← Can It Run? — GPU compatibility matrix · Local LLMs guide
Llama 3.3 70B needs 40 GB VRAM at Q4. The Radeon RX 7900 XTX 24GB has 24 GB.
🦙 Llama 3.3 70B (Meta) is a 70B-parameter model for near-GPT-4 quality for complex tasks. Frontier-class open model, best for demanding use cases. The question is whether the Radeon RX 7900 XTX 24GB’s 24 GB of VRAM can hold it — here’s the exact math.
VRAM requirements
| Quantization | VRAM needed | Radeon RX 7900 XTX 24GB |
|---|---|---|
| Q4_K_M (recommended) | 40 GB | ❌ |
| Q8_0 (near-lossless) | 72 GB | ❌ |
Why it won’t fit (and what to do)
Llama 3.3 70B needs 40 GB at Q4 but the Radeon RX 7900 XTX 24GB has only 24 GB — you’re 16 GB short. You can offload layers to system RAM, but expect single-digit tokens/sec (painfully slow for chat).
About the Radeon RX 7900 XTX 24GB
Architecture: RDNA 3 · VRAM: 24 GB · Price: ~$900.
Good: 24GB at a good price; works with llama.cpp + ROCm/Vulkan
Watch out: AMD software stack is less plug-and-play than CUDA
Check current Radeon RX 7900 XTX 24GB price on Amazon →
Related checks
Other models on the Radeon RX 7900 XTX 24GB
🎯 LLM Hardware Checker
Enter your exact GPU + RAM, see every model you can run.
💾 VRAM Requirements
Exact VRAM per model at Q4/Q5/Q8/FP16 with context scaling.
Frequently asked questions
Can the Radeon RX 7900 XTX 24GB run Llama 3.3 70B?
No — not enough VRAM without CPU offloading. Llama 3.3 70B needs 40 GB VRAM at Q4_K_M; the Radeon RX 7900 XTX 24GB has 24 GB.
How much VRAM does Llama 3.3 70B need?
Llama 3.3 70B needs about 40 GB at Q4_K_M (recommended) and 72 GB at Q8_0.
How many tokens per second will the Radeon RX 7900 XTX 24GB get on Llama 3.3 70B?
It won't fit in VRAM; with CPU offloading expect very slow single-digit tokens/sec.
About the speed figure. The tokens/sec number above is an estimate, not a measured benchmark. Real throughput depends on your runtime and backend (Ollama, llama.cpp, vLLM), the exact quantization you download, context length, memory bandwidth, and whether any layers are offloaded to CPU. Treat it as a rough guide to the tier of performance, not a promised result.