Qwen3 30B-A3B Instruct 2507 on Apple iPhone 17 Pro / 17 Pro Max
Can the Apple iPhone 17 Pro / 17 Pro Max run Qwen3 30B-A3B Instruct 2507?
No, it doesn’t fit (over the app memory limit)
No. Qwen3 30B-A3B Instruct 2507 needs about 13.6 GB even at Q2_K; the Apple iPhone 17 Pro / 17 Pro Max has 7.2 GB usable.
Download Qwen3 30B-A3B Instruct 2507
Recommended: Q2_K. 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 qwen3:30b-instructQuantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
Download the Q2_K file (opens in a new tab)
huggingface.co/unsloth/Qwen3-30B-A3B-Instruct-2507-GGUF (opens in a new tab)
ollama run hf.co/unsloth/Qwen3-30B-A3B-Instruct-2507-GGUF:Q2_KOriginal weights · Hugging Face
Full-precision files from Alibaba, for fine-tuning, vLLM, Transformers.
huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507 (opens in a new tab)
Official repo · GitHub
Reference code, inference scripts and docs from Alibaba. The weights themselves download from Hugging Face.
github.com/QwenLM/Qwen3 (opens in a new tab)
git clone https://github.com/QwenLM/Qwen3How 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 | 7.3 / 45 | |
|---|---|---|
| Memory fit | 0.0 / 25 | |
| Speed | 0.0 / 15 | |
| Memory use | 0.0 / 15 | |
| Match score | 7.3 / 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 | 13.6 GB | 7.2 GB | — | Won't runover the app memory limit | 53Fair quality (C) · 53 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 7/100 (quality, fit, speed and memory use) sets the ranking. | Q2_K |
Q3_K_M | 16.4 GB | 7.2 GB | — | Won't runover the app memory limit | 64Good quality (B) · 64 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 8/100 (quality, fit, speed and memory use) sets the ranking. | Q3_K_M |
Q4_K_M | 20.0 GB | 7.2 GB | — | Won't runover the app memory limit | 73Great quality (A) · 73 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 9/100 (quality, fit, speed and memory use) sets the ranking. | Q4_K_M |
Q5_K_M | 23.1 GB | 7.2 GB | — | Won't runover the app memory limit | 74Great quality (A) · 74 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 | 26.4 GB | 7.2 GB | — | Won't runover the app memory limit | 76Great quality (A) · 76 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 | 33.8 GB | 7.2 GB | — | Won't runover the app memory limit | 77Great quality (A) · 77 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 | 62.5 GB | 7.2 GB | — | Won't runover the app memory limit | 77Great quality (A) · 77 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. |
Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.
Hardware that can run it
-
77Great quality (A) · 77 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.
Apple M1 Max (64 GB)
-
77Great quality (A) · 77 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.
Apple M4 Max (64 GB)
-
77Great quality (A) · 77 of 100: how capable the model is at F16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA RTX PRO 6000 Blackwell
-
76Great quality (A) · 76 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.
Apple M4 Pro (48 GB)
-
74Great quality (A) · 74 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5090
-
73Great quality (A) · 73 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 7900 XTX
Models that do run on the Apple iPhone 17 Pro / 17 Pro Max
- 66Good quality (B) · 66 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Nemotron 3.5 Bolt E4B
- 57Good quality (B) · 57 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Ling 3.0 Tiny (8B-A1.3B)
- 58Good quality (B) · 58 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Mellum2.1 Thinking (12B-A2.5B)
- 64Good quality (B) · 64 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Nanbeige4.2 3B
- 64Good quality (B) · 64 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 E4B
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.