llmrun

Apple · M6 · Laptop

Best AI Models for MacBook Pro 14" M6 (16 GB)

Runs 9B models well; 14B only just fits in 12.5 GB, and 27–31B doesn't fit.

16 GB unified12.5 GB for models153.6 GB/s19 TFLOPS FP162026
Buyabout $1,999

What LLMs can the MacBook Pro 14" M6 run?

#ModelSpeedllmrun ScoreQuant · Memory
1
Q4_K_M · 6.6 GB · 16.9 t/s
16.9 tok/sQ4_K_M · 6.6 GB
2
Qwen3.5 4BAlibaba
Q4_K_M · 3.4 GB · 33.0 t/s
33.0 tok/sQ4_K_M · 3.4 GB
3
Q4_K_M · 7.3 GB · 17.6 t/s
17.6 tok/sQ4_K_M · 7.3 GB
4
Q4_K_M · 5.0 GB · 37.9 t/s
37.9 tok/sQ4_K_M · 5.0 GB
5
Ling 3.0 TinyInclusion AI
Q4_K_M · 5.5 GB · 74.1 t/s
74.1 tok/sQ4_K_M · 5.5 GB
See all 283 models on the MacBook Pro 14" M6 →Bars = traction for models without a Score yet

About the MacBook Pro 14" M6 (16 GB)

The MacBook Pro 14" M6 is one of the fastest 16 GB machines: it runs 9B models well. Among 16 GB machines, only the M1 Pro and M2 Pro write faster. macOS keeps about 3.5 GB, leaving 12.5 GB for models. With 19 TFLOPS it reads long prompts faster than most 16 GB machines: a 4K-token prompt takes 21 s. At its $1,999 MSRP it gives 8.5 tok/s per $1,000, 7th of the 8 machines compared here.

Speed in 16 GB#3154 GB/s
Prompt reading#219 TFLOPS
For models12.5 GBmacOS keeps 3.5 GB
ChipM6released 2026

MacBook Pro 14" M6 strengths and weaknesses

Strengths

  • Runs 7–9B models: Qwen3.5 9B at 16.9 tok/s in 6.6 GB

Weaknesses

  • 27–31B models don't fit: Qwen3.8 27B needs 17.9 GB at Q4 vs 12.5 GB usable here
  • Little room for context: Qwen3 14B uses 11.9 of 12.5 GB usable, 0.6 GB left
  • Slow prompt reading: A 32K-token prompt on Qwen3.5 9B waits 2.8 min for the first token
  • No CUDA: vLLM, AWQ, GPTQ and FP8 builds don't run; use GGUF or MLX

Memory for models

12.5 GB of 16 GB
9B6.6 GB14B11.9 GB
9B6.6 GB14B11.9 GB
For models 12.5 GBmacOS keeps 3.5 GBModel size at Q4

27–31B models need 17.9 GB at Q4, more than the 12.5 GB available. The 24 GB config fits Qwen3.8 27B →Or rent an RTX 3090 (24 GB) from $0.18/hr →

Speed per dollar and per watt

On Qwen3.5 9B (9B params) 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 14" M6 has no current new price, so it is shown at its MSRP.

MachineNew pricetok/stok/s per $1,000tok/s per 100 W
about $5,502183
33.3
31.8
about $89916.9
18.8
–
about $1,59930.0
18.8
21.4
about $2,49945.1
18.0
31.1
about $1,49916.9
11.3
–
about $2,19918.7
8.5
–
about $1,99916.9
8.5
–
about $2,39918.7
7.8
–
MachineUsed pricetok/stok/s per $1,000tok/s per 100 W
RTX 409024 GBBest used value
about $3,000103
34.3
22.9
about $7,000183
26.2
31.8
about $2,00045.1
22.6
31.1

Cost per token: the MacBook Pro 14" M6 against 16–36 GB machines and GPUs

On Qwen3.5 9B (9B params, Q4_K_M, 4K context). Speed, cost per token and power per token depend on the model.

≤16 GB24–36 GBthis laptopat MSRP
Cost per 1M output tokenson Qwen3.5 9B · card over 3 years + power
$7.50
Machine, MSRP
$7.50
Power
not published
3-year cost of ownership$1,999
Or rent an RTX 3090 in the cloud$0.14/hr

Renting costs as much as buying after ≈14,000 hours (≈9.6 years at 4 h a day).

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 Qwen3.5 9B.

MacBook Pro 14" M6 tokens per second by model size

Output speed depends on memory bandwidth (154 GB/s). Grey rows need more than the 12.5 GB available.

