# MacBook Pro 14" (M6) for local AI: current facts

URL: https://insidethemachine.ai/machines/macbook-pro-14-m6 · machines.json 2026-10-27 · prices and speeds checked 2026-10-15 · models.json 2026-10-27

With 16 GB it counts as a 16 GB machine for AI. The smartest model it runs is K2 Horizon 7B (Mac only), 36% as smart as the best paid AI. 40 of 122 chat models fit its 12 GB for AI. About $1,999 (Apple Store, 2026-10-27). Up to 32 GB: Qwen3.8 27B, 59% (price unknown).

## Specs

- Kind: Mac laptop (Mac). Shape: Laptop. Status: Not on sale yet.
- Chip: M6 (12-core CPU, 12-core GPU). Memory: 16 / 24 / 32 GB, Shared (unified): the chip and the graphics use one pool.
- Memory for AI: 12 / 18 / 24 GB. 75% of the memory: the macOS default for the graphics.
- Memory speed: 153 GB/s (Spec page lists 153 GB/s for 16GB and 170 GB/s for the 24GB/32GB configurations.). Spec source: Apple – MacBook Pro tech specs, 2026-10-27, https://www.apple.com/macbook-pro/specs/.
- Power: unknown. Launch price: $1,999.
- From our data notes: Pre-orders open 2026-10-28; not on sale until 2026-11-06 (Apple Store page, checked 2026-10-27). Replaces the M5 14-inch MacBook Pro. Apple says up to 25% faster LLM prompt processing than M5; no measured tokens per second yet.

## Memory sizes (Fig. 1)

Rules: We round each machine down to the biggest standard size (8 to 512 GB) whose memory for AI it has. The GeForce RTX 5090 has 31 GB for AI. A standard 32 GB computer has 24 GB and a 48 GB one has 36 GB, so it counts as 32 GB. It counts as that size for the model picks per size and for the recipes. A machine's fit count ("N of 122 chat models fit") uses its own memory for AI, so its machine page, its /machines row, /my and the /best guides give the same number. So 79 of 122 chat models fit the GeForce RTX 5090, and 64 fit a standard 32 GB computer. "The smartest model it runs" uses the machine's own memory for AI, so a 24 GB graphics card (23 GB for AI) can run a bigger model than a 24 GB Mac (18 GB for AI).

| memory GB | for AI GB | counts as GB | chat models that fit its memory for AI (of 122) | for comparison: fit a standard computer of that size (of 122) | smartest model it runs | % of best paid AI | price |
|---|---|---|---|---|---|---|---|
| 16 | 12 | 16 | 40 | 40 | K2 Horizon 7B (Mac only) | 36% | $1,999 (Apple Store, 2026-10-27) |
| 24 | 18 | 24 | 47 | 47 | K2 Horizon 7B (Mac only) | 36% | no dated price in our data |
| 32 | 24 | 32 | 64 | 64 | Qwen3.8 27B | 59% | no dated price in our data |

- 16 GB: Mac only. K2 Horizon 7B scores higher, but it has no Ollama download yet, only an MLX one, which needs a Mac. The recipes install Gemma 4 12B, the smartest model here that runs with Ollama on Mac, Windows and Linux.
- 24 GB: Mac only. K2 Horizon 7B scores higher, but it has no Ollama download yet, only an MLX one, which needs a Mac. The recipes install Gemma 4 12B, the smartest model here that runs with Ollama on Mac, Windows and Linux.

## The 24/7 helper (Fig. 1a)

Rule: The helper's brain, ears (speech to text) and voice (text to speech) stay loaded together. Ears and voice get up to 15% of the memory for AI each. The brain is the best model that can use tools and fits in the rest. To make an image, the helper pauses the brain and the image model uses its space. Same rule as Fig. 2 on /explore and /my.

