Autor: Jakub Rusinowski · Ostatnia aktualizacja: 11 września 2026
Not at Q4_K_M — that needs 21.1 GB and the Apple M2 has 24 GB. Drop to Q3_K_M and it fits in 17.6 GB, with up to 16K of context.
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| Model | Qwen 3.6 35B-A3B |
| Parameters | 35B (3B active) |
| Quantization | Q4_K_M |
| VRAM needed | 21.1 GB |
| Apple M2 VRAM | 24 GB |
| Verdict | Runs at a lower quant |
| Fits at | Q3_K_M (17.6 GB) |
| Max context | 16K |
| Quant | VRAM needed | Fits 24 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 71.7 GB | ✗ No | — | — |
| Q8_0 | 38.9 GB | ✗ No | — | Build for this |
| Q6_K | 30.4 GB | ✗ No | — | — |
| Q5_K_M | 26.5 GB | ✗ No | — | Build for this |
| Q4_K_M | 22.9 GB | ✓ Yes | 8K | Build for this |
| Q3_K_M | 16.7 GB | ✓ Yes | 32K | — |
| Q2_K | 13.2 GB | ✓ Yes | 32K | — |
Assumes a 4K-token context with an f16 KV cache, on an estimated architecture — this model publishes no config we can read. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 24 GB of unified memory. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
Context costs VRAM too. At Q4_K_M on the Apple M2: 8K 23.8 GB · 32K 29.4 GB ✗ · 128K 52 GB ✗. Past 32K it no longer fits 24 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
Quantize to Q3_K_M. That is the cheapest fix — it costs some quality but no money.
No compatible GPU? Qwen 3.6 35B-A3B on 32 GB of system RAM, CPU only: runs, but it is tight.
Running Qwen 3.6 35B-A3B on this card:
Qwen 3.6 35B-A3B needs ~21 GB but this GPU has 24 GB. Rent a RTX 4090 (24 GB)-class GPU by the hour instead of buying one:
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Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
All Qwen 3.6 sizes on the Apple M2 | Qwen 3.6 35B-A3B model page | Apple M2 GPU page | Check your hardware