#Macbook vs macbook pro geekbench mac
On the benchmarks reported above, there is little to choose between the M1 Pro fitted in a MacBook Pro 16-inch, and the M1 Max in a Mac Studio. Overall transfer rates were measured using Stibium, on ten sets of test files, and suggest that the internal SSD in the Mac Studio is slightly faster than that in the MacBook Pro. Search request times were 1.447 s (Pro) and 1.367 s (Max).Īs both Macs have 2 TB internal SSDs, direct comparison should be both possible and meaningful.Total processing times were 740.75 ms (Pro) and 656.44 ms (Max).Although no large differences were seen, there is the suggestion that the M1 Max is slightly quicker, possibly reflecting parts of the task being run on the GPU rather than the ANE, which is believed to be identical between the two chips. Log entries give total processing time for the ANE phases of this task, and overall time to handle the search request at the end. OpenCL is another problem, as support for that is now deprecated in favour of Metal and Apple’s Accelerate libraries.Īlthough there are several benchmarks which could be applied to the Apple Neural Engine (ANE) in M1 chips, I decided to use a standard task of Visual Look Up which I know to run at least in part on the ANE. I’m very grateful to Damiano for pointing out that, while a graphics benchmark, Cinebench doesn’t use the GPU at all, and its results therefore represent CPU computation rather than GPU. Cinebench multi-core scores were 12,358 (Pro) and 12,377 (Max).While OpenCL returned a higher (faster) score on the M1 Max, there was essentially no difference in Cinebench scores: Multi-core scores were 12532 (Pro) and 12805 (Max).Ĭinebench and Geekbench Compute (OpenCL) scores are harder to interpret.Single-core scores were 1774 (Pro) and 1790 (Max).Single- and multi-core scores were essentially the same: Geekbench was used to compare performance on more general computation tasks. Performance on the two chips was identical for integer, floating-point, NEON and Accelerate. For these tests, E cores were assessed with a workload of two threads run at minimum QoS, which fully loads both the E cores and runs them at maximum frequency, without any contribution from the P cores. This has the strange effect that the time taken to run a single-threaded test is nearly twice that required to run two threads. The E cores on both chips are managed similarly by macOS: with a single low QoS thread, they’re run at low frequency (below 1 GHz), but when loaded with two or more threads, frequency is boosted to 2 GHz. Performance on the two chips was identical for integer, floating-point, NEON (vector processor) and Accelerate (Apple’s performance library, presumed here to use NEON too). The P cores were assessed with a workload of eight threads run at maximum Quality of Service (QoS), which fully loads all the P cores without any contribution from the E cores.
#Macbook vs macbook pro geekbench code
These were tested separately using tight loops of assembly code in AsmAttic. My own app Mints for Neural Engine performance.īoth the M1 Pro and Max have the same general-purpose CPU cores: eight Performance (P) cores, and two Efficiency (E) cores.My own app Stibium for SSD performance,.My own app AsmAttic for in-core performance,.Mac Studio M1 Max, 24-core GPU, 32 GB memory, 2 TB SSD, costing £2599, to which you must add a keyboard, input device and display.MacBook Pro 16-inch M1 Pro, 16-core GPU, 32 GB memory, 2 TB SSD, costing £3,399.Now that I have a Studio (Max) sat behind my M1 Pro MacBook Pro, this article compares their benchmark results. A month ago, I explained what performance to expect in Apple’s new Mac Studio models.
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