← All MacBook Pro 14" models

MacBook Pro 14" M3 Max

The M3 Max MacBook Pro 14" runs local models at 300 to 400 GB/s of memory bandwidth with 36 to 128 GB of unified memory. On Apple Silicon that memory is shared with the GPU, so the whole pool is available for weights: at 128 GB you can hold roughly a 172B dense model at Q4. The Max is where the bus gets wide enough that model size, not bandwidth, becomes the thing you plan around.

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.

By , Founder & Lead Engineer— Updated

Specifications

ChipApple M3 Max
CPU cores14 or 16
GPU cores30 or 40
Unified memory36, 48, 64, 96, or 128 GB
Memory bandwidth300 to 400 GB/s
Neural Engine18 TOPS
Released2023
AvailabilityUsed market

Memory bandwidth is faster than 55% of the Apple Silicon chips shipped in a Mac, against a 1228 GB/s peak.

Its memory ceiling is above 65% of them, against a 512 GB peak.

Pick your configuration

Every option Apple sells with this chip. The model list below recomputes against the one you pick.

GPU cores

Unified memory

Apple couples memory to the core count on this chip, so the options change with the bin above.

What each memory option runs

Unified memory is the ceiling and it is soldered, so this is the decision you cannot revisit.

36 GB unified memory

31 GB usable for weights · 300 GB/s

6,120 of 6,563 models fit, and 5,827 of them run with headroom rather than as a squeeze.

Largest model at Q4
Chinese Mixtral 8x7B · 46.91B
Best all-round pick
Kimi K3 DSpark · Q8_0 · ~70 tok/s

48 GB unified memory

42 GB usable for weights · 400 GB/s

6,273 of 6,563 models fit, and 6,033 of them run with headroom rather than as a squeeze.

Largest model at Q4
Yi 34Bx2 MoE 60B DPO · 60.81B
Best all-round pick
Kimi K3 DSpark · Q8_0 · ~93 tok/s

64 GB unified memory

56 GB usable for weights · 400 GB/s

6,357 of 6,563 models fit, and 6,086 of them run with headroom rather than as a squeeze.

Largest model at Q4
Hy3 REAP 48e · 84.02B
Best all-round pick
Kimi K3 DSpark · Q8_0 · ~93 tok/s

96 GB unified memory

84 GB usable for weights · 300 GB/s

6,384 of 6,563 models fit, and 6,271 of them run with headroom rather than as a squeeze.

Largest model at Q4
LING 3.0 FLASH ABLITERATED · 127.49B
Best all-round pick
Ornith 1.0 35B · Q8_0 · ~58 tok/s

128 GB unified memory

112 GB usable for weights · 400 GB/s

6,420 of 6,563 models fit, and 6,334 of them run with headroom rather than as a squeeze.

Largest model at Q4
Kimi K2 Thinking converted · 170.27B
Best all-round pick
Ornith 1.0 35B · Q8_0 · ~77 tok/s

What a 36 GB M3 Max MacBook Pro 14" can run

Every model in the database against this exact configuration, at 300 GB/s. Ratings and speeds are the same numbers the model pages show.

