What quantization should I use for Qwen2.5-3B-Instruct on a AMD Radeon RX 7900 XTX?

Q8_0 is the highest-quality quant that grades B or better on this hardware with llama.cpp at 8K context; the per-quant table on this page grades all 4 available quants.

Can an AMD Radeon RX 7900 XTX run Qwen2.5-3B-Instruct?

Yes. Qwen2.5-3B-Instruct needs 4.01GB at Q8_0 with llama.cpp and 8K context; the AMD Radeon RX 7900 XTX has 24GB of VRAM (23.5GB usable) — grade A, with decode speed in the interactive tier.

AMD Radeon RX 7900 XTX · Qwen2.5-3B-Instruct · Q8_0

✅ Fits — grade A

InteractivebetaROCm/Vulkan performance not yet calibrated

weights 3.29 GBKV cache 0.30 GBoverhead 0.42 GBpool 23.5 GBneeds 4.01 GB

assumes llama.cpp · batch 1 · 8K context · fp16 KV cache

Also runs with: Ollama (one-line install) · LM Studio (GUI) · KoboldCpp (GUI)

$999 MSRP · as of 2026-07-08

Also good for gaming — 4K-class (estimated from FP32 compute, not a game benchmark).

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Adjust assumptions — runtime, context, GPU count →

Every quant, graded

AMD Radeon RX 7900 XTX × Qwen2.5-3B-Instruct, llama.cpp, 8K context.

Quant	File size	Fit	Speed tier
Q8_0	3.3 GB	Fits · A	interactive · beta
Q6_K	2.5 GB	Fits · A	interactive · beta
Q5_K_M	2.2 GB	Fits · A	interactive · beta
Q4_K_M	1.9 GB	Fits · A	interactive · beta

Qwen2.5-3B-Instruct on similar hardware

More models on the AMD Radeon RX 7900 XTX

Verdict computed from published specs and measured GGUF file sizes — see how the math works.