mlx-serve/Community · Tier list

The local LLM tier list.

Community-voted rankings of the LLMs that run locally on Apple Silicon — auto-updated from Hugging Face, filtered to your Mac's unified memory. One Google account, one vote per model.

Quant playground.

Build a setup the way you'd build a quant: pick a Mac, pick a model, drop it to 3-bit, quantize the KV cache, switch on speculative decoding. Every number is computed live from a roofline model fitted to our own published benchmarks. No download, no waiting.

Chip
Unified memory

Model Weights
KV cache
Context
Speculative decoding
Workload
tok/s generated
tok/s prompt
intelligence
Intelligence

Memory

My Mac has
Must have
Loading votes…
S
A
B
C
D

Not yet ranked

Models with no published Artificial Analysis score. Real enough to run, not yet measured, so they aren't placed on a guess. Vote them up anyway: your votes are what will rank this board. Same hardware filters as above; rows hold their position while you vote.

ModelParams~SizeRuns on↓ / moTagsYour vote

Honest rankings, tiny rules

Voting

One account, one vote per model

Sign in with Google, then ▲ or ▼ any model. Click the same arrow again to take your vote back, or the other one to flip it. Your votes are keyed to your account — refreshing, reinstalling, or switching devices can't double-count you.

Tiers

Benchmarked now, voted later

Nobody has voted yet, and a board where every model sits unranked helps no one, so tiers currently come from the Artificial Analysis Intelligence Index. Models it hasn't scored stay in the table below rather than being placed on a guess. Once the votes are in, the board switches to community ranking: the lower bound of the Wilson confidence interval on the up-ratio, so ten early fans can't out-rank a hundred mixed reviews.

Hardware

The filter is about fitting

Each model lists its approximate quantized footprint; the RAM filter hides anything that wouldn't leave your Mac room to breathe (weights ≲ 75% of unified memory). Votes are global — the filter changes what you see, not the scores.

Privacy

No emails stored, ever

Votes are stored against an opaque account id in Firestore. The public data is just model → up/down counts; your name and email never leave the sign-in widget in your own browser.

Found your model?
Run it in one command.

mlx-serve run <model> downloads it straight from Hugging Face and drops you into a chat — or grab the Mac app.