llmrun

Apple · M5 · Laptop

Best AI Models for MacBook Pro 14-inch (M5) (32 GB)

Runs 9B and 35B MoE models well; 14B and 27–31B fit but are slow (11 and 6 tok/s), and 70B doesn't fit in 28.5 GB.

32 GB unified28.5 GB for models153.6 GB/s16 TFLOPS FP162025
Buyabout $1,839

What LLMs can the MacBook Pro 14-inch (M5) run?

#ModelSpeedllmrun ScoreQuant · Memory
1
Q4_K_M · 22.0 GB · 28.6 t/s
28.6 tok/sQ4_K_M · 22.0 GB
2
Q4_K_M · 16.5 GB · 31.7 t/s
31.7 tok/sQ4_K_M · 16.5 GB
3
Q4_K_M · 19.4 GB · 34.8 t/s
34.8 tok/sQ4_K_M · 19.4 GB
4
Q4_K_M · 13.1 GB · 34.6 t/s
34.6 tok/sQ4_K_M · 13.1 GB
5
Q4_K_M · 19.3 GB · 41.9 t/s
41.9 tok/sQ4_K_M · 19.3 GB
See all 341 models on the MacBook Pro 14-inch (M5) →Bars = traction for models without a Score yet

About the MacBook Pro 14-inch (M5)

The MacBook Pro 14-inch (M5) is a 32 GB laptop with more memory than speed: it runs 9B and 35B MoE models well. macOS keeps about 3.5 GB, leaving 28.5 GB for models. Prompt reading is its weak spot: a 4K-token prompt waits 12 s before the first word on Qwen3.6 35B A3B. At ≈$1,839 it gives 15.6 tok/s per $1,000, 6th of the 6 machines compared here. M5 generation, released 2025.

Speed in 32 GB#6154 GB/s
Prompt reading#516 TFLOPS
For models28.5 GBmacOS keeps 3.5 GB
ChipM5released 2025

MacBook Pro 14-inch (M5) strengths and weaknesses

Strengths

  • Runs 35B MoE models: Qwen3.6 35B A3B at 28.6 tok/s in 22 GB

Weaknesses

  • 70B models don't fit: Llama 3.3 70B Instruct needs 51.3 GB at Q4 vs 28.5 GB usable here
  • Slow on large dense models: Qwen3.8 27B at 6.2 tok/s
  • Slow prompt reading: A 32K-token prompt on Qwen3.6 35B A3B waits 1.6 min for the first token
  • No CUDA: vLLM, AWQ, GPTQ and FP8 builds don't run; use GGUF or MLX

Memory for models

28.5 GB of 32 GB
9B6.6 GB14B11.9 GB27–31B17.9 GB35B MoE22 GB
9B6.6 GB14B11.9 GB35B MoE22 GB
For models 28.5 GBmacOS keeps 3.5 GBModel size at Q4

70B models need 51.3 GB at Q4, more than the 28.5 GB available.Or rent an A100 (80 GB) from $1.12/hr →

Speed per dollar and per watt

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.

MachineNew pricetok/stok/s per $1,000tok/s per 100 W
RTX 509032 GBBest new value
about $5,376213
39.7
37.1
about $1,59946.3
29.0
33.1
about $99923.5
23.5
36.2
about $2,49955.2
22.1
38.1
about $2,29946.5
20.2
–
about $1,83928.6
15.6
–
MachineUsed pricetok/stok/s per $1,000tok/s per 100 W
RTX 409024 GBBest used value
about $3,000151
50.3
33.6
about $6,400213
33.3
37.1
about $2,00055.2
27.6
38.1
about $2,10946.5
22.0
–

Cost per token: the MacBook Pro 14-inch (M5) against 24–64 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.

24–36 GB48–64 GBthis laptopat MSRP
Cost per 1M output tokenson Qwen3.6 35B A3B · card over 3 years + power
$4.08
Machine, new price
$4.08
Power
not published
3-year cost of ownership$1,839
Or rent an A100 in the cloud$1.03/hr

Renting costs as much as buying after ≈1,800 hours (≈1.2 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 Qwen3.6 35B A3B.

MacBook Pro 14-inch (M5) tokens per second by model size

Output speed depends on memory bandwidth (154 GB/s). Grey rows need more than the 28.5 GB available.

