ToolJoltTools

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.

Memory needed (GB)
Headroom on this card (GB)
Max params at this quant (B)
Est. decode speed (tok/s)

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

needed = params × bpw ÷ 8 + reserve · fits if ≤ 128 GB · decode tok/s ≈ 0.6 × 546 GB/s ÷ weight-GB (bandwidth-bound)
References: NVIDIA/Apple official Apple M4 Max (128GB unified) specifications; llama.cpp quantization size tables

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?

  1. 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.
  2. 2The result recomputes live using the formula shown on the page; there is no button to press.
  3. 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.

Related tools

Related ML & AI tools

Sponsored