Can I Run Qwen3 235B A22B Thinking 2507 on a Apple M3 Ultra (512GB)?
Runs comfortably at Q6_K — minimal quality loss.
6 quantizations fit your 512GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q6_KBEST | 194.7 GB | 196.2 GB | 193.0 GB | +317.3 GB |
| Q4_K_M | 143.5 GB | 145.0 GB | 142.2 GB | +368.5 GB |
| Q4_K_S | 135.6 GB | 137.1 GB | 133.7 GB | +376.4 GB |
| Q3_K_M | 99.5 GB | 101.0 GB | 112.5 GB | +412.6 GB |
| Q3_K_S | 91.5 GB | 93.0 GB | 101.4 GB | +420.5 GB |
| Q2_K | 78.3 GB | 79.8 GB | 85.7 GB | +433.7 GB |
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Top-ranked open-source models that fit in 512GB.
FAQ
Can the Apple M3 Ultra (512GB) run Qwen3 235B A22B Thinking 2507?
Yes. The Apple M3 Ultra (512GB)'s 512GB of unified memory is enough to run Qwen3 235B A22B Thinking 2507 at Q6_K quantization (194.7GB required).
What's the best quantization to use?
Q6_K is the highest-precision quantization that fits in your 512GB. It uses about 194.7GB of memory and 196.2GB recommended for comfortable inference.
What if I need more headroom for context length?
KV cache memory grows with context length. The numbers above assume a baseline 2K-4K context. For long-context use (32K+), add another 2-6GB depending on the model architecture.