Apple M3 Max
M3 Max — 400 GB/s bandwidth, up to 128GB.
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Sub-scores sum to 569 / 1000. Headline = 569 × 0.70 (Estimated-confidence discount) = 398. This is an algorithmic performance-tier score — distinct from, and often lower than, the editorial “Our verdict” below, which weighs value and real-world fit (especially for hardware we haven’t measured yet). How scoring works →
Extrapolated from 400 GB/s bandwidth — 56.0 tok/s estimated. No measured benchmarks yet.
Plain-English: Runs 70B with care — snappy enough for a coding agent; vision models supported.
Verdicts extrapolated from catalog VRAM + bandwidth + ecosystem flags. Hover any chip for the rationale. Want measured numbers? Submit your own run with runlocalai-bench --submit.
What it does well
Unified memory architecture. A 64 GB M3 Max runs Llama 3.3 70B at Q4 entirely in fast memory — no system-RAM offload, no partial-offload speed cliff, just steady 12–18 tok/s. The 96 GB and 128 GB configurations open up Llama 4 Scout / DeepSeek V3 territory that no consumer NVIDIA card touches. MLX is a clean, fast runner that takes advantage of the architecture.
Where it breaks
- Tokens/sec on 7–32B class trails NVIDIA — same model, 4090 is 2–3× faster. Apple wins on accessibility, not raw throughput.
- MLX is Apple-only — your model investments don't transfer to NVIDIA without re-quantizing.
- High-memory configs are expensive — a 128 GB M3 Max MacBook Pro pushes past $7,000.
Ideal model range
- Sweet spot: Llama 3.3 70B / R1 Distill Llama 70B at Q4 — 12–18 tok/s, no offload concerns. The reason you bought it.
- Stretch (96–128 GB configs): Llama 4 Scout, DeepSeek V3 at Q3/Q4, Llama 4 Maverick with quantization compromises.
- Comfortable: 32B-class at MLX-native quants with low latency, multimodal models (Gemma 3, Pixtral) with strong vision-language.
Bad use cases
- Maximum tokens-per-second — NVIDIA wins for any model that fits a 4090.
- Coder autocomplete — Apple's tok/s on Qwen 2.5 Coder 32B is half a 4090's; latency in the editor matters.
- Cloud-equivalent throughput per dollar — for high-volume inference, NVIDIA-on-cloud is better $/output.
Verdict
Buy this if you want a portable 70B-capable rig, you already use macOS for development, or you want the easiest path to running models that don't fit a 4090. Skip this if you prioritize raw throughput, run models that fit a 24 GB CUDA card, or do agent-loop / autocomplete workloads where latency matters.
How it compares
- vs RTX 4090 → 4090 is faster on models that fit 24 GB; M3 Max wins on 70B-class with no offload hassle. Different jobs.
- vs M2 Ultra (192 GB Mac Studio) → M2 Ultra has more memory bandwidth and unified-memory ceiling — better for Llama 4 Maverick / DeepSeek V3 territory.
- vs M4 Max → M4 Max is the architectural successor with materially better tokens/sec at the same memory config; pick M4 Max if available.
- vs Linux + RX 7900 XTX → AMD wins on price for 32B-class; M3 Max wins on 70B-class accessibility and out-of-box experience.
›Why this rating
8.5/10 — for users who want to run 70B-class models without hardware acrobatics, Apple Silicon with 64+ GB unified memory is genuinely the easiest path. Slower than CUDA on equivalent VRAM but no offload tax. Loses points on raw tokens-per-second vs NVIDIA + on price for the high-memory configurations.
Overview
M3 Max — 400 GB/s bandwidth, up to 128GB.
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Featured in this stack
The L3 execution stacks that pick this hardware as a recommended component, with the one-line note explaining the role it plays in each.
- Stack · L3·Workstation tier·Role: Compute (Apple Silicon GPU + unified memory)Build a Mac-native AI stack (May 2026)
M3 Max 64GB is the single-Mac sweet spot in May 2026 — 36 GPU cores, 400 GB/s memory bandwidth, all 64GB addressable as VRAM. M4 Pro / M4 Max win on Thunderbolt 5 RDMA for clustering; for single-Mac use, M3 Max delivers 90% of M4 Max throughput at lower price.
Specs
| VRAM | 0 GB |
| System RAM (typical) | 96 GB |
| Power draw (peak) | 95 W |
| Released | 2023 |
| Backends | Metal MLX |
Frequently asked
Does Apple M3 Max support CUDA?
Where next?
Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify hardware specifications.