Mage-VL-Cowork 4.7B on Google Pixel 11 Pro / 11 Pro XL (12 GB RAM)
Can the Google Pixel 11 Pro / 11 Pro XL (12 GB RAM) run Mage-VL-Cowork 4.7B?
Yes, it runs well
Runs well. At Q4_K_M it needs about 4.7 GB of 7.2 GB usable, with an estimated speed of 13.0 tok/s.
- Best quant
Q4_K_M- Generation speed
- 13.0 tok/s
- Prompt processing
- 29.1 tok/s
- First token (1K prompt)
- 35.2 s
- Largest safe context
- 24K
Download Mage-VL-Cowork 4.7B
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.
On Android
No mobile app in the Play Store runs Mage-VL-Cowork 4.7B right now: mobile apps need a GGUF version, and none is published. Mobile apps · models that run on mobile devices.
Files and commands for a computer
Original weights · Hugging Face
Full-precision files from Microsoft, for fine-tuning, vLLM, Transformers.
huggingface.co/microsoft/Mage-VL-Cowork (opens in a new tab)
Official repo · GitHub
Reference code, inference scripts and docs from Microsoft. The weights themselves download from Hugging Face.
github.com/microsoft/Mage (opens in a new tab)
git clone https://github.com/microsoft/MageHow it’s rated
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 quality | 25.7 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 8.6 / 15 | |
| Memory use | 15.0 / 15 | |
| Match score | 74.2 / 100 |
Every quantization on the Google Pixel 11 Pro / 11 Pro XL (12 GB RAM)
| Quant | Memory needed | Available | Speed | Runs | Quality | File to pick in the app |
|---|---|---|---|---|---|---|
Q2_K | 3.7 GB | 7.2 GB | 21.4 tok/s | Runs well | 42Fair quality (C) · 42 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking. | |
Q3_K_M | 4.1 GB | 7.2 GB | 16.8 tok/s | Runs well | 50Fair quality (C) · 50 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. | |
Q4_K_M | 4.7 GB | 7.2 GB | 13.0 tok/s | Runs well | 57Good quality (B) · 57 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. | |
Q5_K_M | 5.2 GB | 7.2 GB | 10.8 tok/s | Runs well | 58Good quality (B) · 58 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. | |
Q6_K | 5.7 GB | 7.2 GB | 9.0 tok/s | Slow | 59Good quality (B) · 59 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. | |
Q8_0 | 6.8 GB | 7.2 GB | 6.6 tok/s | Slowtight fit | 60Good quality (B) · 60 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. | |
F16 | 11.3 GB | 7.2 GB | — | Won't runover the app memory limit | 60Good quality (B) · 60 of 100: how capable the model is at F16, whatever it runs on. Match score 8/100 (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
-
60Good quality (B) · 60 of 100: how capable the model is at F16, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 Ti SUPER
-
60Good quality (B) · 60 of 100: how capable the model is at F16, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4080 SUPER
-
60Good quality (B) · 60 of 100: how capable the model is at F16, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5070 Ti
-
60Good quality (B) · 60 of 100: how capable the model is at F16, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5080
-
59Good quality (B) · 59 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4060
-
60Good quality (B) · 60 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking.
Intel Arc B580
Quick answers
How much memory does Mage-VL-Cowork 4.7B need on the Pixel 11 Pro 12GB?
At Q4_K_M it needs about 4.7 GB. The Pixel 11 Pro 12GB has 7.2 GB usable.
How fast is Mage-VL-Cowork 4.7B on the Pixel 11 Pro 12GB?
About 13.0 tok/s at Q4_K_M, an estimate from the hardware’s memory bandwidth and the size of the model.
Which quantization of Mage-VL-Cowork 4.7B should I use on the Pixel 11 Pro 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.