DynaGuard 8B on UP Squared Pro 7000 (4 GB)

Can the UP Squared Pro 7000 (4 GB) run DynaGuard 8B?

No, it doesn’t fit

No. DynaGuard 8B needs about 6.1 GB even at Q4_K_M; the UP Squared Pro 7000 (4 GB) has 2.0 GB usable.

Download DynaGuard 8B

Recommended: Q4_K_M. Every other quantization has its own download link in the table below.

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

Download the Q4_K_M file (opens in a new tab)

huggingface.co/mradermacher/DynaGuard-8B-GGUF (opens in a new tab)

ollama run hf.co/mradermacher/DynaGuard-8B-GGUF:Q4_K_M

Original weights · Hugging Face

Full-precision files from University of Maryland, for fine-tuning, vLLM, Transformers.

huggingface.co/tomg-group-umd/DynaGuard-8B (opens in a new tab)

No sign-in needed.

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

How it’s rated

Quality 75Great quality (A) · 75 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 10/100 (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 Won't run: How well it runs on the UP Squared Pro 7000 (4 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.	10.1 / 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
SpeedTime for one decision against a 100 ms target: reading the input plus any tokens the model writes.	0.0 / 15
ClarityHow easy the answer is to use in code: a probability or score earns the most, written feedback before a score the least.	0.0 / 15
Match score	10.1 / 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 (4 GB)

Quant	Memory needed	Available	Speed	Runs	Quality	Download
`Q4_K_M`	6.1 GB	2.0 GB	—	Won't run	75Great quality (A) · 75 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 10/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)
`Q5_K_M`	6.9 GB	2.0 GB	—	Won't run	76Great quality (A) · 76 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 10/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)
`Q6_K`	7.8 GB	2.0 GB	—	Won't run	78Great quality (A) · 78 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 10/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)
`Q8_0`	9.7 GB	2.0 GB	—	Won't run	79Great quality (A) · 79 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 10/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)
`F16`	17.4 GB	2.0 GB	—	Won't run	79Great quality (A) · 79 of 100: how capable the model is at F16, whatever it runs on. Match score 10/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab) Original weights (opens in a new tab)

Times are for one request with a 512-token input and about 160 tokens written. Batching servers process many requests at once.

Hardware that can run it

75Great quality (A) · 75 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA B200 Q4_K_M · 174 ms · Runs well
78Great quality (A) · 78 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. AMD Instinct MI350X Q6_K · 277 ms · Runs well
78Great quality (A) · 78 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip Q6_K · 293 ms · Runs well
78Great quality (A) · 78 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. AMD Instinct MI325X Q6_K · 343 ms · Runs well
78Great quality (A) · 78 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA H200 141GB SXM Q6_K · 368 ms · Runs well
78Great quality (A) · 78 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA H200 NVL Q6_K · 373 ms · Runs well

Models that do run on the UP Squared Pro 7000 (4 GB)

80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. GLiNER2.5 Decide Q8_0 · 198 ms
68Good quality (B) · 68 of 100: how capable the model is at F16, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. Llama Prompt Guard 2 22M F16 · 69 ms
86Excellent quality (A+) · 86 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3.5 Q8_0 · 473 ms
74Great quality (A) · 74 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. GLiClass ModernBERT Large v3 Q8_0 · 162 ms
70Great quality (A) · 70 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. GTE Reranker ModernBERT Base Q8_0 · 123 ms

Quick answers

How much memory does DynaGuard 8B need on the UP Squared Pro 7000 4GB?

Even at Q4_K_M it needs about 6.1 GB; the UP Squared Pro 7000 4GB has 2.0 GB usable.

What can the UP Squared Pro 7000 4GB run instead?

GLiNER2.5 Decide, Llama Prompt Guard 2 22M and Jina Reranker v3.5 run best on it; the page lists more, each with its speed.

What hardware can run DynaGuard 8B?

NVIDIA B200 180GB, AMD Instinct MI350X 288GB and NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip 252GB 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.