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Apple M1 Max (GPU, 24 cores) vs Apple M1 Pro (GPU, 16 cores): specs and benchmark comparison

AApple · Apple Silicon

Apple M1 Max (GPU, 24 cores)

  • 24 GPU cores

2021

BApple · Apple Silicon

Apple M1 Pro (GPU, 16 cores)

  • 16 GPU cores

2021

Short verdict

Apple M1 Max (GPU, 24 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 M1 Max (GPU, 24 cores)Apple M1 Pro (GPU, 16 cores) →
  • Rendering and compute

    A +74.6%

    Apple M1 Max (GPU, 24 cores) leads in this scenario (up to 74.6% 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 M1 Max (GPU, 24 cores) is better2

  • Blender Benchmark 4.5.0 64.2% faster794 samples/min vs 483 samples/min

  • Compute units 8 more24 GPU cores vs 16 GPU cores

Where Apple M1 Pro (GPU, 16 cores) is better0

No advantages found in our data.

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

    A ahead by 64.2%

    Position among tested models (18, Metal)

    B · 483A · 794
    02,0004,0006,000
    Each dot is one model’s median in this benchmark. The scale starts at zero, samples/min.

    Apple M1 Max (GPU, 24 cores) is ahead by 64.2% in this benchmark.

    About the measurement and source
    A · Apple M1 Max (GPU, 24 cores)

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

    Blender Open Data (Blender Foundation)

    Median of 26 submissions (0 outliers excluded), interquartile range 781.6–801.43; submissions 2025-07-31 to 2026-07-11; METAL backend. Snapshot 2026-11-14.

    B · Apple M1 Pro (GPU, 16 cores)

    483.4 samples/min · community measurement, sample 44 · November 14, 2026

    Blender Open Data (Blender Foundation)

    Median of 44 submissions (0 outliers excluded), interquartile range 438.63–486.07; submissions 2025-07-17 to 2026-09-23; 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 (5)
BenchmarkABDifference
Blender Benchmark 3.3.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)709.7425.5A +66.8%
Blender Benchmark 3.4.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)725.6437.2A +66%
Blender Benchmark 3.6.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)836.7479.1A +74.6%
Blender Benchmark 4.0.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)773.1466.5A +65.7%
Blender Benchmark 4.1.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)825.3481.2A +71.5%

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

Reference results (8)
BenchmarkABDifference
Blender Benchmark 4.2.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)791.1482.1reference
Blender Benchmark 5.1.1GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)831.6510.5reference
Blender Benchmark 5.2.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)834.5541.2reference
Blender Benchmark 3.5.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)864.6523.5reference
Blender Benchmark 4.3.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)794.7483reference
Blender Benchmark 4.4.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)797.5483.3reference
Blender Benchmark 5.0.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)755.4454.5reference
Blender Benchmark 5.1.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal)830.4509reference

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

Specifications

Chip

  • GPU chip

    AApple M1 Max

    BApple M1 Pro

    differs
  • Architecture

    AApple Silicon

    BApple Silicon

    equal
  • Compute units

    A24 GPU cores

    B16 GPU cores

    A: 8 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 M1 Max (GPU, 24 cores) or Apple M1 Pro (GPU, 16 cores)?

Apple M1 Max (GPU, 24 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 M1 Max (GPU, 24 cores), specifications of Apple M1 Pro (GPU, 16 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 5.1.0checked November 14, 2026

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

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