Apple M4 Max (128GB unified) LLM Calculator — What Can It Run?
Check which models fit on a Apple M4 Max (128GB unified): max parameters per precision, cache headroom and estimated tokens/sec.
Apple M4 Max (128GB unified): 128 GB, 546 GB/s, ~34 TFLOPS FP16. Apple silicon plays a different game: up to 128 GB of UNIFIED memory means a MacBook can load 70B FP16 or 123B Q4 models no consumer GPU can — at 546 GB/s, generation is steady rather than blazing.
Formula
About Apple M4 Max (128GB unified) LLM Calculator — What Can It Run?
"Will it run?" is the first question of local AI, and for the Apple M4 Max (128GB unified) this calculator answers it precisely: enter any model's parameter count and quantization and get the memory bill against this card's 128 GB, the largest model it can hold at that quant, and a bandwidth-derived decode-speed estimate (token generation streams the whole model per token, so 546 GB/s is the speed limit that matters). Apple silicon plays a different game: up to 128 GB of UNIFIED memory means a MacBook can load 70B FP16 or 123B Q4 models no consumer GPU can — at 546 GB/s, generation is steady rather than blazing.
How to use Apple M4 Max (128GB unified) LLM Calculator — What Can It Run?
- 1Enter your values into Apple M4 Max (128GB unified) LLM Calculator — What Can It Run? — sensible, domain-typical defaults are pre-filled so you see a real result immediately.
- 2The result recomputes live using the formula shown on the page; there is no button to press.
- 3Adjust any input to compare scenarios, then read the worked example to see the substituted numbers.
Why use Apple M4 Max (128GB unified) LLM Calculator — What Can It Run??
- ✓Computes Apple M4 Max (128GB unified) LLM instantly in your browser — no sign-up, no upload, no server round-trip.
- ✓100% free and unlimited, with the exact formula shown: needed = params × bpw ÷ 8 + reserve.
- ✓Runs entirely client-side, so every value you enter stays private on your device.
- ✓Live recompute as you type, with a worked example and authoritative references for trust.
Frequently asked questions
Why can a MacBook run models a 4090 cannot?+
Unified memory: the GPU addresses the full 128 GB pool, versus the 4090's fixed 24 GB. Capacity wins for fitting; bandwidth decides speed — 546 GB/s sits between a 4060 Ti and 3090, so big models run, just at single-digit to low-double-digit tokens/s.
What should M-series owners know before downloading 70B?+
Use MLX or llama.cpp Metal builds; leave ~8–16 GB for macOS (set a sensible gpu-layers/wired limit); prefer Q4_K_M/Q5 over FP16 for 3–4× faster decode at minimal quality cost; and expect ~5–9 tok/s on 70B Q4 with M4 Max — usable, not snappy.
How is the tokens/sec estimate for the Apple M4 Max (128GB unified) derived?+
Decode is memory-bound: each token reads every weight once, so speed ≈ effective bandwidth ÷ model size. We assume ~60% of the 546 GB/s peak is achievable, matching llama.cpp benchmarks within ~20%. Prompt prefill is compute-bound and much faster per token.
Why reserve memory beyond the weights?+
The KV cache grows with context (use our per-model KV-cache calculators), CUDA/Metal runtimes take hundreds of MB, and allocator fragmentation wastes more. The default reserve suits 2–8K contexts; long-context work needs significantly more.
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