Showing 6563 of 6563 models

General · radixark · 2026-07-27

Q8_0Excellent
3.0 GB8% of RAM~70 tok/sEstimated2.25B params
Run with ToolPiper

General · openbmb · 2026-05-21

Q8_0Excellent
1.7 GB5% of RAM~146 tok/sEstimated1.08B params
Run with ToolPiper

General · farbodtavakkoli · 2026-06-17

Q8_0Excellent
10.8 GB30% of RAMBenchmark needed9.23B params
Run with ToolPiper

General · Liquid AI · 2026-05-28

Q8_0Excellent
9.9 GB28% of RAMBenchmark needed8.47B params
Run with ToolPiper

General · Liquid AI · 2026-07-28

Q8_0Excellent
3.5 GB10% of RAM~58 tok/sEstimated2.7B params
Run with ToolPiper

General · Liquid AI · 2026-06-24

Q8_0Excellent
0.8 GB2% of RAM~683 tok/sEstimated0.23B params
Run with ToolPiper

General · goekdeniz-guelmez · 2026-07-31

Q8_0Excellent
3.0 GB8% of RAM~69 tok/sEstimated2.27B params
Run with ToolPiper

General · ktruestory · 2026-05-28

Q8_0Excellent
1.7 GB5% of RAM~146 tok/sEstimated1.08B params
Run with ToolPiper

General · petrouil · 2026-07-23

Q8_0Excellent
3.4 GB9% of RAMBenchmark needed2.61B params
Run with ToolPiper

General · weiboai · 2026-06-12

Q8_0Excellent
3.9 GB11% of RAM~51 tok/sEstimated3.09B params
Run with ToolPiper

General · ma7ee7 · 2026-07-30

Q8_0Excellent
4.0 GB11% of RAM~50 tok/sEstimated3.13B params
Run with ToolPiper

Multimodal · Alibaba · 2026-02-28

Q8_0Excellent
1.5 GB4% of RAM~181 tok/sEstimated0.87B params
Run with ToolPiper

Multimodal · Alibaba · 2026-02-28

Q8_0Excellent
3.0 GB8% of RAM~69 tok/sEstimated2.27B params
Run with ToolPiper

Multimodal · Alibaba · 2026-02-28

Q8_0Excellent
1.5 GB4% of RAM~181 tok/sEstimated0.87B params
Run with ToolPiper

Multimodal · Alibaba · 2026-02-28

Q8_0Excellent
3.0 GB8% of RAM~69 tok/sEstimated2.27B params
Run with ToolPiper

General · internscience · 2026-07-13

Q8_0Excellent
5.6 GB15% of RAM~35 tok/sEstimated4.54B params
Run with ToolPiper

Multimodal · ibm-granite · 2026-04-16

Q8_0Excellent
5.0 GB14% of RAM~39 tok/sEstimated4B params
Run with ToolPiper

General · Liquid AI · 2026-03-31

Q8_0Excellent
0.9 GB2% of RAM~449 tok/sEstimated0.35B params
Run with ToolPiper

General · nanbeige · 2026-07-21

Q8_0Excellent
5.2 GB14% of RAM~38 tok/sEstimated4.17B params
Run with ToolPiper

General · cagrigungor · 2026-08-06

Q8_0Excellent
0.8 GB2% of RAM~582 tok/sEstimated0.27B params
Run with ToolPiper

General · ibm-granite · 2026-04-06

Q8_0Excellent
4.3 GB12% of RAM~46 tok/sEstimated3.4B params
Run with ToolPiper

Multimodal · Liquid AI · 2026-01-05

Q8_0Excellent
2.3 GB6% of RAM~98 tok/sEstimated1.6B params
Run with ToolPiper

General · Liquid AI · 2026-01-20

Q8_0Excellent
1.8 GB5% of RAM~134 tok/sEstimated1.17B params
Run with ToolPiper

Reasoning · openonerec · 2026-06-09

Q8_0Excellent
1.4 GB4% of RAM~196 tok/sEstimated0.8B params
Run with ToolPiper

General · Liquid AI · 2026-01-05

Q8_0Excellent
1.8 GB5% of RAM~134 tok/sEstimated1.17B params
Run with ToolPiper

General · Liquid AI · 2026-01-04

Q8_0Excellent
1.8 GB5% of RAM~134 tok/sEstimated1.17B params
Run with ToolPiper

General · Liquid AI · 2025-12-25

Q8_0Excellent
3.4 GB9% of RAM~61 tok/sEstimated2.57B params
Run with ToolPiper