  1. 9BQwen3.5 9B · Q4_K_M · 6.6 GB
    16.9tok/s
  2. 14BQwen3 14B · Q4_K_M · 11.9 GB tight · Q4_K_M
    11.3tok/s
  3. 27–31BQwen3.8 27B · not at 4-bit
    needs 17.9 GB
  4. 35B MoEQwen3.6 35B A3B · not at 4-bit
    needs 22.0 GB
  5. 70BLlama 3.3 70B Instruct · not at 4-bit
    needs 51.3 GB
  6. 120B MoEGPT OSS 120B · not at 4-bit
    needs 70.8 GB

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

Chip generations: writing vs compute

M1 → M5
Writing speed (tok/s)Compute (TFLOPS FP16)
1×2×3×4×M12021M22023M32023M42024M52025M1 · 5.2 TFLOPS FP16M1 · 7.5 tok/s · 68.3 GB/sM2 · 7.2 TFLOPS FP16M2 · 11.0 tok/s · 100 GB/sM3 · 7 TFLOPS FP16M3 · 11.3 tok/s · 102.4 GB/sM4 · 8.6 TFLOPS FP16M4 · 13.2 tok/s · 120 GB/sM5 · 16 TFLOPS FP16M5 · 16.9 tok/s · 153.6 GB/sCompute 3.1×Writing +125%
1×2×3×4×M12021M22023M32023M42024M52025M1 · 5.2 TFLOPS FP16M1 · 7.5 tok/s · 68.3 GB/sM2 · 7.2 TFLOPS FP16M2 · 11.0 tok/s · 100 GB/sM3 · 7 TFLOPS FP16M3 · 11.3 tok/s · 102.4 GB/sM4 · 8.6 TFLOPS FP16M4 · 13.2 tok/s · 120 GB/sM5 · 16 TFLOPS FP16M5 · 16.9 tok/s · 153.6 GB/sCompute 3.1×Writing +125%

Writing speed follows memory bandwidth and barely moved: 7.5 to 16.9 tok/s since the M1. Compute, which sets how fast prompts are read, grew 3.1×. Indexed to the M1; speeds on Qwen3.5 9B, same 16 GB.

All 988 models on the MacBook Pro 14" M6

Featured only

Best quant that fits in 12.5 GB, ordered by llmrun Score. Fit grades how well it runs here, S best. How ranking works

LLM models compatible with MacBook Pro 14" M6 (16 GB) — ranked by Score, recency and Fit
ModelVRAMScoreFit
Surya Ocr 2.5
Q4_K_M·141.5 t/s
0.8 GBS96, Runs great
Q4_K_M·20.4 t/s
5.5 GBB60, Decent
Qwen3 1.7B
Q4_K_M·61.4 t/s
3.4 GBA84, Runs well
Chandra Ocr 2
Q4_K_M·29.5 t/s
3.8 GBA70, Runs well
LFM2.5 8B A1B Opus Distil
Q4_K_M·66.9 t/s
5.6 GBS85, Runs great
Q4_K_M·38.5 t/s
3.7 GBA75, Runs well
GLM 4.6V Flash
Q4_K_M·16.4 t/s
7.2 GBB56, Decent
Muse Glimmer 30B
IQ2_M·10.2 t/s
11.8 GBD27, Barely runs
InternVL2 1B
Q4_K_M·173.4 t/s
2.0 GBS98, Runs great
Q4_K_M·158.1 t/s
0.9 GBS97, Runs great
MiniCPM V 4
Q4_K_M·38.7 t/s
3.1 GBA75, Runs well
JEV 27B VL
IQ2_XS·11.8 t/s
9.5 GBB51, Decent
GPT OSS BF16
Q4_K_M·358.4 t/s
0.3 GBS100, Runs great
BF16·44.1 t/s
2.7 GBA77, Runs well
Q4_K_M·66.9 t/s
5.6 GBS85, Runs great

MacBook Pro 14" M6 specs

Specs

Chip
M6
CPU cores
12
GPU cores
12
Unified memory
16 GB
For models
12.5 GB (macOS keeps 3.5 GB)
Memory bandwidth
153.6 GB/s
FP16 (dense)
19.2 TFLOPS
Neural Engine
76 TOPS
Released
2026-11-06
MSRP
$1,999

MacBook Pro 14" M6 FAQ

Is the MacBook Pro 14" M6 (16 GB) worth it for local LLMs in 2026?

At its $1,999 MSRP it gives 8.5 tok/s per $1,000 on Qwen3.5 9B, 7th of the 8 machines compared here. It runs 9B models well; 14B only just fits in 12.5 GB, and 27–31B doesn't fit.

How much memory is available for AI on the MacBook Pro 14" M6 (16 GB)?

About 12.5 GB of the 16 GB. macOS keeps roughly 3.5 GB for itself and other apps.

What is the largest model the MacBook Pro 14" M6 (16 GB) can run?

GPT OSS 20B (20.9B) is the largest at 4-bit or better: at Q4_K_S it uses 12.4 GB, 99% of the available memory, and runs at about 36.4 tok/s.

Can the MacBook Pro 14" M6 (16 GB) run Qwen3.5 9B?

Yes. Qwen3.5 9B fits at Q4_K_M, using 6.6 GB of the 12.5 GB available, and it is the best model that runs well on this machine.

Can the MacBook Pro 14" M6 (16 GB) run 27–31B models?

No. Qwen3.8 27B needs 17.9 GB at Q4, more than the 12.5 GB available.

How long does the MacBook Pro 14" M6 (16 GB) take to read a long prompt?

On Qwen3.5 9B, about 21 s for a 4K-token prompt and 2.8 min for a 32K-token document before the first word appears.

Is renting a GPU cheaper than buying the MacBook Pro 14" M6?

An RTX 3090 (24 GB) rents from $0.14/hr. Renting costs as much as buying after ≈14,000 hours (≈9.6 years at 4 h a day).