The M2 Pro MacBook Pro 16" runs local models at 200 GB/s of memory bandwidth with 16 to 32 GB of unified memory. On Apple Silicon that memory is shared with the GPU, so the whole pool is available for weights: at 32 GB you can hold roughly a 42B dense model at Q4. The Pro roughly doubles the base chip's memory bus. That moves mid-size models from usable to comfortable without moving you into desktop money.
Apple no longer sells this configuration new. It stays fully evaluated here because the used market is where most of its local AI value now sits.
Memory bandwidth is faster than 35% of the Apple Silicon chips shipped in a Mac, against a 1228 GB/s peak.
Its memory ceiling is above 15% of them, against a 512 GB peak.
Every option Apple sells with this chip. The model list below recomputes against the one you pick.
Unified memory
Unified memory is the ceiling and it is soldered, so this is the decision you cannot revisit.
5,572 of 6,563 models fit, and 5,054 of them run with headroom rather than as a squeeze.
6,082 of 6,563 models fit, and 5,571 of them run with headroom rather than as a squeeze.
Every model in the database against this exact configuration, at 200 GB/s. Ratings and speeds are the same numbers the model pages show.
Showing 6563 of 6563 models
General · openbmb · 2026-05-21
General · Liquid AI · 2026-06-24
General · ktruestory · 2026-05-28
General · petrouil · 2026-07-23
General · radixark · 2026-07-27
General · goekdeniz-guelmez · 2026-07-31
Multimodal · Alibaba · 2026-02-28
Multimodal · Alibaba · 2026-02-28
General · weiboai · 2026-06-12
General · Liquid AI · 2026-07-28
General · Liquid AI · 2026-03-31
General · ma7ee7 · 2026-07-30
General · cagrigungor · 2026-08-06
Multimodal · Alibaba · 2026-02-28
Multimodal · Alibaba · 2026-02-28
General · Liquid AI · 2026-05-28
Multimodal · Liquid AI · 2026-01-05
General · Liquid AI · 2026-01-20
Reasoning · openonerec · 2026-06-09
General · Liquid AI · 2026-01-05
General · Liquid AI · 2026-01-04
General · farbodtavakkoli · 2026-06-17
General · ibm-granite · 2026-04-06
Multimodal · ibm-granite · 2026-04-16
General · Liquid AI · 2025-10-28
General · frontiersmind · 2026-08-03
Chat · Liquid AI · 2026-01-06
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Multimodal · Liquid AI · 2025-08-12
General · bytedance · 2025-10-28
General · ai21labs · 2026-01-06
Multimodal · Liquid AI · 2025-08-12
General · Liquid AI · 2025-12-25
General · Liquid AI · 2025-09-30
General · Liquid AI · 2025-08-22
General · Liquid AI · 2025-09-03
General · Liquid AI · 2025-09-03
General · Liquid AI · 2025-08-25
General · Liquid AI · 2025-09-03
General · Liquid AI · 2025-09-03
General · Liquid AI · 2026-01-05
General · hmellor · 2025-07-22
General · ibm-granite · 2025-04-30
General · Liquid AI · 2025-07-10
General · openonerec · 2025-12-30
General · nanbeige · 2026-07-21
General · amd · 2025-05-17
General · stefanruseti · 2025-06-04
General · lgai-exaone · 2025-07-11
General · Liquid AI · 2025-07-10
Multimodal · Liquid AI · 2025-10-22
General · Liquid AI · 2025-09-22
General · Liquid AI · 2025-07-10
General · NCAI · 2025-12-29
Multimodal · Alibaba · 2026-02-27
Multimodal · Alibaba · 2026-02-27
General · Alibaba · 2025-09-23
General · ibm-granite · 2025-09-16
General · pfnet · 2025-02-05
General · ibm-granite · 2025-09-16
General · Liquid AI · 2025-10-07
General · sapientinc · 2026-05-17
General · ibm-granite · 2025-10-07
General · nvidia · 2026-03-02
General · fableforge-ai · 2026-07-05
General · viorikaai-org · 2026-07-05
General · bananamind · 2026-07-17
General · maliosdark · 2026-07-09
General · raidium · 2026-06-15
Multimodal · NCAI · 2025-12-29
Embedding · taide · 2026-06-12
Multimodal · davidau · 2026-02-02
General · Alibaba · 2025-04-27
Multimodal · Google · 2026-03-02
Multimodal · zai-org
Multimodal · datalab-to
General · Alibaba · 2025-04-28
Multimodal · openbmb
General · Alibaba · 2025-04-28
Reasoning · DeepSeek · 2025-01-20
Multimodal · tencent
General · distil-labs
General · farbodtavakkoli
General · internscience · 2026-07-13
General · jinaai
Multimodal · ath-maas
Reasoning · Microsoft · 2025-04-29
Multimodal · Liquid AI
Reasoning · typhoon-ai
Multimodal · paddlepaddle
General · Liquid AI
Chat · uzlm · 2025-09-03
Multimodal · paddlepaddle
General · adamlucek
