Zamba2 2.7B Instruct on Intel Core Ultra 5 325H NAS (32 GB)

Can the Intel Core Ultra 5 325H NAS (32 GB) run Zamba2 2.7B Instruct?

Yes, it runs great

Runs great. At Q4_K_M it needs about 4.7 GB of 26.2 GB usable, with an estimated speed of 36.1 tok/s.

Best quant: Q4_K_M
Generation speed: 36.1 tok/s
Prompt processing: 207 tok/s
First token (1K prompt): 5.0 s
Largest safe context: 4K

Download Zamba2 2.7B Instruct

Original weights · Hugging Face

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

huggingface.co/Zyphra/Zamba2-2.7B-instruct (opens in a new tab)

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Links checked 2 days ago against Hugging Face, Ollama and GitHub.

How it’s rated

Quality 20Basic quality (D) · 20 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 52/100 (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 Intel Core Ultra 5 325H NAS (32 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.	9.4 / 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.	14.2 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	4.1 / 15
Match score	52.8 / 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 Core Ultra 5 325H NAS (32 GB)

Quant	Memory needed	Available	Speed	Runs	Quality	Download
`Q2_K`	4.1 GB	26.2 GB	59.3 tok/s	Runs great	15Basic quality (D) · 15 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 50/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`Q3_K_M`	4.4 GB	26.2 GB	46.7 tok/s	Runs great	18Basic quality (D) · 18 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 52/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`Q4_K_M`	4.7 GB	26.2 GB	36.1 tok/s	Runs great	20Basic quality (D) · 20 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 52/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`Q5_K_M`	5.0 GB	26.2 GB	29.8 tok/s	Runs well	21Basic quality (D) · 21 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 51/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`Q6_K`	5.3 GB	26.2 GB	25.0 tok/s	Runs well	21Basic quality (D) · 21 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 51/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`Q8_0`	5.9 GB	26.2 GB	18.4 tok/s	Runs well	22Basic quality (D) · 22 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 50/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`F16`	8.4 GB	26.2 GB	8.5 tok/s	Slow	22Basic quality (D) · 22 of 100: how capable the model is at F16, whatever it runs on. Match score 49/100 (quality, fit, speed and memory use) sets the ranking.	Original weights (opens in a new tab)

Memory figures assume 4K of context. Longer conversations or documents grow the KV cache.

Other hardware that runs it

22Basic quality (D) · 22 of 100: how capable the model is at F16, whatever it runs on. Match score 63/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 4070 SUPER F16 · 54.6 tok/s · Runs great
22Basic quality (D) · 22 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 62/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 4060 Q8_0 · 63.9 tok/s · Runs great
22Basic quality (D) · 22 of 100: how capable the model is at F16, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking. AMD Radeon RX 9070 XT F16 · 59.7 tok/s · Runs great
22Basic quality (D) · 22 of 100: how capable the model is at F16, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 4070 Ti SUPER F16 · 72.8 tok/s · Runs great
22Basic quality (D) · 22 of 100: how capable the model is at F16, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 4080 SUPER F16 · 79.7 tok/s · Runs great
22Basic quality (D) · 22 of 100: how capable the model is at F16, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 5060 Ti 16GB F16 · 48.5 tok/s · Runs great

Quick answers

How much memory does Zamba2 2.7B Instruct need on the Intel Core Ultra 5 325H NAS 32GB?

At Q4_K_M it needs about 4.7 GB. The Intel Core Ultra 5 325H NAS 32GB has 26.2 GB usable.

How fast is Zamba2 2.7B Instruct on the Intel Core Ultra 5 325H NAS 32GB?

About 36.1 tok/s at Q4_K_M, an estimate from the hardware’s memory bandwidth and the size of the model.

Which quantization of Zamba2 2.7B Instruct should I use on the Intel Core Ultra 5 325H NAS 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.