Qwen3-VL 30B-A3B Thinking on Apple M4 Max (128 GB)
Can the Apple M4 Max (128 GB) run Qwen3-VL 30B-A3B Thinking?
Yes, it runs well
Runs well. At Q8_0 it needs about 42.0 GB of 96.0 GB usable, with an estimated speed of 44.5 tok/s.
- Best quant
Q8_0- Generation speed
- 44.5 tok/s
- Prompt processing
- 3,457 tok/s
- First token (1K prompt)
- 0.3 s
- Largest safe context
- 256K
Download Qwen3-VL 30B-A3B Thinking
Recommended for the Apple M4 Max (128 GB): Q8_0. 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-vl:30b-a3b-thinking-q8_0Quantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
Download the Q8_0 file (opens in a new tab)
huggingface.co/Qwen/Qwen3-VL-30B-A3B-Thinking-GGUF (opens in a new tab)
ollama run hf.co/Qwen/Qwen3-VL-30B-A3B-Thinking-GGUF:Q8_0Original weights · Hugging Face
Full-precision files from Alibaba, for fine-tuning, vLLM, Transformers.
huggingface.co/Qwen/Qwen3-VL-30B-A3B-Thinking (opens in a new tab)
How the A grade is scored
Every result gets up to 100 points from four parts. The points decide the letter grade.
| Model quality | 34.2 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 15.0 / 15 | |
| Memory use | 10.1 / 15 | |
| Total | 84.3 / 100 | 84 ptsGreat (A) · 84 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.1/15 |
Every quantization on the Apple M4 Max (128 GB)
| Quant | Memory needed | Available | Speed | Fit | Grade · points | Download |
|---|---|---|---|---|---|---|
Q2_K | 21.5 GB | 96.0 GB | 144 tok/s | Runs well | 69 ptsGood (B) · 69 of 100 points: Model quality 23.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.2/15 | GGUF files (opens in a new tab) |
Q3_K_M | 24.3 GB | 96.0 GB | 113 tok/s | Runs well | 74 ptsGreat (A) · 74 of 100 points: Model quality 28.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.8/15 | GGUF files (opens in a new tab) |
Q4_K_M | 28.0 GB | 96.0 GB | 87.4 tok/s | Runs well | 79 ptsGreat (A) · 79 of 100 points: Model quality 32.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 6.7/15 | GGUF (opens in a new tab) |
Q5_K_M | 31.1 GB | 96.0 GB | 72.2 tok/s | Runs well | 80 ptsGreat (A) · 80 of 100 points: Model quality 33.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 7.5/15 | GGUF files (opens in a new tab) |
Q6_K | 34.6 GB | 96.0 GB | 60.7 tok/s | Runs well | 82 ptsGreat (A) · 82 of 100 points: Model quality 33.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.3/15 | GGUF files (opens in a new tab) |
Q8_0 | 42.0 GB | 96.0 GB | 44.5 tok/s | Runs well | 84 ptsGreat (A) · 84 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.1/15 | GGUF (opens in a new tab) |
F16 | 71.2 GB | 96.0 GB | 20.5 tok/s | Runs well | 84 ptsGreat (A) · 84 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 10.7/15, Memory use 15.0/15 | GGUF · part 1 of 2 (opens in a new tab) Original weights (opens in a new tab) |
Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.
Other hardware that runs it
- 89 ptsExcellent (S) · 89 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 Apple M4 Max (64 GB)
- 89 ptsExcellent (S) · 89 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA RTX PRO 6000 Blackwell
- 88 ptsExcellent (S) · 88 of 100 points: Model quality 33.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.8/15 Apple M1 Max (64 GB)
- 88 ptsExcellent (S) · 88 of 100 points: Model quality 33.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5090
- 87 ptsExcellent (S) · 87 of 100 points: Model quality 32.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.9/15 Apple M4 Pro (48 GB)
- 86 ptsExcellent (S) · 86 of 100 points: Model quality 32.5/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 AMD Radeon RX 7900 XTX
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.