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Can the AMD Radeon RX 7900 XTX run CogVLM2 Llama 3 Chat 19B?

71 ptsGood (B) · 71 of 100 points: Model quality 16.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, it runs well

Runs well. At Q5_K_M it needs about 19.9 GB of 24.0 GB usable, with an estimated speed of 43.0 tok/s.

Best quant
Q5_K_M
Generation speed
43.0 tok/s
Prompt processing
3,904 tok/s
First token (1K prompt)
0.3 s
Largest safe context
8K

Download CogVLM2 Llama 3 Chat 19B

Original weights · Hugging Face

Full-precision files from Zhipu AI, for fine-tuning, vLLM, Transformers.

huggingface.co/zai-org/cogvlm2-llama3-chat-19B (opens in a new tab)

No sign-in needed.

Links checked 1 week ago against Hugging Face, Ollama and GitHub.

How the B grade is scored

Every result gets up to 100 points from four parts. The points decide the letter grade.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.16.6 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.15.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.15.0 / 15
Total71.6 / 10071 ptsGood (B) · 71 of 100 points: Model quality 16.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every quantization on the AMD Radeon RX 7900 XTX

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 13.9 GB 24.0 GB 85.5 tok/s Runs well 65 ptsGood (B) · 65 of 100 points: Model quality 12.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.4/15 All files (opens in a new tab)
Q3_K_M 15.6 GB 24.0 GB 67.3 tok/s Runs well 69 ptsGood (B) · 69 of 100 points: Model quality 14.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q4_K_M 18.0 GB 24.0 GB 52.0 tok/s Runs well 71 ptsGood (B) · 71 of 100 points: Model quality 16.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q5_K_M 19.9 GB 24.0 GB 43.0 tok/s Runs well 71 ptsGood (B) · 71 of 100 points: Model quality 16.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q6_K 22.1 GB 24.0 GB 36.1 tok/s Tight fit 70 ptsGood (B) · 70 of 100 points: Model quality 16.9/45, Memory fit 24.0/25, Speed 14.3/15, Memory use 15.0/15 All files (opens in a new tab)
Q8_0 26.8 GB 24.0 GB 10.5 tok/s Runs with offload 49 ptsUsable (C) · 49 of 100 points: Model quality 17.1/45, Memory fit 10.0/25, Speed 7.7/15, Memory use 15.0/15 All files (opens in a new tab)
F16 45.1 GB 24.0 GB — Won't run 5 ptsWon't run (F) · 5 of 100 points: Model quality 5.1/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 Original weights (opens in a new tab)

Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.

Other hardware that runs it

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.