General · Liquid AI · 2026-01-05

Q8_0Excellent
3.4 GB9% of RAM~61 tok/sEstimated2.57B params
Run with ToolPiper

Multimodal · Alibaba · 2026-02-27

Q8_0Excellent
5.7 GB16% of RAM~34 tok/sEstimated4.66B params
Run with ToolPiper

Multimodal · Google · 2026-03-02

Q8_0Excellent
6.2 GB17% of RAM~31 tok/sEstimated5.12B params
Run with ToolPiper

Multimodal · Alibaba · 2026-02-27

Q8_0Excellent
5.7 GB16% of RAM~34 tok/sEstimated4.66B params
Run with ToolPiper

General · inclusionai · 2026-02-09

Q8_0Excellent
18.6 GB52% of RAMBenchmark needed16.26B params
Run with ToolPiper

General · Liquid AI · 2025-10-28

Q8_0Excellent
0.9 GB2% of RAM~449 tok/sEstimated0.35B params
Run with ToolPiper

General · ai21labs · 2026-01-06

Q8_0Excellent
3.9 GB11% of RAMBenchmark needed3.03B params
Run with ToolPiper

General · nvidia · 2026-03-02

Q8_0Excellent
4.8 GB13% of RAM~41 tok/sEstimated3.83B params
Run with ToolPiper

General · frontiersmind · 2026-08-03

Q8_0Excellent
1.2 GB3% of RAM~242 tok/sEstimated0.65B params
Run with ToolPiper

Multimodal · davidau · 2026-02-02

Q8_0Excellent
5.3 GB15% of RAM~37 tok/sEstimated4.3B params
Run with ToolPiper

Chat · Liquid AI · 2026-01-06

Q8_0Excellent
1.8 GB5% of RAM~134 tok/sEstimated1.17B params
Run with ToolPiper

General · ibm-granite · 2025-09-16

Q8_0Excellent
8.2 GB23% of RAMBenchmark needed6.94B params
Run with ToolPiper

Multimodal · Liquid AI · 2025-08-12

Q8_0Excellent
1.0 GB3% of RAM~349 tok/sEstimated0.45B params
Run with ToolPiper

General · openonerec · 2025-12-30

Q8_0Excellent
2.9 GB8% of RAM~74 tok/sEstimated2.13B params
Run with ToolPiper

General · bytedance · 2025-10-28

Q8_0Excellent
2.1 GB6% of RAM~110 tok/sEstimated1.43B params
Run with ToolPiper

General · Liquid AI · 2025-10-07

Q8_0Excellent
9.8 GB27% of RAMBenchmark needed8.34B params
Run with ToolPiper

Multimodal · Liquid AI · 2025-08-12

Q8_0Excellent
2.3 GB6% of RAM~99 tok/sEstimated1.58B params
Run with ToolPiper

Multimodal · Liquid AI · 2025-10-22

Q8_0Excellent
3.8 GB11% of RAM~52 tok/sEstimated3B params
Run with ToolPiper

General · Liquid AI · 2025-09-22

Q8_0Excellent
3.4 GB9% of RAM~61 tok/sEstimated2.57B params
Run with ToolPiper

General · Liquid AI · 2025-09-30

Q8_0Excellent
0.9 GB2% of RAM~449 tok/sEstimated0.35B params
Run with ToolPiper

General · Liquid AI · 2025-08-22

Q8_0Excellent
1.8 GB5% of RAM~134 tok/sEstimated1.17B params
Run with ToolPiper

General · Liquid AI · 2025-09-03

Q8_0Excellent
0.9 GB2% of RAM~449 tok/sEstimated0.35B params
Run with ToolPiper

General · Liquid AI · 2025-09-03

Q8_0Excellent
1.8 GB5% of RAM~134 tok/sEstimated1.17B params
Run with ToolPiper

General · Liquid AI · 2025-08-25

Q8_0Excellent
0.9 GB2% of RAM~449 tok/sEstimated0.35B params
Run with ToolPiper

General · Liquid AI · 2025-09-03

Q8_0Excellent
0.9 GB2% of RAM~449 tok/sEstimated0.35B params
Run with ToolPiper

General · Liquid AI · 2025-09-03

Q8_0Excellent
1.8 GB5% of RAM~134 tok/sEstimated1.17B params
Run with ToolPiper

General · NCAI · 2025-12-29

Q8_0Excellent
8.6 GB24% of RAMBenchmark needed7.25B params
Run with ToolPiper

General · hmellor · 2025-07-22

Q8_0Excellent
1.9 GB5% of RAM~127 tok/sEstimated1.24B params