  1. 9BQwen3.5 9B · Q4_K_M · 6.6 GB
    16.9tok/s
  2. 14BQwen3 14B · Q4_K_M · 11.9 GB
    11.3tok/s
  3. 27–31BQwen3.8 27B · Q4_K_M · 17.9 GB slow
    6.2tok/s
  4. 35B MoEQwen3.6 35B A3B · Q4_K_M · 22.0 GB
    28.6tok/s
  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×M12021M22023M32024M42024M52025M1 · 5.2 TFLOPS FP16M1 · 24.9 tok/s · 68.3 GB/sM2 · 7.2 TFLOPS FP16M2 · 22.1 tok/s · 100 GB/sM3 · 7 TFLOPS FP16M3 · 22.6 tok/s · 102.4 GB/sM4 · 8.6 TFLOPS FP16M4 · 23.5 tok/s · 120 GB/sM5 · 16 TFLOPS FP16M5 · 28.6 tok/s · 153.6 GB/sCompute 3.1×Writing +15%
1×2×3×4×M12021M22023M32024M42024M52025M1 · 5.2 TFLOPS FP16M1 · 24.9 tok/s · 68.3 GB/sM2 · 7.2 TFLOPS FP16M2 · 22.1 tok/s · 100 GB/sM3 · 7 TFLOPS FP16M3 · 22.6 tok/s · 102.4 GB/sM4 · 8.6 TFLOPS FP16M4 · 23.5 tok/s · 120 GB/sM5 · 16 TFLOPS FP16M5 · 28.6 tok/s · 153.6 GB/sCompute 3.1×Writing +15%

Writing speed follows memory bandwidth and barely moved: 24.9 to 28.6 tok/s since the M1. Compute, which sets how fast prompts are read, grew 3.1×. Indexed to the M1; speeds on Qwen3.6 35B A3B, same 16 GB.

All 1165 models on the MacBook Pro 14-inch (M5)

Featured only

Best quant that fits in 28.5 GB, ordered by llmrun Score. Fit grades how well it runs here, S best. How ranking works

LLM models compatible with MacBook Pro 14-inch (M5) — ranked by Score, recency and Fit
ModelVRAMScoreFit
Q4_K_M·137.8 t/s
1.6 GBS96, Runs great
Orca Mini 3B
Q4_K_M·47.6 t/s
2.3 GBA79, Runs well
Llama 3.1 8B
Q4_K_M·20.3 t/s
7.9 GBB60, Decent
Q4_K_M·21.9 t/s
6.8 GBB62, Decent
NextCoder 7B
Q4_K_M·21.5 t/s
5.8 GBB62, Decent
Q4_K_M·15.1 t/s
7.5 GBB55, Decent
Q4_K_M·20.3 t/s
7.9 GBB60, Decent
Llama 3.2 3B
Q4_K_M·50.7 t/s
4.1 GBA80, Runs well
Q4_K_M·11.0 t/s
9.8 GBB49, Decent
Q4_K_M·18.7 t/s
8.4 GBB58, Decent
Q4_K_M·40.4 t/s
2.7 GBA75, Runs well
DeepSeek R1 Distill Llama 8B
Q4_K_M·19.9 t/s
7.3 GBB60, Decent
Q4_K_M·33.2 t/s
3.6 GBA72, Runs well
Qwen2.5 Coder 1.5B Instruct
Q4_K_M·84.0 t/s
1.7 GBS88, Runs great
Q4_K_M·19.5 t/s
7.6 GBB60, Decent

MacBook Pro 14-inch (M5) specs

Specs

Chip
M5
CPU cores
10
GPU cores
10
Unified memory
32 GB LPDDR5X
For models
28.5 GB (macOS keeps 3.5 GB)
Memory bandwidth
153.6 GB/s
FP16 (dense)
16 TFLOPS
Neural Engine
38 TOPS
NPU
16-core Neural Engine
Size
MacBook Pro 14-inch
Released
2025-10-22
MSRP
$1,599

MacBook Pro 14-inch (M5) FAQ

Is the MacBook Pro 14-inch (M5) worth it for local LLMs in 2026?

At ≈$1,839 it gives 15.6 tok/s per $1,000 on Qwen3.6 35B A3B, 6th of the 6 machines compared here. It runs 9B and 35B MoE models well; 14B and 27–31B fit but are slow (11 and 6 tok/s), and 70B doesn't fit in 28.5 GB.

How much memory is available for AI on the MacBook Pro 14-inch (M5)?

About 28.5 GB of the 32 GB. macOS keeps roughly 3.5 GB for itself and other apps.

What is the largest model the MacBook Pro 14-inch (M5) can run?

Qwen3.6 35B A3B (36.0B) is the largest at 4-bit or better: at Q4_K_M it uses 22.0 GB, 77% of the available memory, and runs at about 28.6 tok/s.

Can the MacBook Pro 14-inch (M5) run 70B models?

No. Llama 3.3 70B Instruct needs 51.3 GB at Q4, more than the 28.5 GB available.

How long does the MacBook Pro 14-inch (M5) take to read a long prompt?

On Qwen3.6 35B A3B, about 12 s for a 4K-token prompt and 1.6 min for a 32K-token document before the first word appears.

Is renting a GPU cheaper than buying the MacBook Pro 14-inch (M5)?

An A100 (80 GB) rents from $1.03/hr. Renting costs as much as buying after ≈1,800 hours (≈1.2 years at 4 h a day).