| memory GB | brain | ears (speech to text) | voice (text to speech) | free GB | kept for the system GB | image model (the brain pauses) | brain run command |
|---|---|---|---|---|---|---|---|
| 16 | Qwen3.5 9B (9.6 GB, 23%) | Qwen3-ASR 0.6B (1 GB) | Kokoro 82M v1.0 (0.5 GB) | 0.9 | 4 | Z-Image Turbo (4 GB) | `ollama run qwen3.5:9b` (Ollama) |
| 24 | Gemma 4 12B (11.2 GB, 25%) | MOSS-Transcribe-Diarize 0.9B (2.5 GB) | Magpie TTS Multilingual 357M (2 GB) | 2.3 | 6 | Z-Image Turbo (4 GB) | `ollama run gemma4:12b` (Ollama) |
| 32 | Gemma 4 12B (11.2 GB, 25%) | Qwen3-ASR 1.7B (3 GB) | Magpie TTS Multilingual 357M (2 GB) | 7.8 | 8 | Z-Image Turbo (4 GB) | `ollama run gemma4:12b` (Ollama) |

- 16 GB: why not K2 Horizon 7B as the brain? Our data doesn't list tool use for K2 Horizon 7B, so the helper skips it. A helper needs tools to act for you.
- 24 GB: why not K2 Horizon 7B as the brain? Our data doesn't list tool use for K2 Horizon 7B, so the helper skips it. A helper needs tools to act for you.
- 32 GB: why not Qwen3.8 27B as the brain? Qwen3.8 27B needs 22.7 GB. Next to the ears and voice, the brain has 19 GB left.

## Top picks per size (Fig. 1b, judged on this machine's own memory for AI)

Fit rule: We count 75% of your memory as usable for AI. The rest is for the system and your apps. Runs well: the model fits in usable memory with at least 10% to spare. Runs, but tight: it fits, but less than 10% of usable memory is left. Close other apps first. Needs N GB+: it does not fit. N is the smallest memory size it fits in. Size unknown: we do not know how much memory it needs. On this page "usable" is the machine's own memory for AI.

- 16 GB (12 GB for AI): smartest it runs K2 Horizon 7B (Mac only), 36%, Runs well, run: `mlx_lm.generate --model mlx-community/K2-Horizon-7B-4bit --prompt 'hello'` (MLX (Mac only)).
  Top picks: K2 Horizon 7B 36%, needs 8.6 GB, Runs well; Gemma 4 12B 25%, needs 11.2 GB, Runs, but tight; Qwen3.5 9B 23%, needs 9.6 GB, Runs well; Qwen3.5 4B 23%, needs 5.8 GB, Runs well; MiniCPM5 2B 22%, needs 3.9 GB, Runs well.
  Best by job, at the standard 16 GB size: code Ornith 1.5 9B; agents Mellum2.1 12B-A2.5B Thinking; reads images Gemma 4 12B.
  Set this as your computer: https://insidethemachine.ai/my?os=mac&chip=apple-m6&hw=macbook-pro-14&ram=16
- 24 GB (18 GB for AI): smartest it runs K2 Horizon 7B (Mac only), 36%, Runs well, run: `mlx_lm.generate --model mlx-community/K2-Horizon-7B-4bit --prompt 'hello'` (MLX (Mac only)).
  Top picks: K2 Horizon 7B 36%, needs 8.6 GB, Runs well; Gemma 4 12B 25%, needs 11.2 GB, Runs well; Qwen3.5 9B 23%, needs 9.6 GB, Runs well; Qwen3.5 4B 23%, needs 5.8 GB, Runs well; MiniCPM5 2B 22%, needs 3.9 GB, Runs well.
  Best by job, at the standard 24 GB size: code NousCoder 14B; agents Mellum2.1 12B-A2.5B Thinking; reads images Gemma 4 12B.
  Set this as your computer: https://insidethemachine.ai/my?os=mac&chip=apple-m6&hw=macbook-pro-14&ram=24
- 32 GB (24 GB for AI): smartest it runs Qwen3.8 27B, 59%, Runs, but tight, run: `ollama run qwen3.8:27b` (Ollama).
  Top picks: Qwen3.8 27B 59%, needs 22.7 GB, Runs, but tight; Qwen3.5 27B 40%, needs 21.5 GB, Runs well; Qwen3.6 27B 37%, needs 21.5 GB, Runs well; K2 Horizon 7B 36%, needs 8.6 GB, Runs well; Muse Glimmer 30B 30%, needs 22.7 GB, Runs, but tight.
  Best by job, at the standard 32 GB size: code Qwen3.8 27B; agents Qwen3.8 27B; reads images Qwen3.8 27B.
  Set this as your computer: https://insidethemachine.ai/my?os=mac&chip=apple-m6&hw=macbook-pro-14&ram=32

