Pixtral 12B (2409) on Apple iPhone 17 Pro / 17 Pro Max
Can the Apple iPhone 17 Pro / 17 Pro Max run Pixtral 12B (2409)?
Yes, it runs well (tight fit)
Runs well (tight fit). At Q2_K it needs about 6.9 GB of 7.2 GB usable, with an estimated speed of 12.8 tok/s.
- Best quant
Q2_K- Generation speed
- 12.8 tok/s
- Prompt processing
- 155 tok/s
- First token (1K prompt)
- 6.6 s
- Largest safe context
- 9K
Download Pixtral 12B (2409)
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 iPhone or iPad
No mobile app in the App Store runs Pixtral 12B (2409) 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 Mistral AI, for fine-tuning, vLLM, Transformers.
huggingface.co/mistralai/Pixtral-12B-2409 (opens in a new tab)
How 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 | 15.8 / 45 | |
|---|---|---|
| Memory fit | 24.0 / 25 | |
| Speed | 8.5 / 15 | |
| Memory use | 15.0 / 15 | |
| Match score | 63.2 / 100 |
Every quantization on the Apple iPhone 17 Pro / 17 Pro Max
| Quant | Memory needed | Available | Speed | Runs | Quality | File to pick in the app |
|---|---|---|---|---|---|---|
Q2_K | 6.9 GB | 7.2 GB | 12.8 tok/s | Runs welltight fit | 35Basic quality (D) · 35 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 63/100 (quality, fit, speed and memory use) sets the ranking. | |
Q3_K_M | 8.0 GB | 7.2 GB | — | Won't runover the app memory limit | 42Fair quality (C) · 42 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 5/100 (quality, fit, speed and memory use) sets the ranking. | |
Q4_K_M | 9.5 GB | 7.2 GB | — | Won't runover the app memory limit | 47Fair quality (C) · 47 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 6/100 (quality, fit, speed and memory use) sets the ranking. | |
Q5_K_M | 10.7 GB | 7.2 GB | — | Won't runover the app memory limit | 48Fair quality (C) · 48 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 6/100 (quality, fit, speed and memory use) sets the ranking. | |
Q6_K | 12.1 GB | 7.2 GB | — | Won't runover the app memory limit | 49Fair quality (C) · 49 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 6/100 (quality, fit, speed and memory use) sets the ranking. | |
Q8_0 | 15.1 GB | 7.2 GB | — | Won't runover the app memory limit | 50Fair quality (C) · 50 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 6/100 (quality, fit, speed and memory use) sets the ranking. | |
F16 | 26.7 GB | 7.2 GB | — | Won't runover the app memory limit | 50Fair quality (C) · 50 of 100: how capable the model is at F16, whatever it runs on. Match score 6/100 (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
-
50Fair quality (C) · 50 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 7900 XTX
-
50Fair quality (C) · 50 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 3090
-
50Fair quality (C) · 50 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4090
-
49Fair quality (C) · 49 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 Ti SUPER
-
49Fair quality (C) · 49 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4080 SUPER
-
49Fair quality (C) · 49 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5070 Ti
Quick answers
How much memory does Pixtral 12B (2409) need on the iPhone 17 Pro?
At Q2_K it needs about 6.9 GB. The iPhone 17 Pro has 7.2 GB usable.
How fast is Pixtral 12B (2409) on the iPhone 17 Pro?
About 12.8 tok/s at Q2_K, an estimate from the hardware’s memory bandwidth and the size of the model.
Which quantization of Pixtral 12B (2409) should I use on the iPhone 17 Pro?
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.