Apple M4 Max (GPU, 32 cores) vs Apple M4 Pro (GPU, 20 cores): specs and benchmark comparison
Short verdict
Apple M4 Max (GPU, 32 cores) leads in every scenario with comparable benchmarks: rendering and compute. This does not imply an advantage in tasks without benchmarks.
Compare with AIRendering and compute
A +76.1%Apple M4 Max (GPU, 32 cores) leads in this scenario (up to 76.1% in comparable benchmarks).
No comparable benchmarks yet: gaming: rasterization, gaming: ray tracing, power efficiency.
Advantages
Only measured and rated values: a noticeable benchmark gap and specs where more is better.
Where Apple M4 Max (GPU, 32 cores) is better2
Blender Benchmark 4.5.0 73.1% faster4,455 samples/min vs 2,574 samples/min
Compute units 12 more32 GPU cores vs 20 GPU cores
Where Apple M4 Pro (GPU, 20 cores) is better0
No advantages found in our data.
Benchmarks
Results are compared within one benchmark, one version and the same conditions.
- A ahead by 73.1%
Blender Benchmark 4.5.0
GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) · samples/min, higher is better
Apple M4 Max (GPU, 32 cores)4,455.4 samples/minApple M4 Pro (GPU, 20 cores)2,573.7 samples/minPosition among tested models (18, Metal)
B · 2,574A · 4,45502,0004,0006,000Each dot is one model’s median in this benchmark. The scale starts at zero, samples/min. Apple M4 Max (GPU, 32 cores) is ahead by 73.1% in this benchmark.
About the measurement and source
- A · Apple M4 Max (GPU, 32 cores)
4,455.4 samples/min · community measurement, sample 65 · November 14, 2026
Blender Open Data (Blender Foundation)
Median of 65 submissions (2 outliers excluded), interquartile range 4428.74–4490.11; submissions 2025-07-19 to 2026-03-13; METAL backend. Snapshot 2026-11-14.
- B · Apple M4 Pro (GPU, 20 cores)
2,573.7 samples/min · community measurement, sample 110 · November 14, 2026
Blender Open Data (Blender Foundation)
Median of 110 submissions (13 outliers excluded), interquartile range 2552.03–2586.89; submissions 2025-07-17 to 2026-03-20; METAL backend. Snapshot 2026-11-14.
difference = |A − B| ÷ the smaller value × 100%. The 5% noticeable threshold is a UX heuristic, not statistical significance.
Cycles render in Blender Benchmark. Median of the sum of samples per minute over three scenes after removing outliers.
Other comparable benchmarks (2)
| Benchmark | A | B | Difference |
|---|---|---|---|
| Blender Benchmark 4.3.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 4,342.6 | 2,480.1 | A +75.1% |
| Blender Benchmark 4.4.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 4,440.3 | 2,521.8 | A +76.1% |
Each benchmark version has its own scale: numbers are compared only within a row.
Reference results (9)
| Benchmark | A | B | Difference |
|---|---|---|---|
| Blender Benchmark 4.2.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 4,439.4 | 2,548.3 | reference |
| Blender Benchmark 5.1.1GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 4,859.5 | 2,985.4 | reference |
| Blender Benchmark 5.2.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 4,886 | 2,919.7 | reference |
| Blender Benchmark 5.0.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 4,378.4 | 2,630.2 | reference |
| Blender Benchmark 5.1.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 4,807.6 | 2,945.1 | reference |
| Blender Benchmark 5.3.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 4,650.6 | — | no pair |
| Blender Benchmark 3.6.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | — | 1,877.9 | no pair |
| Blender Benchmark 4.0.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | — | 1,751.5 | no pair |
| Blender Benchmark 4.1.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | — | 2,297 | no pair |
Each benchmark version has its own scale: numbers are compared only within a row.
Specifications
| Specification | A · Apple M4 Max (GPU, 32 cores) | B · Apple M4 Pro (GPU, 20 cores) | Difference |
|---|---|---|---|
| Chip | |||
| GPU chip | Apple M4 Max | Apple M4 Pro | differs |
| Architecture | Apple Silicon | Apple Silicon | equal |
| Compute unitsSM (NVIDIA), CU (AMD) and Xe-core (Intel) are different units and are not compared numerically across vendors. | 32 GPU cores | 20 GPU cores | A: 12 more |
| Memory | |||
| Memory type | Unified memory | Unified memory | equal |
Chip
GPU chip
AApple M4 Max
BApple M4 Pro
differsArchitecture
AApple Silicon
BApple Silicon
equalCompute units
A32 GPU cores
B20 GPU cores
A: 12 moreSM (NVIDIA), CU (AMD) and Xe-core (Intel) are different units and are not compared numerically across vendors.
Memory
Memory type
AUnified memory
BUnified memory
equal
“More” does not always mean “better”: higher power draw or size is a system requirement, not an advantage (such bars are dimmed).
Compare with AI
An AI model reviews the specs and benchmarks of this pair and gives a plain-language verdict on who each model suits.
Questions and answers
Which is faster: Apple M4 Max (GPU, 32 cores) or Apple M4 Pro (GPU, 20 cores)?
Apple M4 Max (GPU, 32 cores) leads in every scenario with comparable benchmarks: rendering and compute. This does not imply an advantage in tasks without benchmarks.
See also
Data sources (2)
- Apple — specifications of Apple M4 Max (GPU, 32 cores), specifications of Apple M4 Pro (GPU, 20 cores)checked November 14, 2026
- Blender Open Data (Blender Foundation) — benchmark Blender Benchmark 4.2.0, benchmark Blender Benchmark 4.5.0, benchmark Blender Benchmark 5.1.1, benchmark Blender Benchmark 5.2.0, benchmark Blender Benchmark 3.6.0, benchmark Blender Benchmark 4.0.0, benchmark Blender Benchmark 4.1.0, benchmark Blender Benchmark 4.3.0, benchmark Blender Benchmark 4.4.0, benchmark Blender Benchmark 5.0.0, benchmark Blender Benchmark 5.1.0, benchmark Blender Benchmark 5.3.0checked November 14, 2026
How we compare: methodology. Where the data comes from: sources.