Q: What quantization of CodeLlama 34B should I use on a AMD Radeon RX 6950 XT?

For 16 GB VRAM on the AMD Radeon RX 6950 XT, the Q4_K_M variant is the best fit. Estimated ~8 tokens/sec on the Q4_K_M quantization.

Q: How fast does CodeLlama 34B run on AMD Radeon RX 6950 XT?

Roughly 8 tokens/sec for Q4_K_M. Real speed depends on context length, backend (Ollama, llama.cpp, LM Studio), and KV cache size.

Q: What if AMD Radeon RX 6950 XT is not enough for CodeLlama 34B?

Consider upgrading to NVIDIA GeForce RTX 4090 (24 GB VRAM) which fits the recommended 24 GB target. Or pick a smaller quantization to stay on your current card.

Question 1

Can I run CodeLlama 34B on a AMD Radeon RX 6950 XT?

Accepted Answer

Sort of — AMD Radeon RX 6950 XT can run CodeLlama 34B (Q4_K_M) only by spilling layers to RAM. Generation will be slow. CPU + GPU hybrid — not enough VRAM (16 GB < 22 GB min), but 64 GB RAM is sufficient. Expect significantly slower inference.

Question 2

What quantization of CodeLlama 34B should I use on a AMD Radeon RX 6950 XT?

Accepted Answer

For 16 GB VRAM on the AMD Radeon RX 6950 XT, the Q4_K_M variant is the best fit. Estimated ~8 tokens/sec on the Q4_K_M quantization.

Question 3

How fast does CodeLlama 34B run on AMD Radeon RX 6950 XT?

Accepted Answer

Roughly 8 tokens/sec for Q4_K_M. Real speed depends on context length, backend (Ollama, llama.cpp, LM Studio), and KV cache size.

Question 4

What if AMD Radeon RX 6950 XT is not enough for CodeLlama 34B?

Accepted Answer

Consider upgrading to NVIDIA GeForce RTX 4090 (24 GB VRAM) which fits the recommended 24 GB target. Or pick a smaller quantization to stay on your current card.

Can I Run CodeLlama 34B on AMD Radeon RX 6950 XT?

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Every CodeLlama 34B quantization on AMD Radeon RX 6950 XT

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