## Prices (Fig. 3, approximate, USD, cheapest first)

Prices are approximate, in US dollars, with the shop and the date we checked. A memory-chip shortage pushed 2026 prices up. Check before you buy.

Per memory size: 16 GB $1,999 (Apple Store, 2026-10-27); 24 GB no dated price in our data; 32 GB no dated price in our data.

| price USD | condition | what you get | kind of price | shop or tracker | date | link |
|---|---|---|---|---|---|---|
| $1,999 | new | 14", M6, 16GB | Starting price | Apple Store – Buy MacBook Pro | 2026-10-27 | https://www.apple.com/shop/buy-mac/macbook-pro |

## Published speeds (Fig. 4, not our tests)

Speeds are copied from published tests by makers and the community, with sources. We did not run them. Different apps and settings give different speeds, so compare with care. On the page each bar is a share of the fastest published result for that model on any machine in our data.

None found yet. Memory speed (153 GB/s) is the best guide: higher means faster answers.

Check your own computer (read-only, sends nothing): `curl -fsSL https://insidethemachine.ai/scan.sh | sh` (Mac or Linux) or `irm https://insidethemachine.ai/scan.ps1 | iex` (Windows PowerShell).

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Reference file (https://insidethemachine.ai/machines/macbook-pro-14-m6.md). Its "chat models that fit" counts this machine's own memory for AI.

# MacBook Pro 14" (M6) for local AI

URL: https://insidethemachine.ai/machines/macbook-pro-14-m6
Type: Mac laptop. Chip: M6 (12-core CPU, 12-core GPU). Memory: unified, options 16, 24, 32 GB. Bandwidth: 153 GB/s (Spec page lists 153 GB/s for 16GB and 170 GB/s for the 24GB/32GB configurations.). Spec source: https://www.apple.com/macbook-pro/specs/ (2026-10-27).
Price: from about $1,999 for the 16 GB model (2026-10-27, approximate). Status: announced.

## Which models fit

| memory GB | usable GB | chat models that fit its own usable GB (of 122) | best 3 that fit | best it runs |
|---|---|---|---|---|
| 16 | 12 | 40 | K2 Horizon 7B (8.6 GB, Mac only), Gemma 4 12B (11.2 GB), Qwen3.5 9B (9.6 GB) | K2 Horizon 7B (Mac only) |
| 24 | 18 | 47 | K2 Horizon 7B (8.6 GB, Mac only), Gemma 4 12B (11.2 GB), Qwen3.5 9B (9.6 GB) | K2 Horizon 7B (Mac only) |
| 32 | 24 | 64 | Qwen3.8 27B (22.7 GB), Qwen3.5 27B (21.5 GB), Qwen3.6 27B (21.5 GB) | Qwen3.8 27B |

## Published speeds

None found yet.

Notes: Pre-orders open 2026-10-28; not on sale until 2026-11-06 (Apple Store page, checked 2026-10-27). Replaces the M5 14-inch MacBook Pro. Apple says up to 25% faster LLM prompt processing than M5; no measured tokens per second yet.

## Questions

**What is the best local LLM for the MacBook Pro 14" (M6)?**
With 32 GB, Qwen3.8 27B (needs 22.7 GB). Its Artificial Analysis score is 33.7: 59% of the best paid AI, Claude Opus 5.5. 64 of the 122 open chat models fit in its own 24 GB for AI. With 16 GB: K2 Horizon 7B.

**How much does the MacBook Pro 14" (M6) cost?**
From about $1,999 for the 16 GB model (as of 2026-10-27). 2026 prices are inflated by the memory-chip shortage; check before buying.