Can Desktop PC · RTX PRO 6000 Blackwell · 128 GB RAM run Llama 4 Scout (109B-A17B)?
96 GB VRAM + 128 GB RAM · 1792 GB/s memory bandwidth · Llama 4 Scout (109B-A17B) has 108.6B parameters (17B active per token).
Short answer
Yes, excellent for chat and acceptable or better for every workload we test.
Best quantization for chat: Q5_K_M (73 GB of weights) on Ollama. Generation: 55–70 tok/s, leaving about 20 GB free for your other apps.
How it rates for each workload
Same model and machine, different jobs. Agents and long documents send far bigger prompts than chat, so they need much more speed and memory.
| Workload | Verdict | Quant | Generation | First reply | Context | |
|---|---|---|---|---|---|---|
| Chatwith Open WebUI | Excellent | Q5_K_M | 55–70 tok/s | under 1 s | 8K | Details |
| Coding questionswith Continue | Comfortable | Q6_K | 45–60 tok/s | ≈2 s | 16K | Details |
| Coding in a repositorywith Aider | Acceptable | Q6_K | 40–55 tok/s | ≈6 s | 32K | Details |
| Agentic codingwith OpenCode | Acceptable | Q6_K | 35–50 tok/s | ≈9 s | 32K | Details |
| Long documents (64K)with Open WebUI | Excellent | Q5_K_M | 30–40 tok/s | ≈30 s | 64K | Details |
Speeds are estimates calibrated against measured benchmarks on similar hardware. “First reply” is the time to read the workload’s opening prompt. How we calculate
Get it running
Copy-paste commands for the Q5_K_M build with a 64K context. Ollama and llama.cpp download the file straight from Hugging Face.
ollama run hf.co/unsloth/Llama-4-Scout-17B-16E-Instruct-GGUF:Q5_K_M
This build is split into 2 files, which Ollama can't import from Hugging Face. Use llama.cpp or LM Studio instead.
Other models for Desktop PC · RTX PRO 6000 Blackwell · 128 GB RAM
The best-rated models for chat on this machine.
- Qwen3.6 35B-A3B260–360 tok/sExcellent
- Qwen3-Next 80B-A3B Instruct260–360 tok/sExcellent
- gpt-oss-120b≈180 tok/sExcellent
- Gemma 4 26B-A4B210–280 tok/sExcellent
- Qwen3.5 35B-A3B260–360 tok/sExcellent
- LFM2.5 24B-A2B530–720 tok/sExcellent
Cheapest machines for Llama 4 Scout (109B-A17B)
Hardware rated comfortable or better for chat, lowest price first.
- Ryzen AI Max+ 395 mini PC / Framework Desktop · 128 GB$2,000 · 11–16 tok/sComfortable
- Mac Studio M2 Max 96 GB$3,799 · 18–25 tok/sExcellent
- MacBook Pro M3 Max 96 GB$3,999 · 14–19 tok/sComfortable
- Mac Studio M5 Max 128 GB$4,099 · 20–35 tok/sExcellent
- Mac Studio M4 Max 128 GB$4,099 · 25–30 tok/sExcellent
- MacBook Pro M2 Max 96 GB$5,099 · 18–25 tok/sExcellent
Different tool, context size or workload?
These pages use typical settings. The full check models your exact setup.