO 6000 Blackwell
VRAM Tier
Troubleshooting
Buying Guide
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