Can I Run Llama 4.5 on NVIDIA RTX 6000 Ada Generation?
Written by Jakub Rusinowski · Last updated July 21, 2026
No — Llama 4.5 Scout at Q4_K_M needs 69.4 GB at 8K context (65.8 GB weights + 3.6 GB KV cache/overhead), and the NVIDIA RTX 6000 Ada Generation's 48 GB leaves it ~21.4 GB short. The cheapest card that runs it is the NVIDIA RTX PRO 5000 Blackwell (72 GB) (72 GB).
Get a personalized upgrade path →
or compare on Vast.ai from $0.77/hr (typical low · varies)
As an Amazon Associate we earn from qualifying purchases. Cloud GPU links are referral links — we may earn a commission at no extra cost to you.
NVIDIA RTX 6000 Ada Generation Specs
| VRAM | 48 GB |
| Memory Bandwidth | 960 GB/s |
Llama 4.5 Scout on the NVIDIA RTX 6000 Ada Generation: VRAM by quantization
| Quant | VRAM needed | Fits 48 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 221.6 GB | ✗ No | — | — |
| Q8_0 | 119.4 GB | ✗ No | — | — |
| Q6_K | 92.9 GB | ✗ No | — | — |
| Q5_K_M | 80.8 GB | ✗ No | — | — |
| Q4_K_M | 69.4 GB | ✗ No | — | — |
| Q3_K_M | 50 GB | ✗ No | — | — |
| Q2_K | 39.4 GB | ✓ Yes | 32K | — |
Assumes an 8K-token context with an f16 KV cache, on an estimated architecture — this model publishes no config we can read. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 48 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 6000 Ada Generation: 8K 69.4 GB ✗ · 32K 77.6 GB ✗ · 128K 110.6 GB ✗. Past 8K it no longer fits 48 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
No compatible GPU? Llama 4.5 Scout on 64 GB of system RAM, CPU only: runs, but it is tight.
Why It Does Not Fit
Every Llama 4.5 variant requires more VRAM than the NVIDIA RTX 6000 Ada Generation provides (48 GB).
Nearest GPU That Fits
NVIDIA RTX PRO 5000 Blackwell (72 GB) (72 GB VRAM).
Llama 4.5 needs ~69 GB but this GPU has 48 GB. Rent a A100 (80 GB)-class GPU by the hour instead of buying one:
Affiliate links — we may earn a commission if you sign up, at no extra cost to you.
Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
FAQ
Is the NVIDIA RTX 6000 Ada Generation enough to run Llama 4.5 locally?
No — Llama 4.5 Scout at Q4_K_M needs 69.4 GB at 8K context (65.8 GB weights + 3.6 GB KV cache/overhead), and the NVIDIA RTX 6000 Ada Generation's 48 GB leaves it ~21.4 GB short. The cheapest card that runs it is the NVIDIA RTX PRO 5000 Blackwell (72 GB) (72 GB).
What's the cheapest GPU that runs Llama 4.5?
The NVIDIA RTX PRO 5000 Blackwell (72 GB) (72 GB VRAM) is the cheapest upgrade that fits it.
Llama 4.5 on Other GPUs
- Llama 4.5 on NVIDIA L40S
- Llama 4.5 on Apple M3 Pro
- Llama 4.5 on NVIDIA GeForce RTX 5090
- Llama 4.5 on Apple M4
- Llama 4.5 on Apple M2 Pro
Popular Models on the NVIDIA RTX 6000 Ada Generation
- DeepSeek R1 on NVIDIA RTX 6000 Ada Generation
- Qwen 3 on NVIDIA RTX 6000 Ada Generation
- Qwen 2.5 Family on NVIDIA RTX 6000 Ada Generation
VRAM Tier
Troubleshooting
- CUDA out of memory — why it happens and how to fix it
- Which GGUF quant should I download? (Q4 vs Q5 vs Q8)
Buying Guide
← Can I Run It? | Llama 4.5 Model Page | NVIDIA RTX 6000 Ada Generation GPU Page | VRAM calculator | Check Your Hardware