Qwen AgentWorld 35B-A3B on OnePlus 13 (24 GB RAM)

Can the OnePlus 13 (24 GB RAM) run Qwen AgentWorld 35B-A3B?

Yes, it runs well (tight fit)

Runs well (tight fit). At Q2_K it needs about 14.6 GB of 15.6 GB usable, with an estimated speed of 37.3 tok/s.

Best quant: Q2_K
Generation speed: 37.3 tok/s
Prompt processing: 78.1 tok/s
First token (1K prompt): 13.1 s
Largest safe context: 54K

Best app to run it on the OnePlus 13 (24 GB RAM)

On Android

PocketPal AI

Mobile app · runs on llama.cpp

Runs the model on the device itself, offline: download it once in the app.

Get it on Google Play Then download Qwen AgentWorld 35B-A3B in the app

ChatterUI Runs the model on the device itself, offline: download it once in the app.

Want an agent? Qwen AgentWorld 35B-A3B supports tool use, so you can pair a llama.cpp or MLX LM server with one of these. Apps that run on this computer come first.

Coding agents

Personal assistants

How we choose: the files published for this model, your operating system and GPU, whether it fits fully in memory, and published speed tests (MLX vs llama.cpp on Apple silicon, vLLM vs llama.cpp vs Ollama on NVIDIA). Details.

Download Qwen AgentWorld 35B-A3B

On a phone, tablet or other mobile device you install a chat app and get the model file through it, so there are no commands to copy. Use Qwen-AgentWorld-35B-A3B-UD-Q2_K_XL.gguf for the OnePlus 13 (24 GB RAM).

On Android

PocketPal AI

Free mobile app · runs the model on the device with llama.cpp

Get it on Google Play

Install PocketPal AI (free) and open it.
Tap the menu (☰), then Models, then + and Add from Hugging Face.
Search for unsloth/Qwen-AgentWorld-35B-A3B-GGUF, open it and download Qwen-AgentWorld-35B-A3B-UD-Q2_K_XL.gguf.
Tap Load next to the model and start a chat. It runs on the device, with no connection needed from then on.

Also works: ChatterUI

Files and commands for a computer

Recommended for the OnePlus 13 (24 GB RAM): 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 80/100 (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 welltight fit: How well it runs on the OnePlus 13 (24 GB RAM): 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.	27.4 / 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.	24.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	14.5 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	15.0 / 15
Match score	80.9 / 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 OnePlus 13 (24 GB RAM)

Quant	Memory needed	Available	Speed	Runs	Quality	File to pick in the app
`Q2_K`	14.6 GB	15.6 GB	37.3 tok/s	Runs welltight fit	60Good quality (B) · 60 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking.	`UD-Q2_K_XL`
`Q3_K_M`	17.8 GB	15.6 GB	—	Won't runover the app memory limit	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.	`Q3_K_M`
`Q4_K_M`	21.9 GB	15.6 GB	—	Won't runover the app memory limit	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.	`Q4_K_M`
`Q5_K_M`	25.4 GB	15.6 GB	—	Won't runover the app memory limit	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.	`Q5_K_M`
`Q6_K`	29.2 GB	15.6 GB	—	Won't runover the app memory limit	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.	`Q6_K`
`Q8_0`	37.5 GB	15.6 GB	—	Won't runover the app memory limit	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.	`Q8_0`
`F16`	70.1 GB	15.6 GB	—	Won't runover the app memory limit	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.	—

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

Other hardware that runs 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

Quick answers

How much memory does Qwen AgentWorld 35B-A3B need on the OnePlus 13 24GB?

At Q2_K it needs about 14.6 GB. The OnePlus 13 24GB has 15.6 GB usable.

How fast is Qwen AgentWorld 35B-A3B on the OnePlus 13 24GB?

About 37.3 tok/s at Q2_K, an estimate from the hardware’s memory bandwidth and the size of the model.

Which quantization of Qwen AgentWorld 35B-A3B should I use on the OnePlus 13 24GB?

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.