Apple M2 Max vs Apple M2
The M2 Max delivers 3.8x the FP32 throughput of the M2 (14 vs 3.6 TFLOPS dense). The M2 Max also carries 72 GB more memory (96 GB vs 24 GB).
Apple M2 Max
Full specs →Apple M2
Full specs →Specifications
Performance (TFLOPS)
FLOPS by Precision
What actually differs
The M2 Max is the newer part: Apple M2, launched in 2023, against the M2's Apple M2 from 2022. Newer architectures typically add lower-precision formats and better throughput per watt, so check the precision rows your workload actually uses.
Dense throughput for the M2 Max against the M2: FP32 14 vs 3.6 TFLOPS. Sparse figures, where the vendor publishes them, appear under each dense number in the performance table.
Memory is 96 GB against 24 GB, fed at 400 GB/s versus 100 GB/s. More memory per GPU means larger models fit before you have to shard across cards, which often matters more than raw TFLOPS for inference.
For LLM training and inference, weight the FP8 and FP16 rows and memory capacity most heavily. For scientific and HPC workloads, the FP64 row is the one to read.
Frequently asked questions
Is the M2 Max faster than the M2?
At FP32 precision the M2 Max reaches 14 TFLOPS dense against 3.6 TFLOPS for the M2. The performance table on this page lists every published precision for both GPUs.
Which has more memory, the M2 Max or the M2?
The M2 Max carries 96 GB of VRAM versus 24 GB for the M2. Memory bandwidth is 400 GB/s for the M2 Max and 100 GB/s for the M2.
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