Qwen AgentWorld 35B-A3B on Marvell OCTEON TX2 CN9130 NAS (4 GB)

Can the Marvell OCTEON TX2 CN9130 NAS (4 GB) run Qwen AgentWorld 35B-A3B?

No, it doesn’t fit

No. Qwen AgentWorld 35B-A3B needs about 14.8 GB even at Q2_K; the Marvell OCTEON TX2 CN9130 NAS (4 GB) has 2.0 GB usable.

Download Qwen AgentWorld 35B-A3B

Recommended: Q2_K. 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 Q2_K (UD-Q2_K_XL) file (opens in a new tab)

huggingface.co/unsloth/Qwen-AgentWorld-35B-A3B-GGUF (opens in a new tab)

ollama run hf.co/unsloth/Qwen-AgentWorld-35B-A3B-GGUF:UD-Q2_K_XL

Original weights · Hugging Face

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

huggingface.co/Qwen/Qwen-AgentWorld-35B-A3B (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 60Good quality (B) · 60 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 8/100 (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 Marvell OCTEON TX2 CN9130 NAS (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.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.	8.2 / 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.	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	8.2 / 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 Marvell OCTEON TX2 CN9130 NAS (4 GB)

Quant	Memory needed	Available	Speed	Runs	Quality	Download
`Q2_K`	14.8 GB	2.0 GB	—	Won't run	60Good quality (B) · 60 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 8/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (UD-Q2_K_XL) (opens in a new tab)
`Q3_K_M`	17.9 GB	2.0 GB	—	Won't run	73Great quality (A) · 73 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 9/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)
`Q4_K_M`	22.1 GB	2.0 GB	—	Won't run	82Great quality (A) · 82 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 11/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)
`Q5_K_M`	25.5 GB	2.0 GB	—	Won't run	84Great quality (A) · 84 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 11/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)
`Q6_K`	29.3 GB	2.0 GB	—	Won't run	86Excellent quality (A+) · 86 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 11/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)
`Q8_0`	37.7 GB	2.0 GB	—	Won't run	87Excellent quality (A+) · 87 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 11/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)
`F16`	70.2 GB	2.0 GB	—	Won't run	87Excellent quality (A+) · 87 of 100: how capable the model is at F16, whatever it runs on. Match score 11/100 (quality, fit, speed and memory use) sets the ranking.	GGUF · folder (opens in a new tab) Original weights (opens in a new tab)

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

Hardware that can run it

87Excellent quality (A+) · 87 of 100: how capable the model is at F16, whatever it runs on. Match score 94/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA RTX PRO 6000 Blackwell F16 · 98.2 tok/s · Runs great
86Excellent quality (A+) · 86 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking. Apple M1 Max (64 GB) Q6_K · 72.3 tok/s · Runs great
86Excellent quality (A+) · 86 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking. Apple M4 Max (64 GB) Q6_K · 90.1 tok/s · Runs great
84Great quality (A) · 84 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. Apple M4 Pro (48 GB) Q5_K_M · 62.2 tok/s · Runs great
84Great quality (A) · 84 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 5090 Q5_K_M · 194 tok/s · Runs great
87Excellent quality (A+) · 87 of 100: how capable the model is at F16, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. Apple M2 Ultra (192 GB) F16 · 51.3 tok/s · Runs great

Models that do run on the Marvell OCTEON TX2 CN9130 NAS (4 GB)

53Fair quality (C) · 53 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. LFM3 1.7B Q4_K_M · 4.7 tok/s
35Basic quality (D) · 35 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 63/100 (quality, fit, speed and memory use) sets the ranking. PaddleOCR-VL 1.6 0.9B Q3_K_M · 11.0 tok/s
42Fair quality (C) · 42 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 63/100 (quality, fit, speed and memory use) sets the ranking. LFM3-VL 2B Q3_K_M · 5.5 tok/s
38Basic quality (D) · 38 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking. MiniCPM-V 4.7 1B Q4_K_M · 5.3 tok/s
29Basic quality (D) · 29 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking. MiniCPM-OCR 1.0 1.3B Q2_K · 10.3 tok/s

Quick answers

How much memory does Qwen AgentWorld 35B-A3B need on the Marvell OCTEON TX2 CN9130 NAS 4GB?

Even at Q2_K it needs about 14.8 GB; the Marvell OCTEON TX2 CN9130 NAS 4GB has 2.0 GB usable.

What can the Marvell OCTEON TX2 CN9130 NAS 4GB run instead?

LFM3 1.7B, PaddleOCR-VL 1.6 0.9B and LFM3-VL 2B run best on it; the page lists more, each with its speed.

What hardware can run Qwen AgentWorld 35B-A3B?

NVIDIA RTX PRO 6000 Blackwell 96GB, M1 Max 64GB and M4 Max 64GB 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.