Apple M3 Max 14 Core — Benchmarks & Specs
Short answer: the Apple M3 Max 14 Core generates a median 50.7 tokens/sec on 7-9B dense models at 4-bit (Q4) under llama.cpp, across 3 cited runs from llama.cpp GitHub Discussion #4167 and XiongjieDai/GPU-Benchmarks-on-LLM-Inference.
Bottom line: how fast is the Apple M3 Max 14 Core?
SpecPicks median: 50.7 tokens/sec across 3 cited single-user runs of 7-9B dense models at 4-bit (Q4) under llama.cpp (range 49.0–66.3 tok/s), from llama.cpp GitHub Discussion #4167, XiongjieDai/GPU-Benchmarks-on-LLM-Inference (2 runs). For local LLM inference it generates 7.7 tokens/sec running llama3.1:70b at q4_K_M under llama.cpp, per XiongjieDai/GPU-Benchmarks-on-LLM-Inference. In PassMark CPU Mark it scores 36,303 points, per PassMark Software. Across all its cores it scores 21,043 points in Cinebench R23 multi, per render4you.com.
Every figure above is a row in the tables below, and each row links out to the review or public benchmark database the number was taken from; the SpecPicks median is computed here from the runs it names, each a row in the AI table. SpecPicks aggregates published measurements; it does not report first-party benchmark runs.
The Apple M3 Max 14 Core is a processor from Apple. Data on this page draws on 10 synthetic benchmark results, 12 community AI inference reports, 4 measured game frame-rate results, compiled from heyuan110.com, PassMark Software, XiongjieDai/GPU-Benchmarks-on-LLM-Inference, Notebookcheck, Geekbench Browser, llama.cpp GitHub Discussion #4167, Technetbook, Alexander Hiesch, GameGPU, kunalganglani.com, Local AI Master, MacRumors Forums, render4you.com; each table row links to its source. Read this page when shopping the Apple M3 Max 14 Core, comparing it against other processors in your build, or sizing it for a specific workload (gaming at 1080p/1440p/4K, synthetic benchmark scores, or local LLM inference).
Gaming Performance (measured FPS)
Average and 1% low frame rates by game, resolution, and quality preset. Bars are scaled against the fastest result on this page.
| Game | Resolution | Settings | Relative | Avg FPS | 1% low | Test GPU | Source |
|---|---|---|---|---|---|---|---|
| Cyberpunk 2077 | 1080p | High | 105 fps | — | Not recorded | GameGPU 2025-07-20 | |
| Cyberpunk 2077 | 1080p | High FSR Quality | 105 fps | — | Not recorded | Technetbook 2025-07 | |
| Baldur's Gate 3 | 1080p | High | 90 fps | — | Not recorded | MacRumors Forums 2024-01 | |
| Cyberpunk 2077 | 1080p | High | 78 fps | — | Not recorded | Technetbook 2025-07 |
AI Inference Performance
Tokens per second under each model + quantization. Higher = faster generation. Bars compare runs across the same model.
| Model | Quantization | Relative | Tokens/sec | VRAM used | Source |
|---|---|---|---|---|---|
| llama2:7b | q4_0 llama.cpp | 66.3 tok/s | — | llama.cpp GitHub Discussion #4167 2023-11-24 | |
| llama3.1:8b | q4_K_M ollama | 58.0 tok/s | — | heyuan110.com 2026-04-14 | |
| llama3:8b | q4_K_M llama.cpp | 50.7 tok/s | — | GitHub: XiongjieDai/GPU-Benchmarks-on-LLM-Inference 2024-07 | |
| llama3.1:8b | q4_K_M llama.cpp | 49.0 tok/s | — | XiongjieDai/GPU-Benchmarks-on-LLM-Inference (GitHub) 2024-05 | |
| llama3.1:8b | q4_K_M ollama | 46.0 tok/s | — | kunalganglani.com 2025-01 | |
| qwen2.5:14b | q4_K_M ollama | 33.0 tok/s | — | heyuan110.com 2026-04-14 | |
| llama3.1:13b | q4_K_M ollama | 30.0 tok/s | — | Local AI Master 2025-06 | |
| gemma4:27b | q4_K_M llama.cpp | 17.0 tok/s | — | Alexander Hiesch (hiesch.eu) 2026-05-06 | |
| llama3.1:70b | q4_K_M llama.cpp | 7.7 tok/s | — | XiongjieDai/GPU-Benchmarks-on-LLM-Inference (GitHub) 2024-05 | |
| llama3:70b | q4_K_M llama.cpp | 7.5 tok/s | — | GitHub: XiongjieDai/GPU-Benchmarks-on-LLM-Inference 2024-07 | |
| llama3.1:70b | q4_K_M ollama | 7.5 tok/s | — | heyuan110.com 2026-04-14 | |
| llama3.3:70b | q4_K_M ollama | 7.5 tok/s | — | heyuan110.com 2026-04-14 |
Synthetic Benchmarks
Higher is better. Bars are scaled within each benchmark family (multi-thread, single-thread, etc.) so you can compare like-with-like at a glance.
| Benchmark | Relative | Score | Source |
|---|---|---|---|
| PassMark CPU Mark | 36,303 points | PassMark Software retrieved 2026-06-02 | |
| Cinebench R23 multi | 21,043 points | render4you.com 2024-01 | |
| Geekbench 6 multi | 18,943 points | Geekbench Browser retrieved 2026-06-02 | |
| Geekbench 6 multi | 17,576 points | Notebookcheck retrieved 2026-08-04 | |
| PassMark CPU Mark single thread | 4,759 points | PassMark Software retrieved 2026-06-02 | |
| PassMark CPU Mark single thread | 4,752 points | PassMark Software retrieved 2026-08-04 | |
| PassMark CPU Mark single thread | 4,751 points | PassMark Software retrieved 2026-10-05 | |
| Geekbench 6 single | 3,107 points | Geekbench Browser retrieved 2026-06-02 | |
| Geekbench 6 single | 2,847 points | Notebookcheck retrieved 2026-08-04 | |
| Cinebench R23 single | 1,950 points | Notebookcheck 2023-11-08 |
Apple M3 Max 14 Core — Frequently Asked Questions
What is the Apple M3 Max 14 Core best used for?
Where do the Apple M3 Max 14 Core benchmark numbers come from?
How many cores does the Apple M3 Max 14 Core have, and how does it benchmark?
Where can I buy the Apple M3 Max 14 Core?
Buying guides that rank the Apple M3 Max 14 Core's class
This page is the raw performance data. The guides below turn it into a ranked pick for a specific build.
Editorial guides covering the Apple M3 Max 14 Core
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