LLaVA 1.6 Mistral 7B on Apple iPhone 17 Pro / 17 Pro Max
Can the Apple iPhone 17 Pro / 17 Pro Max run LLaVA 1.6 Mistral 7B?
Yes, it runs well
Runs well. At Q3_K_M it needs about 5.4 GB of 7.2 GB usable, with an estimated speed of 16.5 tok/s.
- Best quant
Q3_K_M- Generation speed
- 16.5 tok/s
- Prompt processing
- 254 tok/s
- First token (1K prompt)
- 4.0 s
- Largest safe context
- 21K
Download LLaVA 1.6 Mistral 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 iPhone or iPad
No mobile app in the App Store runs LLaVA 1.6 Mistral 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
Recommended for the Apple iPhone 17 Pro / 17 Pro Max: Q3_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.
ollama run llava:7b-v1.6-mistral-q3_K_MOriginal weights · Hugging Face
Full-precision files from LLaVA, for fine-tuning, vLLM, Transformers.
huggingface.co/llava-hf/llava-v1.6-mistral-7b-hf (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 | 10.6 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 9.6 / 15 | |
| Memory use | 15.0 / 15 | |
| Match score | 60.2 / 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 | 4.7 GB | 7.2 GB | 21.0 tok/s | Runs well | 19Basic quality (D) · 19 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 59/100 (quality, fit, speed and memory use) sets the ranking. | |
Q3_K_M | 5.4 GB | 7.2 GB | 16.5 tok/s | Runs well | 23Basic quality (D) · 23 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking. | |
Q4_K_M | 6.3 GB | 7.2 GB | 12.8 tok/s | Runs welltight fit | 26Basic quality (D) · 26 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 59/100 (quality, fit, speed and memory use) sets the ranking. | |
Q5_K_M | 7.0 GB | 7.2 GB | 10.6 tok/s | Runs welltight fit | 27Basic quality (D) · 27 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 58/100 (quality, fit, speed and memory use) sets the ranking. | |
Q6_K | 7.9 GB | 7.2 GB | — | Won't runover the app memory limit | 27Basic quality (D) · 27 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 3/100 (quality, fit, speed and memory use) sets the ranking. | |
Q8_0 | 9.7 GB | 7.2 GB | — | Won't runover the app memory limit | 28Basic quality (D) · 28 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 3/100 (quality, fit, speed and memory use) sets the ranking. | |
F16 | 16.8 GB | 7.2 GB | — | Won't runover the app memory limit | 28Basic quality (D) · 28 of 100: how capable the model is at F16, whatever it runs on. Match score 3/100 (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
-
28Basic quality (D) · 28 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 9070 XT
-
28Basic quality (D) · 28 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 Ti SUPER
-
28Basic quality (D) · 28 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4080 SUPER
-
28Basic quality (D) · 28 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5070 Ti
-
28Basic quality (D) · 28 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5080
-
27Basic quality (D) · 27 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 3060 12GB
Quick answers
How much memory does LLaVA 1.6 Mistral 7B need on the iPhone 17 Pro?
At Q3_K_M it needs about 5.4 GB. The iPhone 17 Pro has 7.2 GB usable.
How fast is LLaVA 1.6 Mistral 7B on the iPhone 17 Pro?
About 16.5 tok/s at Q3_K_M, an estimate from the hardware’s memory bandwidth and the size of the model.
Which quantization of LLaVA 1.6 Mistral 7B should I use on the iPhone 17 Pro?
Q3_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.