Apple · M5 Max · Laptop

Best AI Models for MacBook Pro 16" M5 Max (128 GB)

Runs 27–31B and 120B MoE models well; dense 70B fits but is slow at 9 tok/s.

128 GB unified124.5 GB for models614 GB/s68 TFLOPS FP162026

Buy$5,399

Memory

36 GB48 GB64 GB128 GB$5,399

Same chip in

MacBook Pro 16"$5,399 Mac StudioMacBook Pro 14"

What LLMs can the MacBook Pro 16" M5 Max run?

#	Model	Speed	Quant · Memory
1	Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB · 24.7 t/s	24.7 tok/s	Q4_K_M · 17.9 GB
2	Qwen3.6 27BAlibaba Q4_K_M · 17.9 GB · 24.7 t/s	24.7 tok/s	Q4_K_M · 17.9 GB
3	Gemma 4 31B ITGoogle Q4_K_M · 21.7 GB · 21.1 t/s	21.1 tok/s	Q4_K_M · 21.7 GB
4	Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB · 80.7 t/s	80.7 tok/s	Q4_K_M · 16.5 GB
5	NVIDIA Nemotron 3.5 Lightning 30B A3B BF16NVIDIA Q4_K_M · 19.3 GB · 72.7 t/s	72.7 tok/s	Q4_K_M · 19.3 GB

#	Model	Speed	Quant · Memory
1	Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB · 24.7 t/s	24.7 tok/s	Q4_K_M · 17.9 GB
2	Gemma 4 31B ITGoogle Q4_K_M · 21.7 GB · 21.1 t/s	21.1 tok/s	Q4_K_M · 21.7 GB
3	Qwen3.6 35B A3BAlibaba Q4_K_M · 22.0 GB · 67.8 t/s	67.8 tok/s	Q4_K_M · 22.0 GB
4	Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB · 80.7 t/s	80.7 tok/s	Q4_K_M · 16.5 GB
5	NVIDIA Nemotron 3.5 Lightning 30B A3B BF16NVIDIA Q4_K_M · 19.3 GB · 72.7 t/s	72.7 tok/s	Q4_K_M · 19.3 GB

#	Model	Speed	Quant · Memory
1	Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB · 24.7 t/s	24.7 tok/s	Q4_K_M · 17.9 GB
2	Gemma 4 31B ITGoogle Q4_K_M · 21.7 GB · 21.1 t/s	21.1 tok/s	Q4_K_M · 21.7 GB
3	Qwen3.5 27BAlibaba Q4_K_M · 17.9 GB · 24.7 t/s	24.7 tok/s	Q4_K_M · 17.9 GB
4	Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB · 80.7 t/s	80.7 tok/s	Q4_K_M · 16.5 GB
5	NVIDIA Nemotron 3.5 Lightning 30B A3B BF16NVIDIA Q4_K_M · 19.3 GB · 72.7 t/s	72.7 tok/s	Q4_K_M · 19.3 GB

#	Model	Speed	Math Score	Quant · Memory
1	Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB · 24.7 t/s	24.7 tok/s		Q4_K_M · 17.9 GB
2	Qwen3.6 27BAlibaba Q4_K_M · 17.9 GB · 24.7 t/s	24.7 tok/s		Q4_K_M · 17.9 GB
3	Qwen3.6 35B A3BAlibaba Q4_K_M · 22.0 GB · 67.8 t/s	67.8 tok/s		Q4_K_M · 22.0 GB
4	Gemma 4 31B ITGoogle Q4_K_M · 21.7 GB · 21.1 t/s	21.1 tok/s	overall	Q4_K_M · 21.7 GB
5	NVIDIA Nemotron 3.5 Lightning 30B A3B BF16NVIDIA Q4_K_M · 19.3 GB · 72.7 t/s	72.7 tok/s		Q4_K_M · 19.3 GB

#	Model	Speed ↓	Quant · Memory
1	Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 132 t/s	132 tok/s	Q4_K_M · 3.4 GB
2	GPT OSS 20BOpenAI Q4_K_M · 13.1 GB · 92.4 t/s	92.4 tok/s	Q4_K_M · 13.1 GB
3	Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB · 80.7 t/s	80.7 tok/s	Q4_K_M · 16.5 GB
4	NVIDIA Nemotron 3.5 Lightning 30B A3B BF16NVIDIA Q4_K_M · 19.3 GB · 72.7 t/s	72.7 tok/s	Q4_K_M · 19.3 GB
5	Qwen3 30B A3B Thinking 2507Alibaba Q4_K_M · 19.4 GB · 69.5 t/s	69.5 tok/s	Q4_K_M · 19.4 GB