Run with ToolPiper

General · inclusionai · 2025-11-25

Q8_0Excellent
18.6 GB52% of RAMBenchmark needed16.26B params
Run with ToolPiper

General · ibm-granite · 2025-04-30

Q8_0Excellent
7.9 GB22% of RAMBenchmark needed6.67B params
Run with ToolPiper

General · Liquid AI · 2025-07-10

Q8_0Excellent
1.8 GB5% of RAM~134 tok/sEstimated1.17B params
Run with ToolPiper

General · ibm-granite · 2025-09-16

Q8_0Excellent
4.3 GB12% of RAM~46 tok/sEstimated3.4B params
Run with ToolPiper

General · amd · 2025-05-17

Q8_0Excellent
2.2 GB6% of RAM~105 tok/sEstimated1.5B params
Run with ToolPiper

General · stefanruseti · 2025-06-04

Q8_0Excellent
1.9 GB5% of RAM~127 tok/sEstimated1.24B params
Run with ToolPiper

General · ibm-granite · 2025-09-16

Q8_0Excellent
4.1 GB11% of RAM~49 tok/sEstimated3.19B params
Run with ToolPiper

General · lgai-exaone · 2025-07-11

Q8_0Excellent
1.9 GB5% of RAM~123 tok/sEstimated1.28B params
Run with ToolPiper

General · Liquid AI · 2025-07-10

Q8_0Excellent
0.9 GB2% of RAM~449 tok/sEstimated0.35B params
Run with ToolPiper

General · Liquid AI · 2025-07-10

Q8_0Excellent
1.3 GB4% of RAM~212 tok/sEstimated0.74B params
Run with ToolPiper

Multimodal · NCAI · 2025-12-29

Q8_0Excellent
9.0 GB25% of RAMBenchmark needed7.58B params
Run with ToolPiper

General · typhoon-ai · 2025-09-23

Q8_0Excellent
5.0 GB14% of RAM~39 tok/sEstimated4.02B params
Run with ToolPiper

General · Alibaba · 2025-08-05

Q8_0Excellent
5.0 GB14% of RAM~39 tok/sEstimated4.02B params
Run with ToolPiper

General · Alibaba · 2025-09-23

Q8_0Excellent
1.3 GB4% of RAM~210 tok/sEstimated0.75B params
Run with ToolPiper

Reasoning · Microsoft · 2025-04-29

Q8_0Excellent
4.8 GB13% of RAM~41 tok/sEstimated3.84B params
Run with ToolPiper

General · pfnet · 2025-02-05

Q8_0Excellent
1.9 GB5% of RAM~122 tok/sEstimated1.29B params
Run with ToolPiper

General · bytedance-seed · 2025-04-09

Q8_0Excellent
11.0 GB30% of RAMBenchmark needed9.37B params
Run with ToolPiper

General · sapientinc · 2026-05-17

Q8_0Excellent
1.8 GB5% of RAM~133 tok/sEstimated1.18B params
Run with ToolPiper

General · z-lab · 2026-01-04

Q8_0Excellent
5.0 GB14% of RAM~39 tok/sEstimated4B params
Run with ToolPiper

General · ibm-granite · 2025-10-07

Q8_0Excellent
0.9 GB2% of RAM~449 tok/sEstimated0.35B params
Run with ToolPiper

General · fableforge-ai · 2026-07-05

Q8_0Excellent
2.2 GB6% of RAM~102 tok/sEstimated1.54B params
Run with ToolPiper

General · viorikaai-org · 2026-07-05

Q8_0Excellent
0.6 GB2% of RAM~3,143 tok/sEstimated0.05B params
Run with ToolPiper

Reasoning · jackrong · 2026-03-16

Q8_0Excellent
11.3 GB31% of RAM~16 tok/sEstimated9.65B params
Run with ToolPiper

General · bananamind · 2026-07-17

Q8_0Excellent
0.5 GB1% of RAM~15,714 tok/sEstimated0.01B params
Run with ToolPiper

General · lgai-exaone · 2025-03-12

Q8_0Excellent
3.2 GB9% of RAM~65 tok/sEstimated2.41B params
Run with ToolPiper

General · maliosdark · 2026-07-09

Q8_0Excellent
0.6 GB2% of RAM~3,143 tok/sEstimated0.05B params
Run with ToolPiper

General · raidium · 2026-06-15

Q8_0Excellent
0.5 GB1% of RAM~7,857 tok/sEstimated0.02B params
Run with ToolPiper

