lfm2-24b-a2b

THINKING MODEL

Mac mini (Apple M4 Pro)

64 GB · macOS 15.7.4

Tested on March 6, 2026

Top 100% Compare

Global Score

18 /100

Not Rec.

Hardware Fit

59/100

Quality

0/100

Get this model

Get it in LM Studio

Search and download models directly from the app

🤗

Find on HuggingFace

MLX versions & conversions

Hardware

Machine: Mac mini
CPU: Apple M4 Pro
Cores: 14 total (10 perf + 4 eff)
Frequency: 2.4 GHz
RAM: 64 GB LPDDR5
GPU: Apple M4 Pro
OS: macOS 15.7.4
Arch: arm64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 6.6
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±4.3
First chunk latency Delay before the first streamed chunk arrives from runtime: 1.0 s
Time to first token How fast the model starts responding — lower is better: 1.0 s
Load time Time to load the model into memory before inference: N/A
Memory usage RAM consumed during inference — percentage of total system memory: 0.0 GB (0%)
Total tokens Total number of tokens generated across all benchmark prompts: 558

Score breakdown

Speed

9/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

0/20

Coding

0/20

Instruction following

0/20

Structured output

0/15

Math

0/15

Multilingual

0/10

Category levels

Reasoning: Poor Coding: Poor Instruction Following: Poor Structured Output: Poor Math: Poor Multilingual: Poor

Metadata

Spec version: 0.2.1
Runtime: LM Studio 0.4.6+1
Model format: GGUF
Hardware profile: HIGH-END
Result hash: ee428d98cb597d14e3f6228b34d1587ca2929ee82106ee04e1d3c90647797460

Interpretation

Hardware fit: 59/100. Overall suitability: NOT RECOMMENDED (Global 18/100). Category profile: Reasoning: Poor, Coding: Poor, Instruction Following: Poor, Structured Output: Poor, Math: Poor, Multilingual: Poor. Warning: model produced very low accuracy on quality tasks — results may be unusable despite good hardware performance.

Warnings

Model produced very low accuracy on quality tasks — results may be unusable despite good hardware performance.
Token speed is unstable (stddev 4.3 tok/s, mean 6.6 tok/s) — may indicate thermal throttling or memory pressure.

Bench Environment

Power: AC CPU load: avg 29% (peak 34%)

Run yours now

$ npm install -g metrillm@latest

$ metrillm

Requires Node 20+ and Ollama or LM Studio running

Or run without installing: npx metrillm@latest