mxbai-rerank-base v2 on Intel Core Ultra 5 225 / 7 265 / 9 285 (desktop) NAS (32 GB)

Can the Intel Core Ultra 5 225 / 7 265 / 9 285 (desktop) NAS (32 GB) run mxbai-rerank-base v2?

Yes, but slowly

Slow. At Q8_0 it needs about 3.2 GB of 26.2 GB usable and makes one decision in about 537 ms.

Best quant: Q8_0
Time per decision: 537 ms
Decisions per second: 1.9/s
Input assumed: 512 tokens
Returns: Probability or score

Download mxbai-rerank-base v2

Original weights · Hugging Face

Full-precision files from Mixedbread, for Transformers, Sentence Transformers, Text Embeddings Inference, Infinity or vLLM.

huggingface.co/mixedbread-ai/mxbai-rerank-base-v2 (opens in a new tab)

No sign-in needed.

Links checked 5 hours ago against Hugging Face, Ollama and GitHub.

How it’s rated

Quality 76Great quality (A) · 76 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking.: How capable the model itself is at Q8_0, 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 Core Ultra 5 225 / 7 265 / 9 285 (desktop) 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.

PrecisionEditorial precision tier from the model’s published benchmarks, scaled by the quantization or precision used.	34.2 / 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
SpeedTime for one decision against a 100 ms target: reading the input plus any tokens the model writes.	6.5 / 15
ClarityHow easy the answer is to use in code: a probability or score earns the most, written feedback before a score the least.	15.0 / 15
Match score	80.7 / 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 5 225 / 7 265 / 9 285 (desktop) NAS (32 GB)

Quant	Memory needed	Available	Speed	Runs	Quality	Download
`Q4_K_M`	3.0 GB	26.2 GB	532 ms	Slow	72Great quality (A) · 72 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`Q5_K_M`	3.1 GB	26.2 GB	533 ms	Slow	73Great quality (A) · 73 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`Q6_K`	3.1 GB	26.2 GB	534 ms	Slow	75Great quality (A) · 75 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`Q8_0`	3.2 GB	26.2 GB	537 ms	Slow	76Great quality (A) · 76 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`F16`	3.7 GB	26.2 GB	549 ms	Slow	76Great quality (A) · 76 of 100: how capable the model is at F16, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking.	Original weights (opens in a new tab)

Times are for one request with a 512-token input and about 1 tokens written. Batching servers process many requests at once.

Other hardware that runs it

76Great quality (A) · 76 of 100: how capable the model is at F16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. AMD Radeon RX 7900 XTX F16 · 9.4 ms · Runs great
76Great quality (A) · 76 of 100: how capable the model is at F16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. AMD Radeon RX 9070 XT F16 · 11 ms · Runs great
76Great quality (A) · 76 of 100: how capable the model is at F16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. AMD Ryzen AI Max+ 395 (128 GB) F16 · 19 ms · Runs great
76Great quality (A) · 76 of 100: how capable the model is at F16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. Apple M1 Max (64 GB) F16 · 48 ms · Runs great
76Great quality (A) · 76 of 100: how capable the model is at F16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. Apple M2 Ultra (192 GB) F16 · 21 ms · Runs great
76Great quality (A) · 76 of 100: how capable the model is at F16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. Apple M3 Ultra (256 GB) F16 · 21 ms · Runs great

Quick answers

How much memory does mxbai-rerank-base v2 need on the Intel Core Ultra 5 225 / 7 265 / 9 285 (desktop) NAS 32GB?

At Q8_0 it needs about 3.2 GB. The Intel Core Ultra 5 225 / 7 265 / 9 285 (desktop) NAS 32GB has 26.2 GB usable.

How fast is mxbai-rerank-base v2 on the Intel Core Ultra 5 225 / 7 265 / 9 285 (desktop) NAS 32GB?

It makes one decision in about 537 ms at Q8_0, an estimate from the hardware and the size of the model.

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.