#	Model	Speed	Agents Score	Quant · Memory
1	Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB · 24.7 t/s	24.7 tok/s		Q4_K_M · 17.9 GB
2	Qwen2.5 Coder 32B InstructAlibaba Q4_K_M · 24.3 GB · 21.0 t/s	21.0 tok/s		Q4_K_M · 24.3 GB
3	GPT OSS 120BOpenAI Q4_K_M · 70.8 GB · 65.5 t/s	65.5 tok/s		Q4_K_M · 70.8 GB
4	Gemma 4 31B ITGoogle Q4_K_M · 21.7 GB · 21.1 t/s	21.1 tok/s	overall	Q4_K_M · 21.7 GB
5	NVIDIA Nemotron 3.5 Lightning 30B A3B BF16NVIDIA Q4_K_M · 19.3 GB · 72.7 t/s	72.7 tok/s		Q4_K_M · 19.3 GB

See all 401 models on the MacBook Pro 16" M5 Max →Bars = traction for models without a Score yet

About the MacBook Pro 16" M5 Max (128 GB)

The MacBook Pro 16" M5 Max is one of the fastest 128 GB machines: it runs 27–31B and 120B MoE models well. Among 128 GB machines, only the M1 Ultra and M2 Ultra write faster. macOS keeps about 3.5 GB, leaving 124.5 GB for models. With 68 TFLOPS it reads long prompts faster than most 128 GB machines: a 4K-token prompt takes 17 s. At its $5,399 MSRP it gives 12.6 tok/s per $1,000, 5th of the 6 machines compared here. M5 Max generation, released 2026.

Speed in 128 GB#3614 GB/s

Prompt reading#368 TFLOPS

For models124.5 GBmacOS keeps 3.5 GB

ChipM5 Maxreleased 2026

MacBook Pro 16" M5 Max strengths and weaknesses

Strengths

Runs 120B MoE models: GPT OSS 120B at 65.5 tok/s in 70.8 GB
Room for long context: Qwen3.8 27B at Q4 uses 17.9 GB, leaving 106.6 GB free

Weaknesses

Slow on large dense models: Llama 3.3 70B Instruct at 9.2 tok/s
Slow prompt reading: A 32K-token prompt on Qwen3.8 27B waits 2.2 min for the first token
No CUDA: vLLM, AWQ, GPTQ and FP8 builds don't run; use GGUF or MLX

Memory for models

124.5 GB of 128 GB

35B MoE22 GB70B51.3 GB120B MoE70.8 GB127B82.8 GB

35B MoE22 GB127B82.8 GB

For models 124.5 GBmacOS keeps 3.5 GBModel size at Q4

Everything on the size ladder fits. Two 27B-class models together use 35.7 GB and leave 88.8 GB free.

Speed per dollar and per watt

NewUsed

On Qwen3.6 35B A3B (35B params, 3B active) at Q4_K_M. New means a shop price, either a street quote or the maker's own price; used is compared with used. The last two columns are the speed you get per $1,000 of price and per 100 W of power; higher is better. The MacBook Pro 16" M5 Max has no current new price, so it is shown at its MSRP.

Machine	New price	tok/s	tok/s per $1,000	tok/s per 100 W
RTX 509032 GB	about $5,376	213	39.7	37.1
Mac Studio M4 Max128 GB	about $3,499	64.2	18.3	44.3
Mac Studio M2 Ultra192 GB	about $5,599	75.9	13.6	25.7
DGX Spark128 GB	about $3,999	54.0	13.5	22.5
MacBook Pro 16" M5 Max128 GB	about $5,399	67.8	12.6	–
Mac Studio M3 Ultra256 GB	about $7,099	76.6	10.8	28.4

Machine	Used price	tok/s	tok/s per $1,000	tok/s per 100 W
RTX 409024 GB	about $3,000	151	50.3	33.6
RTX 509032 GB	about $6,400	213	33.3	37.1

Cost per token: the MacBook Pro 16" M5 Max against 24–256 GB machines and GPUs

On Qwen3.6 35B A3B (35B params, 3B active, Q4_K_M, 4K context). Speed, cost per token and power per token depend on the model.

