Apple · M4 · Laptop
Best AI Models for MacBook Pro 14" M4 (16 GB)
Runs 9B models at 13 tok/s; 14B only just fits in 12.5 GB, and 27–31B doesn't fit.
| # | Model | Speed | llmrun Score | Quant · Memory |
|---|---|---|---|---|
| 1 | Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 13.2 t/s | 13.2 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 25.8 t/s | 25.8 tok/s | Q4_K_M · 3.4 GB | |
| 3 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 29.6 t/s | 29.6 tok/s | Q4_K_M · 5.0 GB | |
| 4 | Q4_K_M · 7.9 GB · 15.8 t/s | 15.8 tok/s | Q4_K_M · 7.9 GB | |
| 5 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 62.8 t/s | 62.8 tok/s | Q4_K_M · 5.5 GB |
| # | Model | Speed | Coding Score | Quant · Memory |
|---|---|---|---|---|
| 1 | Q4_K_M · 7.9 GB · 15.8 t/s | 15.8 tok/s | Q4_K_M · 7.9 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 25.8 t/s | 25.8 tok/s | overall | Q4_K_M · 3.4 GB |
| 3 | Qwen3 8BAlibaba Q4_K_M · 7.6 GB · 15.2 t/s | 15.2 tok/s | overall | Q4_K_M · 7.6 GB |
| 4 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 62.8 t/s | 62.8 tok/s | Q4_K_M · 5.5 GB | |
| 5 | Gemma 4 E4B ITGoogle Q4_K_M · 5.6 GB · 15.8 t/s | 15.8 tok/s | Q4_K_M · 5.6 GB |
| # | Model | Speed | Reasoning Score | Quant · Memory |
|---|---|---|---|---|
| 1 | Qwen3 8BAlibabaHow to run → Q4_K_M · 7.6 GB · 15.2 t/s | 15.2 tok/s | Q4_K_M · 7.6 GB | |
| 2 | Q4_K_M · 7.9 GB · 15.8 t/s | 15.8 tok/s | Q4_K_M · 7.9 GB | |
| 3 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 29.6 t/s | 29.6 tok/s | Q4_K_M · 5.0 GB | |
| 4 | Qwen2.5 7B InstructAlibaba Q4_K_M · 5.8 GB · 16.8 t/s | 16.8 tok/s | Q4_K_M · 5.8 GB | |
| 5 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 62.8 t/s | 62.8 tok/s | Q4_K_M · 5.5 GB |
| # | Model | Speed | Long context Score | Quant · Memory |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 25.8 t/s | 25.8 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Q4_K_M · 7.9 GB · 15.8 t/s | 15.8 tok/s | Q4_K_M · 7.9 GB | |
| 3 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 62.8 t/s | 62.8 tok/s | Q4_K_M · 5.5 GB | |
| 4 | Gemma 4 E4B ITGoogle Q4_K_M · 5.6 GB · 15.8 t/s | 15.8 tok/s | Q4_K_M · 5.6 GB | |
| 5 | Gemma 4 E2B ITGoogle Q4_K_M · 3.5 GB · 24.5 t/s | 24.5 tok/s | Q4_K_M · 3.5 GB |
| # | Model | Speed ↓ | llmrun Score | Quant · Memory |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 25.8 t/s | 25.8 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 62.8 t/s | 62.8 tok/s | Q4_K_M · 5.5 GB | |
| 3 | Gemma 4 E2B ITGoogle Q4_K_M · 3.5 GB · 24.5 t/s | 24.5 tok/s | Q4_K_M · 3.5 GB | |
| 4 | Gemma 4 E4B ITGoogle Q4_K_M · 5.6 GB · 15.8 t/s | 15.8 tok/s | Q4_K_M · 5.6 GB | |
| 5 | Qwen3 8BAlibaba Q4_K_M · 7.6 GB · 15.2 t/s | 15.2 tok/s | Q4_K_M · 7.6 GB |
| # | Model | Speed | Vision Score | Quant · Memory |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 25.8 t/s | 25.8 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 29.6 t/s | 29.6 tok/s | Q4_K_M · 5.0 GB | |
| 3 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 13.2 t/s | 13.2 tok/s | Q4_K_M · 6.6 GB | |
| 4 | MiniCPM V 4.7 1BOpenBMB Q4_K_M · 1.6 GB · 65.6 t/s | 65.6 tok/s | Q4_K_M · 1.6 GB | |
| 5 | LFM3 Omni 2BLiquid AI Q4_K_M · 2.4 GB · 49.4 t/s | 49.4 tok/s | Q4_K_M · 2.4 GB |
The MacBook Pro 14" M4 is a mid-range 16 GB laptop: it runs 9B models at 13 tok/s. Among 16 GB machines, only the M1 Pro, M2 Pro and M5 write faster. macOS keeps about 3.5 GB, leaving 12.5 GB for models. Prompt reading is its weak spot: a 4K-token prompt waits 46 s before the first word on Qwen3.5 9B. At its $1,599 MSRP it gives 8.3 tok/s per $1,000, 6th of the 6 machines compared here. M4 generation, released 2024; the newer M5 writes 28% faster with 1.9× the compute.
