Skip to content

text model · North · macOS

Can I run North Mini Code 1.0 on Apple M5 (32GB)?

Compatibility verdict VRAM threshold engine
No, not enough memory would not load

No. North Mini Code 1.0 needs ~21.1 GB even at Q4_K_M, but Apple M5 (32GB) only has ~21 GB usable.

Needs ~21.1 GB Device usable ~21 GB

Needs ~21.1 GB even at Q4_K_M, but only ~21 GB is usable.

That figure is at a 4k context and moves about ±15% as context length changes.

The gap is about 0.1 GB: North Mini Code 1.0 needs roughly 21.1 GB at Q4_K_M and Apple M5 (32GB) leaves only about 21 GB usable for a model. The lightest tracked hardware that runs North Mini Code 1.0 is the Nvidia GeForce RTX 4090 (24GB) at 24 GB. See North Mini Code 1.0 on Nvidia GeForce RTX 4090 (24GB).

Q4_K_M needed
~21.1 GB
Usable on device
~21 GB
Device memory
32 GB
Share on X Share on Reddit

Which quant fits

Quant ladder vs ~21 GB usable
Q2_K
~14.9 GB
Q3_K_M
~17 GB
Q4_K_M
~21.1 GB
Q5_K_M
~23.8 GB
Q6_K
~27.1 GB
Q8_0
~34.1 GB
FP16
~63.1 GB
The line marks Apple M5 (32GB)'s ~21 GB budget; rungs past it are too large.
Model North
Parameters
30.5B (MoE, 3B active)
Q4_K_M size
19 GB
Q8_0 size
32 GB
Context
500k
Ollama tag
north-mini-code-1.0
Full North Mini Code 1.0 requirements →
Device macOS
Memory
32 GB unified
Usable for weights
~21 GB
Best runtime
MLX direct / Ollama (MLX backend)
Best models for Apple M5 (32GB) →

What you can run instead

Run North Mini Code 1.0 on other hardware

FAQ

Can Apple M5 (32GB) run North Mini Code 1.0?

No. North Mini Code 1.0 needs ~21.1 GB even at Q4_K_M, but Apple M5 (32GB) only has ~21 GB usable.

How much memory does North Mini Code 1.0 need?

Apple M5 (32GB) does not have enough memory. At Q4_K_M the weights are ~19 GB; with KV cache and runtime overhead, budget ~21.1 GB at a 4k context. It is a Mixture-of-Experts model (30.5B total / 3B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run North Mini Code 1.0 on macOS?

LM Studio for a simple setup; mlx-lm for the most speed. vLLM is NOT a Mac tool, it is a CUDA/Linux serving engine. Unified memory is not a fixed VRAM slice; ~70% is usable for weights.

Embed this

North Mini Code 1.0 on Apple M5 (32GB) compatibility badge A live badge for your model card or README, updated as the data is.
Markdown
$ [![North Mini Code 1.0 on Apple M5 (32GB)](https://localmodel.run/badge/north-mini-code-1.0/apple-m5-32gb.svg)](https://localmodel.run/can-i-run/north-mini-code-1.0/apple-m5-32gb)

Sources

Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.