Embedding · taide · 2026-06-12

Q8_0Excellent
0.8 GB2% of RAM~524 tok/sEstimated0.3B params
Run with ToolPiper

General · Alibaba · 2025-04-27

Q8_0Excellent
1.3 GB4% of RAM~210 tok/sEstimated0.75B params
Run with ToolPiper

General · Alibaba · 2025-04-27

Q8_0Excellent
2.8 GB8% of RAM~77 tok/sEstimated2.03B params
Run with ToolPiper

Multimodal · Alibaba · 2025-01-26

Q8_0Excellent
4.7 GB13% of RAM~42 tok/sEstimated3.75B params
Run with ToolPiper

Multimodal · Google · 2026-03-02

Q8_0Excellent
9.4 GB26% of RAM~20 tok/sEstimated8B params
Run with ToolPiper

Multimodal · zai-org

Q8_0Excellent
2.0 GB6% of RAM~118 tok/sEstimated1.33B params
Run with ToolPiper

Multimodal · Alibaba

Q8_0Excellent
2.9 GB8% of RAM~74 tok/sEstimated2.13B params
Run with ToolPiper

Multimodal · datalab-to

Q8_0Excellent
1.3 GB4% of RAM~228 tok/sEstimated0.69B params
Run with ToolPiper

General · Alibaba · 2025-04-28

Q8_0Excellent
2.4 GB7% of RAM~91 tok/sEstimated1.72B params
Run with ToolPiper

General · huggingfacetb · 2025-07-08

Q8_0Excellent
3.9 GB11% of RAM~51 tok/sEstimated3.08B params
Run with ToolPiper

Multimodal · openbmb

Q8_0Excellent
2.0 GB5% of RAM~121 tok/sEstimated1.3B params
Run with ToolPiper

General · Alibaba · 2025-04-28

Q8_0Excellent
1.2 GB3% of RAM~262 tok/sEstimated0.6B params
Run with ToolPiper

Multimodal · rednote-hilab

Q8_0Excellent
3.9 GB11% of RAM~52 tok/sEstimated3.04B params
Run with ToolPiper

Reasoning · DeepSeek · 2025-01-20

Q8_0Excellent
2.5 GB7% of RAM~88 tok/sEstimated1.78B params
Run with ToolPiper

Multimodal · moonshotai

Q8_0Excellent
18.8 GB52% of RAMBenchmark needed16.41B params
Run with ToolPiper

Multimodal · tencent

Q8_0Excellent
1.7 GB5% of RAMBenchmark needed1.12B params
Run with ToolPiper

Multimodal · dots-studio

Q8_0Excellent
3.9 GB11% of RAM~52 tok/sEstimated3.04B params
Run with ToolPiper

General · distil-labs

Q8_0Excellent
0.9 GB2% of RAM~449 tok/sEstimated0.35B params
Run with ToolPiper

General · farbodtavakkoli

Q8_0Excellent
1.8 GB5% of RAM~130 tok/sEstimated1.21B params
Run with ToolPiper

Multimodal · raxcore-dev

Q8_0Excellent
3.0 GB8% of RAM~69 tok/sEstimated2.27B params
Run with ToolPiper

Multimodal · moonshotai

Q8_0Excellent
18.8 GB52% of RAMBenchmark needed16.41B params
Run with ToolPiper

General · huggingfacetb · 2025-06-19

Q8_0Excellent
3.9 GB11% of RAM~51 tok/sEstimated3.08B params
Run with ToolPiper

General · jinaai

Q8_0Excellent
2.2 GB6% of RAM~102 tok/sEstimated1.54B params
Run with ToolPiper

Multimodal · ath-maas

Q8_0Excellent
1.4 GB4% of RAM~185 tok/sEstimated0.85B params
Run with ToolPiper

Multimodal · Alibaba

Q8_0Excellent
2.9 GB8% of RAM~74 tok/sEstimated2.13B params
Run with ToolPiper

Multimodal · Liquid AI

Q8_0Excellent
1.0 GB3% of RAM~349 tok/sEstimated0.45B params
Run with ToolPiper

Reasoning · typhoon-ai

Q8_0Excellent
2.9 GB8% of RAM~74 tok/sEstimated2.13B params
Run with ToolPiper

Multimodal · paddlepaddle

Q8_0Excellent
1.6 GB4% of RAM~164 tok/sEstimated0.96B params
Run with ToolPiper

General · Liquid AI

