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Apple M2 Max (GPU, 38 cores) vs Apple M4 Pro (GPU, 20 cores): specs and benchmark comparison

AApple · Apple Silicon

Apple M2 Max (GPU, 38 cores)

  • 38 GPU cores

2023

BApple · Apple Silicon

Apple M4 Pro (GPU, 20 cores)

  • 20 GPU cores

2024

Short verdict

Apple M4 Pro (GPU, 20 cores) leads in every scenario with comparable benchmarks: rendering and compute. This does not imply an advantage in tasks without benchmarks.

Compare with AI
← Apple M2 Max (GPU, 38 cores)Apple M4 Pro (GPU, 20 cores) →

  • Rendering and compute

    B +42.9%

    Apple M4 Pro (GPU, 20 cores) leads in this scenario (up to 42.9% 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 M2 Max (GPU, 38 cores) is better1

  • Compute units 18 more38 GPU cores vs 20 GPU cores

Where Apple M4 Pro (GPU, 20 cores) is better1

  • Blender Benchmark 4.5.0 42.9% faster2,574 samples/min vs 1,801 samples/min

Benchmarks

Results are compared within one benchmark, one version and the same conditions.

  • Blender Benchmark 4.5.0

    GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) · samples/min, higher is better

    B ahead by 42.9%

    Position among tested models (18, Metal)

    A · 1,801B · 2,574
    02,0004,0006,000
    Each dot is one model’s median in this benchmark. The scale starts at zero, samples/min.

    Apple M4 Pro (GPU, 20 cores) is ahead by 42.9% in this benchmark.

    About the measurement and source
    A · Apple M2 Max (GPU, 38 cores)

    1,801.3 samples/min · community measurement, sample 21 · November 14, 2026

    Blender Open Data (Blender Foundation)

    Median of 21 submissions (4 outliers excluded), interquartile range 1784.05–1811.88; submissions 2025-07-17 to 2026-04-08; 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.

Reference results (14)
BenchmarkABDifference
Blender Benchmark 4.2.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,699.12,548.3reference
Blender Benchmark 5.1.1GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,769.72,985.4reference
Blender Benchmark 5.2.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,745.82,919.7reference
Blender Benchmark 3.3.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,449.3—no pair
Blender Benchmark 3.4.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,506.1—no pair
Blender Benchmark 3.5.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,918.9—no pair
Blender Benchmark 3.6.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,915.71,877.9reference
Blender Benchmark 4.0.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,7661,751.5reference
Blender Benchmark 4.1.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,756.82,297reference
Blender Benchmark 4.3.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,778.52,480.1reference
Blender Benchmark 4.4.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,799.42,521.8reference
Blender Benchmark 5.0.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,593.92,630.2reference
Blender Benchmark 5.1.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,648.62,945.1reference
Blender Benchmark 5.3.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,558.7—no pair

Each benchmark version has its own scale: numbers are compared only within a row.

Specifications

Chip

  • GPU chip

    AApple M2 Max

    BApple M4 Pro

    differs

  • Architecture

    AApple Silicon

    BApple Silicon

    equal

  • Compute units

    A38 GPU cores

    B20 GPU cores

    A: 18 more

    SM (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.

AI verdict

Questions and answers

Which is faster: Apple M2 Max (GPU, 38 cores) or Apple M4 Pro (GPU, 20 cores)?

Apple M4 Pro (GPU, 20 cores) leads in every scenario with comparable benchmarks: rendering and compute. This does not imply an advantage in tasks without benchmarks.

Data sources (2)
  • Apple — specifications of Apple M2 Max (GPU, 38 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 3.3.0, benchmark Blender Benchmark 3.4.0, benchmark Blender Benchmark 3.5.0, 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.

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