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Can the Marvell OCTEON TX2 CN9130 NAS (32 GB) run GLiDE 0.8B?

7Basic quality (D) · 7 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 41/100 (quality, fit, speed and memory use) sets the ranking.

Yes, it runs well

Runs well. At Q2_K it needs about 3.1 GB of 26.2 GB usable, with an estimated speed of 17.9 tok/s.

Best quant
Q2_K
Generation speed
17.9 tok/s
Prompt processing
16.7 tok/s
First token (1K prompt)
61.4 s
Largest safe context
256K

Download GLiDE 0.8B

Original weights · Hugging Face

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

huggingface.co/fastino/GLiDE-0.8B (opens in a new tab)

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

How it’s rated

Quality 7Basic quality (D) · 7 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 41/100 (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 well
How well it runs on the Marvell OCTEON TX2 CN9130 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.3.5 / 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.10.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.2.7 / 15
Match score41.2 / 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 Marvell OCTEON TX2 CN9130 NAS (32 GB)

Quant Memory needed Available Speed Runs Quality Download
Q2_K 3.1 GB 26.2 GB 17.9 tok/s Runs well 7Basic quality (D) · 7 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 41/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q3_K_M 3.2 GB 26.2 GB 14.1 tok/s Runs well 9Basic quality (D) · 9 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 40/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q4_K_M 3.3 GB 26.2 GB 10.9 tok/s Runs well 10Basic quality (D) · 10 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 40/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q5_K_M 3.3 GB 26.2 GB 9.0 tok/s Slow 10Basic quality (D) · 10 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 39/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q6_K 3.4 GB 26.2 GB 7.6 tok/s Slow 10Basic quality (D) · 10 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 39/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q8_0 3.6 GB 26.2 GB 5.6 tok/s Slow 11Basic quality (D) · 11 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 38/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
F16 4.3 GB 26.2 GB 2.6 tok/s Very slow 11Basic quality (D) · 11 of 100: how capable the model is at F16, whatever it runs on. Match score 37/100 (quality, fit, speed and memory use) sets the ranking. Original weights (opens in a new tab)

Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.

Other hardware that runs it

Quick answers

How much memory does GLiDE 0.8B need on the Marvell OCTEON TX2 CN9130 NAS 32GB?

At Q2_K it needs about 3.1 GB. The Marvell OCTEON TX2 CN9130 NAS 32GB has 26.2 GB usable.

How fast is GLiDE 0.8B on the Marvell OCTEON TX2 CN9130 NAS 32GB?

About 17.9 tok/s at Q2_K, an estimate from the hardware’s memory bandwidth and the size of the model.

Which quantization of GLiDE 0.8B should I use on the Marvell OCTEON TX2 CN9130 NAS 32GB?

Q2_K. 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.

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