Q8_0Excellent
0.9 GB2% of RAM~449 tok/sEstimated0.35B params
Run with ToolPiper

Chat · uzlm · 2025-09-03

Q8_0Excellent
1.9 GB5% of RAM~127 tok/sEstimated1.24B params
Run with ToolPiper

Multimodal · paddlepaddle

Q8_0Excellent
1.6 GB4% of RAM~164 tok/sEstimated0.96B params
Run with ToolPiper

Chat · baseten · 2025-09-12

Q8_0Excellent
4.1 GB11% of RAM~49 tok/sEstimated3.21B params
Run with ToolPiper

General · jetbrains

Q8_0Excellent
14.1 GB39% of RAMBenchmark needed12.15B params
Run with ToolPiper

General · adamlucek

Q8_0Excellent
1.9 GB5% of RAM~127 tok/sEstimated1.24B params
Run with ToolPiper

Coding · shahriarferdoush

Q8_0Excellent
1.9 GB5% of RAM~127 tok/sEstimated1.24B params
Run with ToolPiper

General · ahczhg

Q8_0Excellent
1.9 GB5% of RAM~127 tok/sEstimated1.24B params
Run with ToolPiper

General · onnx-community · 2025-04-28

Q8_0Excellent
1.0 GB3% of RAM~349 tok/sEstimated0.45B params
Run with ToolPiper

General · etherll

Q8_0Excellent
1.3 GB4% of RAM~212 tok/sEstimated0.74B params
Run with ToolPiper

General · baidu

Q8_0Excellent
0.9 GB3% of RAM~437 tok/sEstimated0.36B params
Run with ToolPiper

General · Liquid AI

Q8_0Excellent
1.8 GB5% of RAM~134 tok/sEstimated1.17B params
Run with ToolPiper

General · openbmb

Q8_0Excellent
1.7 GB5% of RAM~146 tok/sEstimated1.08B params
Run with ToolPiper

Multimodal · lkhl

Q8_0Excellent
2.7 GB7% of RAM~80 tok/sEstimated1.96B params
Run with ToolPiper

Multimodal · infly

Q8_0Excellent
3.0 GB8% of RAM~71 tok/sEstimated2.21B params
Run with ToolPiper

General · benjamin

Q8_0Excellent
1.7 GB5% of RAM~147 tok/sEstimated1.07B params
Run with ToolPiper

General · lemonelabs

Q8_0Excellent
1.8 GB5% of RAM~130 tok/sEstimated1.21B params
Run with ToolPiper

General · openbmb · 2025-06-05

Q8_0Excellent
1.0 GB3% of RAM~365 tok/sEstimated0.43B params
Run with ToolPiper

General · jetbrains

Q8_0Excellent
14.1 GB39% of RAMBenchmark needed12.15B params
Run with ToolPiper

General · farbodtavakkoli

Q8_0Excellent
2.5 GB7% of RAMBenchmark needed1.77B params
Run with ToolPiper

General · novachronoai

Q8_0Excellent
1.8 GB5% of RAM~130 tok/sEstimated1.21B params
Run with ToolPiper

Multimodal · paddlepaddle

Q8_0Excellent
1.6 GB4% of RAM~164 tok/sEstimated0.96B params
Run with ToolPiper
Q8_0Excellent
4.0 GB11% of RAM~50 tok/sEstimated3.13B params
Run with ToolPiper

General · kamilamila

Q8_0Excellent
1.2 GB3% of RAM~253 tok/sEstimated0.62B params
Run with ToolPiper

General · launch

Q8_0Excellent
2.5 GB7% of RAM~88 tok/sEstimated1.78B params
Run with ToolPiper

General · arcee-ai

Q8_0Excellent
7.3 GB20% of RAMBenchmark needed6.12B params
Run with ToolPiper
Q8_0Excellent
2.2 GB6% of RAM~105 tok/sEstimated1.5B params
Run with ToolPiper

General · Liquid AI

Q8_0Excellent
1.8 GB5% of RAM~130 tok/sEstimated1.21B params
Run with ToolPiper

General · menlo · 2025-06-25

Q8_0Excellent
5.0 GB14% of RAM~39 tok/sEstimated4.02B params
Run with ToolPiper
Q8_0Excellent
1.7 GB5% of RAM~146 tok/sEstimated1.08B params
Run with ToolPiper