Coding · shahriarferdoush
General · ahczhg
General · onnx-community · 2025-04-28
General · etherll
General · baidu
General · Liquid AI
General · openbmb
Multimodal · lkhl
General · benjamin
General · lemonelabs
General · openbmb · 2025-06-05
General · farbodtavakkoli
General · novachronoai
Multimodal · paddlepaddle
General · kamilamila
General · launch
General · arcee-ai
General · getonit
General · Liquid AI
General · saidutta69
General · agentica-org
General · novaciano
General · kgrabko
General · ordenwills
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Reasoning · nvidia
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Reasoning · jackrong
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General · lgai-exaone · 2025-03-12
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Nobody has submitted a benchmark on the M2 Pro yet, so every speed on this page is the formula estimate rather than a measured run. The estimate is bandwidth-driven and calibrated against chips that do have data, which makes it a good guide and not a promise.
ToolPiper contributes a result anonymously when you run the benchmark, and the leaderboard shows every chip that already has one.
What each step actually changes for local models, rather than which one is newer.
MacBook Pro 16" M2 Max
2x the memory bandwidth, up to 96 GB instead of 32 GB
Newer generationMacBook Pro 16" M5 Pro
1.5x the memory bandwidth, up to 64 GB instead of 32 GB
Used market alternativeMacBook Pro 16" M1 Pro
Same bandwidth and the same memory ceiling
Same chip, other MacMacBook Pro 14" M2 Pro
The same chip in a different Mac
Same chip, other MacMac mini M2 Pro
The same chip in a different Mac
Apple has not announced any of this. The M7 Max and Ultra are the first parts Apple designed after cancelling a generation to reach them, so extrapolating from the M5 under-represents them. These rows assume LPDDR6, whose wider channels grow every bus by half, at its top speed bin by the time the Max and Ultra ship. The 1.5 TB Ultra ceiling is Bloomberg's reported design target, and whether that configuration ships depends on the memory market. Stacked memory or a new package fabric would land above these numbers; nobody outside Apple can price that yet.
Projected chip · expected 2027
691 GB/s · 24 to 96 GB unified memory
18-core CPU · 20 or 24-core GPU · 76 TOPS Neural Engine
Would hold about a 129B model at Q4
On a PC the model has to fit in GPU VRAM, which is a separate pool from system RAM and usually the smaller of the two. Apple Silicon has one pool. The M2 Pro's 200 GB/s bus is shared by CPU, GPU, and Neural Engine, so a 32 GB machine can hand almost all of that to a model with no copy across a bus.
Apple stopped selling this one, which is exactly why it is interesting. The 16-inch chassis has the most thermal headroom Apple ships in a laptop, so sustained token throughput stays close to the burst figure. A used M2 Pro at 32 GB still gives you 200 GB/s and a hard 42B ceiling, and neither number degrades with age the way a battery does.
No. A 70B model at Q4_K_M needs about 46 GB, and the largest M2 Pro MacBook Pro 16" tops out at 32 GB, which leaves about 28 GB for weights. The practical ceiling on this machine is around 42B parameters at Q4.
Memory is the only spec that changes what you can run at all. 16 GB holds about a 20B model at Q4; 32 GB holds about 42B. It is soldered, so this is a one-time decision, and it is the upgrade worth paying for before core count.
Token generation is bandwidth-bound, so M2 Pro throughput scales with its 200 GB/s memory bus. Divide bandwidth by the size of the weights actually read per token to get the ceiling, then expect roughly half of that in practice. A 7B model at Q4 reads about 4 GB per token pass, so the M2 Pro lands in the tens of tokens per second and a 70B model lands in the single digits.
For inference, the specs that matter do not age: 200 GB/s and up to 32 GB of unified memory are the same numbers today as they were in 2023. A used M2 Pro at the top memory option usually beats a new base-tier machine at the same price on both. Check the battery and the display, not the silicon.
ToolPiper downloads, manages, and runs local models on Apple Silicon. Free, and nothing leaves the machine.