on

Can the AMD EPYC 7002 / 7003 series NAS (512 GB) run OLMo 7B Instruct?

9Basic quality (D) · 9 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 45/100 (quality, fit, speed and memory use) sets the ranking.

Yes, it runs great

Runs great. At Q2_K it needs about 42.1 GB of 471 GB usable, with an estimated speed of 33.3 tok/s.

Best quant
Q2_K
Generation speed
33.3 tok/s
Prompt processing
58.1 tok/s
First token (1K prompt)
17.6 s
Largest safe context
2K

Download OLMo 7B Instruct

Original weights · Hugging Face

Full-precision files from Ai2, for fine-tuning, vLLM, Transformers.

huggingface.co/allenai/OLMo-7B-Instruct-hf (opens in a new tab)

No sign-in needed.

How it’s rated

Quality 9Basic quality (D) · 9 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 45/100 (quality, fit, speed and memory use) sets the ranking.
How capable the model itself is at Q2_K, 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 EPYC 7002 / 7003 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.4.4 / 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.13.7 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.2.1 / 15
Match score45.2 / 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 EPYC 7002 / 7003 series NAS (512 GB)

Quant Memory needed Available Speed Runs Quality Download
Q2_K 42.1 GB 471 GB 33.3 tok/s Runs great 9Basic quality (D) · 9 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 45/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q3_K_M 42.7 GB 471 GB 26.2 tok/s Runs well 11Basic quality (D) · 11 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 44/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q4_K_M 43.6 GB 471 GB 20.3 tok/s Runs well 13Basic quality (D) · 13 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 43/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q5_K_M 44.2 GB 471 GB 16.7 tok/s Runs well 13Basic quality (D) · 13 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 42/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q6_K 45.0 GB 471 GB 14.1 tok/s Runs well 13Basic quality (D) · 13 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 42/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q8_0 46.7 GB 471 GB 10.3 tok/s Runs well 14Basic quality (D) · 14 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 41/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
F16 53.1 GB 471 GB 4.8 tok/s Slow 14Basic quality (D) · 14 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 2K 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.

Was this page helpful?