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Can the Other Android device (12 GB RAM) run MiMo V2.6 Distill Qwen 9B?

74Great quality (A) · 74 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.

Yes, but slowly (tight fit)

Slow (tight fit). At Q4_K_M it needs about 6.6 GB of 7.2 GB usable, with an estimated speed of 3.3 tok/s.

Best quant
Q4_K_M
Generation speed
3.3 tok/s
Prompt processing
7.3 tok/s
First token (1K prompt)
139.9 s
Largest safe context
25K

Best app to run it on the Other Android device (12 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 MiMo V2.6 Distill Qwen 9B in the app

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

Want an agent? MiMo V2.6 Distill Qwen 9B 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 MiMo V2.6 Distill Qwen 9B

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 MiMo-V2.6-Distill-Qwen-9B-Q4_K_M.gguf for the Other Android device (12 GB RAM).

On Android

PocketPal AI

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

Get it on Google Play

  1. Install PocketPal AI (free) and open it.
  2. Tap the menu (☰), then Models, then + and Add from Hugging Face.
  3. Search for bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF, open it and download MiMo-V2.6-Distill-Qwen-9B-Q4_K_M.gguf.
  4. 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 Other Android device (12 GB RAM): Q4_K_M. Every other quantization has its own download link in the table below.

Quickest · Ollama

One command downloads a ready-to-run version and starts a chat.

Get Ollama at ollama.com/download (opens in a new tab) · model page (opens in a new tab)

ollama run mimo-v2.6:9b-q4_K_M

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/bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF (opens in a new tab)

ollama run hf.co/bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF:Q4_K_M

Original weights · Hugging Face

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

huggingface.co/XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B (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 74Great quality (A) · 74 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.
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 Slowtight fit
How well it runs on the Other Android device (12 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.33.3 / 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.4.3 / 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 score76.6 / 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 Other Android device (12 GB RAM)

Quant Memory needed Available Speed Runs Quality File to pick in the app
Q2_K 4.6 GB 7.2 GB 5.4 tok/s Slow 54Fair quality (C) · 54 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. Q2_K
Q3_K_M 5.5 GB 7.2 GB 4.2 tok/s Slow 65Good quality (B) · 65 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. Q3_K_M
Q4_K_M 6.6 GB 7.2 GB 3.3 tok/s Slowtight fit 74Great quality (A) · 74 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. Q4_K_M
Q5_K_M 7.5 GB 7.2 GB — Won't runover the app memory limit 75Great quality (A) · 75 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. Q5_K_M
Q6_K 8.6 GB 7.2 GB — Won't runover the app memory limit 77Great quality (A) · 77 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. Q6_K
Q8_0 10.8 GB 7.2 GB — Won't runover the app memory limit 78Great quality (A) · 78 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. Q8_0
F16 19.7 GB 7.2 GB — Won't runover the app memory limit 78Great quality (A) · 78 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. BF16

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 MiMo V2.6 Distill Qwen 9B need on the Other Android device 12GB?

At Q4_K_M it needs about 6.6 GB. The Other Android device 12GB has 7.2 GB usable.

How fast is MiMo V2.6 Distill Qwen 9B on the Other Android device 12GB?

About 3.3 tok/s at Q4_K_M, an estimate from the hardware’s memory bandwidth and the size of the model.

Which quantization of MiMo V2.6 Distill Qwen 9B should I use on the Other Android device 12GB?

Q4_K_M. 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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