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Can the AMD Radeon AI PRO R9700 run CogVLM2 Llama 3 Chat 19B?

36Basic quality (D) · 36 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking.

Yes, it runs great

Runs great. At Q4_K_M it needs about 18.4 GB of 32.0 GB usable, with an estimated speed of 34.7 tok/s.

Best quant
Q4_K_M
Generation speed
34.7 tok/s
Prompt processing
3,043 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)

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How it’s rated

Quality 36Basic quality (D) · 36 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking.
How capable the model itself is at Q4_K_M, from its editorial quality tier scaled by the quantization or precision. It’s the same on any hardware that runs this variant. Scale: A+ 85+ · A 70+ · B 55+ · C 40+ · D under 40.
Runs Runs great
How well it runs on the AMD Radeon AI PRO R9700: speed, capped by how well it fits in memory. Runs great: 30+ tokens/s (or near the image, video or decision speed target) · Runs well: 10+ tokens/s · Slow: 3+ tokens/s · Very slow: under 3 · Won’t run: doesn’t fit even with offload. A tight fit or RAM offload caps it at Runs well; heavy offload caps it at Slow.

Match score

To order lists, each result also gets a match score out of 100 from four parts. It favors the most capable model that still runs well.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.16.2 / 45
Memory fitFull marks when everything sits in GPU 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.14.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.13.3 / 15
Match score68.5 / 100

The match score orders results; it is not shown as a grade. Quality and Runs are the two ratings in the tables.

Every quantization on the AMD Radeon AI PRO R9700

Quant Memory needed Available Speed Runs Quality Download
Q2_K 14.3 GB 32.0 GB 57.0 tok/s Runs great 26Basic quality (D) · 26 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 62/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q3_K_M 16.0 GB 32.0 GB 44.9 tok/s Runs great 31Basic quality (D) · 31 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q4_K_M 18.4 GB 32.0 GB 34.7 tok/s Runs great 36Basic quality (D) · 36 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q5_K_M 20.3 GB 32.0 GB 28.7 tok/s Runs well 36Basic quality (D) · 36 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q6_K 22.5 GB 32.0 GB 24.1 tok/s Runs well 37Basic quality (D) · 37 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q8_0 27.2 GB 32.0 GB 17.7 tok/s Runs well 38Basic quality (D) · 38 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
F16 45.5 GB 32.0 GB 2.3 tok/s Very slowheavy RAM offload 38Basic quality (D) · 38 of 100: how capable the model is at F16, whatever it runs on. Match score 39/100 (quality, fit, speed and memory use) sets the ranking. 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

Quick answers

How much memory does CogVLM2 Llama 3 Chat 19B need on the AI PRO R9700 32GB?

At Q4_K_M it needs about 18.4 GB. The AI PRO R9700 32GB has 32.0 GB usable.

How fast is CogVLM2 Llama 3 Chat 19B on the AI PRO R9700 32GB?

About 34.7 tok/s at Q4_K_M, an estimate from the hardware’s memory bandwidth and the size of the model.

Which quantization of CogVLM2 Llama 3 Chat 19B should I use on the AI PRO R9700 32GB?

Q4_K_M. Of the versions that fit, it is the one that runs best; when two run equally well, the check prefers the higher-rated one.

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.

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