InternLM 7B on Apple iPhone 17 Pro / 17 Pro Max
Can the Apple iPhone 17 Pro / 17 Pro Max run InternLM 7B?
Yes, it runs well
Runs well. At Q2_K it needs about 4.6 GB of 7.2 GB usable, with an estimated speed of 21.7 tok/s.
- Best quant
Q2_K- Generation speed
- 21.7 tok/s
- Prompt processing
- 263 tok/s
- First token (1K prompt)
- 3.9 s
- Largest safe context
- 2K
Download InternLM 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 InternLM 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 Shanghai AI Lab, for fine-tuning, vLLM, Transformers.
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 | 3.8 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 11.1 / 15 | |
| Memory use | 14.7 / 15 | |
| Match score | 54.6 / 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 | 4.6 GB | 7.2 GB | 21.7 tok/s | Runs well | 8Basic quality (D) · 8 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 54/100 (quality, fit, speed and memory use) sets the ranking. | |
Q3_K_M | 5.3 GB | 7.2 GB | 17.1 tok/s | Runs well | 10Basic quality (D) · 10 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 54/100 (quality, fit, speed and memory use) sets the ranking. | |
Q4_K_M | 6.1 GB | 7.2 GB | 13.2 tok/s | Runs welltight fit | 11Basic quality (D) · 11 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 52/100 (quality, fit, speed and memory use) sets the ranking. | |
Q5_K_M | 6.9 GB | 7.2 GB | 10.9 tok/s | Runs welltight fit | 11Basic quality (D) · 11 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 52/100 (quality, fit, speed and memory use) sets the ranking. | |
Q6_K | 7.7 GB | 7.2 GB | — | Won't runover the app memory limit | 11Basic quality (D) · 11 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 1/100 (quality, fit, speed and memory use) sets the ranking. | |
Q8_0 | 9.4 GB | 7.2 GB | — | Won't runover the app memory limit | 12Basic quality (D) · 12 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 1/100 (quality, fit, speed and memory use) sets the ranking. | |
F16 | 16.3 GB | 7.2 GB | — | Won't runover the app memory limit | 12Basic quality (D) · 12 of 100: how capable the model is at F16, whatever it runs on. Match score 1/100 (quality, fit, speed and memory use) sets the ranking. |
Memory figures assume 2K of context. Longer conversations or documents grow the KV cache.
Other hardware that runs it
-
12Basic quality (D) · 12 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 SUPER
-
11Basic quality (D) · 11 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking.
Intel Arc B580
-
11Basic quality (D) · 11 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 3060 12GB
-
12Basic quality (D) · 12 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 9070 XT
-
12Basic quality (D) · 12 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 Ti SUPER
-
12Basic quality (D) · 12 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4080 SUPER
Quick answers
How much memory does InternLM 7B need on the iPhone 17 Pro?
At Q2_K it needs about 4.6 GB. The iPhone 17 Pro has 7.2 GB usable.
How fast is InternLM 7B on the iPhone 17 Pro?
About 21.7 tok/s at Q2_K, an estimate from the hardware’s memory bandwidth and the size of the model.
Which quantization of InternLM 7B 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.