Can RX 7900 GRE 16GB run Qwen2.5-72B-Instruct?

AMD · 16 GB GDDR6 · 576 GB/s bandwidth · Alibaba · 72.7B · model ctx up to 128K

No — Qwen2.5-72B-Instruct at Q4 needs ≈ 48.26 GB even at 4K context, beyond the RX 7900 GRE 16GB's 16 GB GDDR6. It would only run with heavy CPU/disk offload. Decode at Q4/8K: ≈ 1.2 tok/s (estimated, batch 1). FP16 needs ≈ 160.94 GB — does not fit on this card. Estimates come from memory-bandwidth math; rows tagged measured override estimates. Relative ranking is more reliable than absolute tok/s. Methodology.

Fit & speed by quant and context

Quant	Context	VRAM needed	Fits?	tok/s (decode)
Q4	4K	48.26 GB	No	1.6 est.
Q4	8K default	55.53 GB	No	1.2 est.
Q4	32K	99.15 GB	No	—
FP16	4K	153.67 GB	No	—
FP16	8K default	160.94 GB	No	—
FP16	32K	204.56 GB	No	—

Fits = weights + KV(ctx) + 1 GB overhead ≤ 95% of VRAM. Measured anchors are context-agnostic; the fit verdict is recomputed per context. A missing tok/s means the model is far beyond this card (offload-only territory).

VRAM breakdown at 8K context

Quant	Weights	KV cache	Overhead	Total needed	RX 7900 GRE 16GB VRAM
Q4	39.99 GB	14.54 GB	1 GB	55.53 GB	16 GB
FP16	145.4 GB	14.54 GB	1 GB	160.94 GB	16 GB

Other GPUs that run Qwen2.5-72B-Instruct

• B200 192GB SXM — ≈70.0 tok/s Q4 est.
• MI300X 192GB — ≈46.4 tok/s Q4 est.
• H200 141GB SXM5 — ≈42.0 tok/s Q4 est.
• H100 80GB SXM5 — ≈29.3 tok/s Q4 est.
• Gaudi 3 128GB — ≈28.7 tok/s Q4 est.
• A100 80GB SXM4 — ≈16.47 tok/s Q4 measured
• MacBook Pro M4 Max 128GB — ≈11.0 tok/s Q4 measured
• Mac Studio M3 Ultra 96GB — ≈7.2 tok/s Q4 est.

All GPUs for Qwen2.5-72B-Instruct →

Other models for the RX 7900 GRE 16GB

• Qwen3-0.6B — ≈458.2 tok/s Q4 est.
• gemma-3-1b-it — ≈366.5 tok/s Q4 est.
• Llama-3.2-1B-Instruct — ≈305.5 tok/s Q4 est.
• Qwen3-1.7B — ≈183.3 tok/s Q4 est.
• Llama-3.2-3B-Instruct — ≈114.5 tok/s Q4 est.
• gpt-oss-20b — ≈101.8 tok/s Q4 est.
• Phi-4-mini-instruct — ≈96.5 tok/s Q4 est.
• Phi-4-mini-reasoning — ≈96.5 tok/s Q4 est.

All models on the RX 7900 GRE 16GB →