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Apple M2 Max (GPU, 30 cores) vs Apple M3 Pro (GPU, 18 cores): specs and benchmark comparison

AApple · Apple Silicon

Apple M2 Max (GPU, 30 cores)

  • 30 GPU cores

2023

BApple · Apple Silicon

Apple M3 Pro (GPU, 18 cores)

  • 18 GPU cores

2023

Short verdict

Apple M3 Pro (GPU, 18 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, 30 cores)Apple M3 Pro (GPU, 18 cores) →

  • Rendering and compute

    B +27.1%

    Apple M3 Pro (GPU, 18 cores) leads in this scenario (up to 27.1% 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 M2 Max (GPU, 30 cores) is better1

  • Compute units 12 more30 GPU cores vs 18 GPU cores

Where Apple M3 Pro (GPU, 18 cores) is better1

  • Blender Benchmark 4.2.0 27.1% faster1,771 samples/min vs 1,393 samples/min

Benchmarks

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

  • Blender Benchmark 4.2.0

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

    B ahead by 27.1%

    Position among tested models (15, Metal)

    A · 1,393B · 1,771
    02,0004,0006,000
    Each dot is one model’s median in this benchmark. The scale starts at zero, samples/min.

    Apple M3 Pro (GPU, 18 cores) is ahead by 27.1% in this benchmark.

    About the measurement and source
    A · Apple M2 Max (GPU, 30 cores)

    1,393.1 samples/min · community measurement, sample 26 · November 14, 2026

    Blender Open Data (Blender Foundation)

    Median of 26 submissions (2 outliers excluded), interquartile range 1381.31–1398.38; submissions 2024-07-31 to 2025-07-18; METAL backend. Snapshot 2026-11-14.

    B · Apple M3 Pro (GPU, 18 cores)

    1,770.5 samples/min · community measurement, sample 46 · November 14, 2026

    Blender Open Data (Blender Foundation)

    Median of 46 submissions (2 outliers excluded), interquartile range 1745.51–1785.54; submissions 2024-07-17 to 2025-06-04; 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 (1)
BenchmarkABDifference
Blender Benchmark 4.0.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,4451,499.6B +3.8%

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

Reference results (12)
BenchmarkABDifference
Blender Benchmark 4.5.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,466.31,758.3reference
Blender Benchmark 5.1.1GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,400.51,955.8reference
Blender Benchmark 5.2.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,448.11,846.2reference
Blender Benchmark 3.4.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,222—no pair
Blender Benchmark 3.5.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,563.71,324.4reference
Blender Benchmark 3.6.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,551.81,315reference
Blender Benchmark 4.1.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,425.31,510.1reference
Blender Benchmark 4.3.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,453.21,712.5reference
Blender Benchmark 4.4.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,478.11,756.8reference
Blender Benchmark 5.0.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,322.7—no pair
Blender Benchmark 5.1.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)1,413.81,960reference
Blender Benchmark 3.3.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)—1,127.2no pair

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

Specifications

Chip

  • GPU chip

    AApple M2 Max

    BApple M3 Pro

    differs

  • Architecture

    AApple Silicon

    BApple Silicon

    equal

  • Compute units

    A30 GPU cores

    B18 GPU cores

    A: 12 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, 30 cores) or Apple M3 Pro (GPU, 18 cores)?

Apple M3 Pro (GPU, 18 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, 30 cores), specifications of Apple M3 Pro (GPU, 18 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 3.4.0, 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 3.3.0checked November 14, 2026

How we compare: methodology. Where the data comes from: sources.

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