Can I Run Meta Llama 4 Scout (109B-A17B MoE) on AMD Radeon RX 7900 XTX (24GB GDDR6)?
Full VRAM footprint analysis, tokens/sec generation benchmark, and copy-paste Ollama & vLLM runtime commands for running Meta Llama 4 Scout (109B-A17B MoE) (109B) on AMD Radeon RX 7900 XTX (24GB GDDR6) (24 GB).
✕ Out of Memory — Exceeds VRAM Capacity
OLLAMA_FLASH_ATTENTION=1 OLLAMA_KV_CACHE_TYPE=q8_0 ollama run llama4:scoutLocal Hardware Configurations & Pricing
⚠️ Out of VRAM: High-Capacity Hardware Upgrades2x NVIDIA RTX 3090 Dual Rig (48GB Total VRAM)
Best price-to-VRAM homelab rig for 70B Q4_K_M & Qwen 3.8 27B Q8
Apple Mac Studio M4 Max (128GB Unified Memory)
Running Llama 4 Scout 109B & 70B Q8 locally with 128K+ context
AMD Radeon RX 7900 XTX (24GB GDDR6)
Cheapest 24GB brand-new GPU for ROCm / Ollama on Linux
⚠️ Out of VRAM? Don't downgrade model quality.
Out of VRAMSpin up an on-demand cloud GPU instance in 60 seconds with pre-installed Ollama and vLLM. (Meta Llama 4 Scout (109B-A17B MoE) @ 71.66 GB VRAM)
Quantization Precision Matrix
32K ctx • KV: Q8_0| Quantization | Weights | KV Cache | Total VRAM | Est. Speed | Fit Status |
|---|---|---|---|---|---|
| FP1616 bpw | 218 GB | 3.22 GB | 229.6 GB (957%) | 0 t/s | OOM |
| Q8_08.5 bpw | 115.54 GB | 3.22 GB | 123.55 GB (515%) | 0 t/s | OOM |
| Q6_K6.56 bpw | 89.38 GB | 3.22 GB | 96.48 GB (402%) | 0 t/s | OOM |
| Q5_K_M5.68 bpw | 77.39 GB | 3.22 GB | 84.07 GB (350%) | 0 t/s | OOM |
| Q4_K_M4.8 bpw | 65.4 GB | 3.22 GB | 71.66 GB (299%) | 0 t/s | OOM |
| FP44.25 bpw | 57.77 GB | 3.22 GB | 63.76 GB (266%) | 0 t/s | OOM |
| IQ3_XS3.3 bpw | 44.69 GB | 3.22 GB | 50.22 GB (209%) | 0 t/s | OOM |
Export Full Architecture & Infrastructure Spec
Get an executive-ready PDF report with exact memory math, hardware benchmarks, and cost comparisons.
Frequently Asked Questions: Meta Llama 4 Scout (109B-A17B MoE) on AMD Radeon RX 7900 XTX (24GB GDDR6)
How much VRAM does Meta Llama 4 Scout (109B-A17B MoE) need on AMD Radeon RX 7900 XTX (24GB GDDR6)?
At standard 4-bit quantization (Q4_K_M) with 32K context, Meta Llama 4 Scout (109B-A17B MoE) requires 71.66 GB of total VRAM (weights + KV cache + CUDA runtime overhead).
What inference speed will Meta Llama 4 Scout (109B-A17B MoE) achieve on AMD Radeon RX 7900 XTX (24GB GDDR6)?
Based on AMD Radeon RX 7900 XTX (24GB GDDR6)'s 960 GB/s memory bandwidth, expected decode speed is approximately 0 tokens per second.
Can I expand context beyond 32K tokens?
Each additional 32K tokens of context requires additional KV cache memory. For longer context windows, consider 8-bit or 4-bit KV cache quantization.