MacBook Pro 14" M4 strengths and weaknesses
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 6.1 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 GB27–31B 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 $0.17/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" M4 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 |
|---|---|---|---|---|
Mac Mini M4 Pro24 GB | about $1,599 | 30.0 | 18.8 | 21.4 |
Mac Studio M4 Max36 GB | about $2,499 | 45.1 | 18.0 | 31.1 |
Mac Mini M416 GB | about $799 | 13.2 | 16.5 | 20.3 |
| about $2,299 | 33.8 | 14.7 | – | |
MacBook Pro 14 M532 GB | about $1,839 | 16.9 | 9.2 | – |
MacBook Pro 14" M416 GB | about $1,599 | 13.2 | 8.3 | – |
| Machine | Used price | tok/s | tok/s per $1,000 | tok/s per 100 W |
|---|---|---|---|---|
Mac Studio M4 Max36 GB | about $2,000 | 45.1 | 22.6 | 31.1 |
| about $2,109 | 33.8 | 16.0 | – |
Cost per token: the MacBook Pro 14" M4 against 16–64 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.
- Machine, MSRP
- $7.68
- Power
- not published
Renting costs as much as buying after ≈9,500 hours (≈6.5 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
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.
Output speed depends on memory bandwidth (120 GB/s). Grey rows need more than the 12.5 GB available.
- 9BQwen3.5 9B · Q4_K_M · 6.6 GB13.2tok/s
- 8.8tok/s
- 27–31BQwen3.8 27B · not at 4-bitneeds 17.9 GB
- 35B MoEQwen3.6 35B A3B · not at 4-bitneeds 22.0 GB
- 70BLlama 3.3 70B Instruct · not at 4-bitneeds 51.3 GB
- 120B MoEGPT OSS 120B · not at 4-bitneeds 70.8 GB
Estimated speeds: Q4_K_M, 4K context, one user. How we estimate
Chip generations: writing vs compute
M1 → M5Writing 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 281 models on the MacBook Pro 14" M4
Featured onlyBest quant that fits in 12.5 GB, ordered by llmrun Score. Fit grades how well it runs here, S best. How ranking works
| Model | Quant | VRAM | Speed | Context | Score | Fit |
|---|---|---|---|---|---|---|
LFM2.5 8B A1BChatFunctions | Q4_K_M | 5.6 GB | 56.2 t/s | 128K | A82, Runs well | |
Ornith 1.5 9BChatFunctions | Q4_K_M | 6.6 GB | 13.2 t/s | 262K | B52, Decent | |
D1 Omni 600MVision | Q4_K_M | 1.2 GB | 116.7 t/s | 128K | S94, Runs great | |
Unlimited OCRVision | Q4_K_M | 3.3 GB | 81.3 t/s | 33K | S88, Runs great | |
LFM3 Omni 2BVisionChatFunctions | Q4_K_M | 2.4 GB | 49.4 t/s | 128K | A79, Runs well | |
Mellum2.1 12B A2.5B ThinkingChatFunctions | Q4_K_M | 7.8 GB | 41.8 t/s | 131K | A76, Runs well | |
LFM3 VL 2BVisionChatFunctions | Q4_K_M | 2.3 GB | 54.2 t/s | 128K | A81, Runs well | |
MinerU2.5 Pro 2605 1.2BVision | Q4_K_M | 1.1 GB | 82.4 t/s | 8K | S88, Runs great | |
MiniCPM V 4.6VisionFunctions | Q4_K_M | 1.5 GB | 74.3 t/s | 262K | S86, Runs great | |
GPT OSS 20BChatFunctions | Q4_K_S | 12.3 GB | 29.6 t/s | 131K | C40, Usable | |
NVIDIA Nemotron 3.5 Bolt E4B BF16ChatFunctions | Q4_K_M | 5.6 GB | 15.8 t/s | 66K | B55, Decent | |
D1 2BVisionFunctions | Q4_K_M | 2.3 GB | 54.2 t/s | 128K | A81, Runs well | |
MiniCPM V 4.6 ThinkingVisionFunctions | Q4_K_M | 1.5 GB | 74.3 t/s | 262K | S86, Runs great | |
Intern Decision 0.8BVisionFunctions | Q4_K_M | 0.9 GB | 97.7 t/s | 262K | S91, Runs great | |
MinerU2.5 Pro 2604 1.2BVision | Q4_K_M | 1.1 GB | 82.4 t/s | 8K | S88, Runs great |
Specs
- Chip
- M4
- CPU cores
- 10
- GPU cores
- 10
- Unified memory
- 16 GB
- For models
- 12.5 GB (macOS keeps 3.5 GB)
- Memory bandwidth
- 120 GB/s
- FP16 (dense)
- 8.6 TFLOPS
- Neural Engine
- 38 TOPS
- Released
- 2024-11-08
- MSRP
- $1,599
MacBook Pro 14" M4 FAQ
Is the MacBook Pro 14" M4 (16 GB) worth it for local LLMs in 2026?
At its $1,599 MSRP it gives 8.3 tok/s per $1,000 on Qwen3.5 9B, 6th of the 6 machines compared here. It runs 9B models at 13 tok/s; 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" M4 (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" M4 (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 29.6 tok/s.
Can the MacBook Pro 14" M4 (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" M4 (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" M4 (16 GB) take to read a long prompt?
On Qwen3.5 9B, about 46 s for a 4K-token prompt and 6.1 min for a 32K-token document before the first word appears.
Is renting a GPU cheaper than buying the MacBook Pro 14" M4?
An RTX 3090 (24 GB) rents from $0.17/hr. Renting costs as much as buying after ≈9,500 hours (≈6.5 years at 4 h a day).