NewUsed

Speed$ per 1M tokens

24–36 GB96–128 GB192+ GBthis laptopat MSRP

Cost per 1M output tokenson Qwen3.6 35B A3B · card over 3 years + power

$5.05

Machine, MSRP: $5.05
Power: not published

3-year cost of ownership$5,399

Or rent an A100 in the cloud$1.12/hr

Renting costs as much as buying after ≈4,800 hours (≈3.3 years at 4 h a day).

Power$/kWhUseh/dayKeepyears

Each dot is a machine or GPU; hover or tap it for its numbers, click to open it. Machines without a price for the chosen basis are left out. Machines without a published power figure are left out of Per watt and costed without power. How we calculate cost per token

Similar devices and alternatives

Other memory sizes of the same machine first, then machines and GPUs people weigh against it, each with the one reason it is worth a look. Speeds on Qwen3.6 35B A3B.

Same chip, 64 GB less memoryMacBook Pro 16" M5 Max (64 GB)Apple · 60.5 GB for models · M5 Max

same speed▼ 64 GBno price

Same family Same chip, 80 GB less memoryMacBook Pro 16" M5 Max (48 GB)Apple · 44.5 GB for models · M5 Max

same speed▼ 80 GBno price

Same family About as fastMac Studio M4 Max (128 GB)Apple · 124.5 GB for models · M4 Max

▼ 5% speedsame memory$3,499

Reads prompts 4× faster, 120 GB for modelsDGX SparkNVIDIA · 120 GB for models · GB10

▲ 4× prompts▼ 20% speed▼ 4.5 GB$3,999

2.2× faster if your models fit in 24 GBRTX 4090NVIDIA · 24 GB VRAM · GPU

▲ 123% speed▼ 100.5 GB$1,599rent $0.37/hr

3.1× faster if your models fit in 32 GBRTX 5090NVIDIA · 32 GB VRAM · GPU

▲ 215% speed▼ 92.5 GB$5,376rent $0.48/hr

MacBook Pro 16" M5 Max tokens per second by model size

Output speed depends on memory bandwidth (614 GB/s). Grey rows need more than the 124.5 GB available.

9BQwen3.5 9B · Q4_K_M · 6.6 GB
67.6tok/s
14BQwen3 14B · Q4_K_M · 11.9 GB
45.2tok/s
27–31BQwen3.8 27B · Q4_K_M · 17.9 GB
24.7tok/s
35B MoEQwen3.6 35B A3B · Q4_K_M · 22.0 GB
67.8tok/s
70BLlama 3.3 70B Instruct · Q4_K_M · 51.3 GB slow
9.2tok/s
120B MoEGPT OSS 120B · Q4_K_M · 70.8 GB
65.5tok/s

Estimated speeds: Q4_K_M, 4K context, one user. How we estimate

Max generations: writing vs compute

M1 Max → M5 Max

Writing speed (tok/s)Compute (TFLOPS FP16)

Writing speed follows memory bandwidth and barely moved: 54.5 to 67.8 tok/s since the M1 Max. Compute, which sets how fast prompts are read, grew 3.3×. Indexed to the M1 Max; speeds on Qwen3.6 35B A3B, same 64 GB.

All 1290 models on the MacBook Pro 16" M5 Max

Featured only

Best quant that fits in 124.5 GB, ordered by llmrun Score. Fit grades how well it runs here, S best. How ranking works

