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Can the Intel Xeon D-2700 series NAS (512 GB) run CogVLM2 Llama 3 Chat 19B?

31Basic quality (D) · 31 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 46/100 (quality, fit, speed and memory use) sets the ranking.

Yes, but slowly

Slow. At Q3_K_M it needs about 52.1 GB of 471 GB usable, with an estimated speed of 3.4 tok/s.

Best quant
Q3_K_M
Generation speed
3.4 tok/s
Prompt processing
17.8 tok/s
First token (1K prompt)
57.4 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 31Basic quality (D) · 31 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 46/100 (quality, fit, speed and memory use) sets the ranking.
How capable the model itself is at Q3_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 Slow
How well it runs on the Intel Xeon D-2700 series NAS (512 GB): 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.14.4 / 45
Memory fitFull marks when the model fits in the share of the NAS’s memory that models can use (the rest stays with the NAS system and its storage services); fewer when it goes past that limit.25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.4.3 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.2.6 / 15
Match score46.3 / 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 Intel Xeon D-2700 series NAS (512 GB)

Quant Memory needed Available Speed Runs Quality Download
Q2_K 50.4 GB 471 GB 4.3 tok/s Slow 26Basic quality (D) · 26 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 44/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q3_K_M 52.1 GB 471 GB 3.4 tok/s Slow 31Basic quality (D) · 31 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 46/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q4_K_M 54.5 GB 471 GB 2.6 tok/s Very slow 36Basic quality (D) · 36 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 47/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q5_K_M 56.4 GB 471 GB 2.1 tok/s Very slow 36Basic quality (D) · 36 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 47/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q6_K 58.6 GB 471 GB 1.8 tok/s Very slow 37Basic quality (D) · 37 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 47/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q8_0 63.2 GB 471 GB 1.3 tok/s Very slow 38Basic quality (D) · 38 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 47/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
F16 81.6 GB 471 GB 0.6 tok/s Very slow 38Basic quality (D) · 38 of 100: how capable the model is at F16, whatever it runs on. Match score 47/100 (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

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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