General · moonshotai

Q8_0Excellent
18.8 GB52% of RAMBenchmark needed16.41B params
Run with ToolPiper

General · jangq-ai

Q8_0Excellent
17.6 GB49% of RAMBenchmark needed15.3B params
Run with ToolPiper

General · agentica-org

Q8_0Excellent
2.5 GB7% of RAM~88 tok/sEstimated1.78B params
Run with ToolPiper

General · novaciano

Q8_0Excellent
2.2 GB6% of RAM~105 tok/sEstimated1.5B params
Run with ToolPiper

General · dmusingu

Q8_0Excellent
2.9 GB8% of RAM~74 tok/sEstimated2.13B params
Run with ToolPiper

General · kgrabko

Q8_0Excellent
2.2 GB6% of RAM~105 tok/sEstimated1.5B params
Run with ToolPiper

General · ordenwills

Q8_0Excellent
0.9 GB2% of RAM~449 tok/sEstimated0.35B params
Run with ToolPiper
Q8_0Excellent
2.1 GB6% of RAM~113 tok/sEstimated1.39B params
Run with ToolPiper

General · carsenk

Q8_0Excellent
1.9 GB5% of RAM~127 tok/sEstimated1.24B params
Run with ToolPiper

General · dealignai

Q8_0Excellent
17.6 GB49% of RAMBenchmark needed15.3B params
Run with ToolPiper

30-core vs 40-core GPU

Apple ties the memory bus to the bin on this chip: 300 GB/s at 30 cores and 400 GB/s at 40. That moves tokens per second. It does not move which models fit, because that is memory, not cores.

ConfigurationMemory bandwidthMemory optionsModels that fit
14-core CPU, 30-core GPU300 GB/s36, 96 GBIdentical
16-core CPU, 40-core GPU400 GB/s48, 64, 128 GBIdentical

On openbuddy zero 56b v21.2 32k the 30-core generates about 8 tok/s and the 40-core about 10 tok/s, a 33% difference. Both hold the model at the same quantization.

Measured on the M3 Max

Nobody has submitted a benchmark on the M3 Max 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 comes next

Projection dated 2026-09-08

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.

M7 MaxProjected

Projected chip · expected 2027

1382 GB/s · 48 to 384 GB unified memory

20-core CPU · 56 or 64-core GPU · 76 TOPS Neural Engine

Would hold about a 521B model at Q4

Why unified memory is the number that matters

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 M3 Max's 400 GB/s bus is shared by CPU, GPU, and Neural Engine, so a 128 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 14-inch chassis cools well enough to hold its clocks through a long generation run, and it is the smallest machine Apple puts a Max chip in. A used M3 Max at 128 GB still gives you 400 GB/s and a hard 172B ceiling, and neither number degrades with age the way a battery does.

Common questions

Can the M3 Max MacBook Pro 14" run a 70B model?

Yes, at 128 GB. A 70B model at Q4_K_M needs about 46 GB including an 8K context, and 128 GB of unified memory leaves about 112 GB for weights once macOS takes its share. At 36 GB it does not fit at any quantization worth running.

How much unified memory should I get with the M3 Max MacBook Pro 14"?

Memory is the only spec that changes what you can run at all. 36 GB holds about a 47B model at Q4; 128 GB holds about 172B. It is soldered, so this is a one-time decision, and it is the upgrade worth paying for before core count.

How fast are local LLMs on the M3 Max?

Token generation is bandwidth-bound, so M3 Max throughput scales with its 400 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 M3 Max lands in the tens of tokens per second and a 70B model lands in the single digits.

Is the 40-core GPU worth it over the 30-core on the M3 Max?

For throughput, yes: Apple ties bandwidth to the bin here, so the 30-core runs at 300 GB/s and the 40-core at 400 GB/s, about 33% more. For fit, no: both bins hold exactly the same models, because that is set by memory rather than by cores.

Is a used M3 Max MacBook Pro 14" still worth buying for local AI?

For inference, the specs that matter do not age: 400 GB/s and up to 128 GB of unified memory are the same numbers today as they were in 2023. A used M3 Max 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.

Run these models on your MacBook Pro 14"

ToolPiper downloads, manages, and runs local models on Apple Silicon. Free, and nothing leaves the machine.