LLM models compatible with MacBook Pro 16" M5 Max (128 GB) — ranked by Score, recency and Fit
Model	Quant	VRAM	Speed	Context	Fit
Hermes 4.3 36B36.2BChatReasoningRoleplay Q4_K_M·19.3 t/s	Q4_K_M	24.1 GB19%	19.3 t/s	524K	B59, Decent
LFM2 24B A2B23.8BChatFunctions Q4_K_M·88.1 t/s	Q4_K_M	14.9 GB12%	88.1 t/s	128K	S89, Runs great
EuroLLM 1.7B Instruct1.7BChat Q4_K_M·286.5 t/s	Q4_K_M	1.7 GB1%	286.5 t/s	4K	S100, Runs great
Translategemma 4B IT4.3BVision Q4_K_M·151.3 t/s	Q4_K_M	5 GB4%	151.3 t/s	—	S97, Runs great
Olmo 3.1 32B Think32.2BChat BF16·6.6 t/s	BF16	66.6 GB54%	6.6 t/s	66K	C43, Usable
DeepSeek V4 Flash 162B92.2BChat Q4_K_M·7.7 t/s	Q4_K_M	55.8 GB45%	7.7 t/s	1049K	B45, Decent
Falcon Mamba Tiny Dev9MChat BF16·21490.0 t/s	BF16	0.4 GB0%	21490.0 t/s	—	S100, Runs great
ERNIE 4.5 0.3B Paddle361MChat BF16·413.3 t/s	BF16	1.2 GB1%	413.3 t/s	131K	S100, Runs great
Qwen2.5 3B Instruct3.1BChatFunctions Q4_K_M·192.7 t/s	Q4_K_M	2.8 GB2%	192.7 t/s	33K	S99, Runs great
GLM 4.5V107.7BVisionFunctions Q4_K_M·34.2 t/s	Q4_K_M	66.0 GB53%	34.2 t/s	66K	A73, Runs well
Llama 3.2 1B Instruct1.2BChatFunctions Q4_K_M·524.1 t/s	Q4_K_M	2.3 GB2%	524.1 t/s	131K	S100, Runs great
Qwen2.5 1.5B Quantized.w8a81.8BChatFunctions Q4_K_M·300.6 t/s	Q4_K_M	1.8 GB1%	300.6 t/s	33K	S100, Runs great
Dobby Mini Unhinged Llama 3.1 8B8.0BChatRoleplay Q4_K_M·79.7 t/s	Q4_K_M	7.3 GB6%	79.7 t/s	131K	S88, Runs great
Bielik 11B V3.0 Instruct11.2BChat BF16·17.5 t/s	BF16	27.4 GB22%	17.5 t/s	—	B57, Decent
DeepHat V1 7B7.6BChatCode Q4_K_M·86.1 t/s	Q4_K_M	5.8 GB5%	86.1 t/s	33K	S88, Runs great

MacBook Pro 16" M5 Max specs

Specs

Chip: M5 Max
CPU cores: 18
GPU cores: 40
Unified memory: 128 GB LPDDR5X
For models: 124.5 GB (macOS keeps 3.5 GB)
Memory bandwidth: 614 GB/s
FP16 (dense): 68 TFLOPS
Neural Engine: 38 TOPS
NPU: 16-core Neural Engine
Size: MacBook Pro 14/16-inch
Released: 2026-03-11
MSRP: $5,399

MacBook Pro 16" M5 Max FAQ

Is the MacBook Pro 16" M5 Max (128 GB) worth it for local LLMs in 2026?

At its $5,399 MSRP it gives 12.6 tok/s per $1,000 on Qwen3.6 35B A3B, 5th of the 6 machines compared here. It runs 27–31B and 120B MoE models well; dense 70B fits but is slow at 9 tok/s.

How much memory is available for AI on the MacBook Pro 16" M5 Max (128 GB)?

About 124.5 GB of the 128 GB. macOS keeps roughly 3.5 GB for itself and other apps.

What is the largest model the MacBook Pro 16" M5 Max (128 GB) can run?

Mistral Medium 3.5 128B (127.7B) is the largest at 4-bit or better: at Q4_K_M it uses 82.8 GB, 67% of the available memory, and runs at about 5.5 tok/s. At 3-bit, a bigger model fits too: Inkling Small (266.0B) at IQ3_S, 116.2 GB.

Can the MacBook Pro 16" M5 Max (128 GB) run Qwen3.8 27B?

Yes. Qwen3.8 27B fits at Q4_K_M, using 17.9 GB of the 124.5 GB available, and it is the best model that runs well on this machine.

Can the MacBook Pro 16" M5 Max (128 GB) run 70B models?

Yes, but slowly: Llama 3.3 70B Instruct at Q4_K_M uses 51.3 GB and writes about 9.2 tok/s.

How long does the MacBook Pro 16" M5 Max (128 GB) take to read a long prompt?

On Qwen3.8 27B, about 17 s for a 4K-token prompt and 2.2 min for a 32K-token document before the first word appears.

Is renting a GPU cheaper than buying the MacBook Pro 16" M5 Max?

An A100 (80 GB) rents from $1.12/hr. Renting costs as much as buying after ≈4,800 hours (≈3.3 years at 4 h a day).

48 GB GPUs All Macs Laptops Mac Pro M2 Ultra Mac Studio M1 Ultra Mac Studio M2 Ultra Best coding LLMs All hardware