Snowflake Arctic Instruct on UP Squared Pro 7000 (8 GB)

Can the UP Squared Pro 7000 (8 GB) run Snowflake Arctic Instruct?

No, it doesn’t fit

No. Snowflake Arctic Instruct needs about 193 GB even at Q2_K; the UP Squared Pro 7000 (8 GB) has 4.0 GB usable.

Download Snowflake Arctic Instruct

Original weights · Hugging Face

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

huggingface.co/Snowflake/snowflake-arctic-instruct (opens in a new tab)

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Links checked 3 days ago against Hugging Face, Ollama and GitHub.

How it’s rated

Quality 35Basic quality (D) · 35 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 4/100 (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 Won't run: How well it runs on the UP Squared Pro 7000 (8 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.	4.7 / 45
Memory fitFull marks when the model fits in the share of unified memory the GPU can use; fewer when it goes past that limit.	0.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	0.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	0.0 / 15
Match score	4.7 / 100

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

It doesn’t fit, so only a reduced share of the quality points counts and fit, speed and memory use score zero.

Every quantization on the UP Squared Pro 7000 (8 GB)

Quant	Memory needed	Available	Speed	Runs	Quality	Download
`Q2_K`	193 GB	4.0 GB	—	Won't run	35Basic quality (D) · 35 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 4/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`Q3_K_M`	236 GB	4.0 GB	—	Won't run	42Fair quality (C) · 42 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 5/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`Q4_K_M`	293 GB	4.0 GB	—	Won't run	47Fair quality (C) · 47 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 6/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`Q5_K_M`	341 GB	4.0 GB	—	Won't run	48Fair quality (C) · 48 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 6/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`Q6_K`	394 GB	4.0 GB	—	Won't run	49Fair quality (C) · 49 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 6/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`Q8_0`	509 GB	4.0 GB	—	Won't run	50Fair quality (C) · 50 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 6/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`F16`	959 GB	4.0 GB	—	Won't run	50Fair quality (C) · 50 of 100: how capable the model is at F16, whatever it runs on. Match score 6/100 (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.

Hardware that can run it

47Fair quality (C) · 47 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. Apple M3 Ultra (512 GB) Q4_K_M · 43.5 tok/s · Runs great
35Basic quality (D) · 35 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 55/100 (quality, fit, speed and memory use) sets the ranking. Apple M3 Ultra (256 GB) Q2_K · 56.4 tok/s · Runs well (over GPU memory limit)
47Fair quality (C) · 47 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. Apple M5 Ultra (512 GB) Q4_K_M · 59.6 tok/s · Runs great
42Fair quality (C) · 42 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. AMD Instinct MI325X Q3_K_M · 188 tok/s · Runs well (tight fit)
42Fair quality (C) · 42 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. AMD Instinct MI350X Q3_K_M · 209 tok/s · Runs well (tight fit)
42Fair quality (C) · 42 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip Q3_K_M · 211 tok/s · Runs well (tight fit)

Models that do run on the UP Squared Pro 7000 (8 GB)

57Good quality (B) · 57 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. MiniCPM5 2B Q4_K_M · 14.3 tok/s
57Good quality (B) · 57 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. Nemotron Labs Dory 1.0 4B Q3_K_M · 11.7 tok/s
42Fair quality (C) · 42 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. Unlimited OCR 2 (3B-A0.6B) Q5_K_M · 42.2 tok/s
52Fair quality (C) · 52 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 E2B Q3_K_M · 20.2 tok/s
55Good quality (B) · 55 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. Spark-X2.6 4B Q3_K_M · 11.3 tok/s

Quick answers

How much memory does Snowflake Arctic Instruct need on the UP Squared Pro 7000 8GB?

Even at Q2_K it needs about 193 GB; the UP Squared Pro 7000 8GB has 4.0 GB usable.

What can the UP Squared Pro 7000 8GB run instead?

MiniCPM5 2B, Nemotron Labs Dory 1.0 4B and Unlimited OCR 2 (3B-A0.6B) run best on it; the page lists more, each with its speed.

What hardware can run Snowflake Arctic Instruct?

M3 Ultra 512GB, M3 Ultra 256GB and M5 Ultra 512GB run it; the page lists more, each with its speed.

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.