liquid/lfm2-24b-a2b

lfm2_moe · 24B · 4bit

Mac mini (Apple M4)

24 GB · macOS 26.3

Tested on April 1, 2026 · Submitted by cryptoepops

Top 36% Compare

Global Score

74 /100

Good

Hardware Fit

84/100

Quality

69/100

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Hardware

Machine: Mac mini
CPU: Apple M4
Cores: 10 total (4 perf + 6 eff)
Frequency: 2.4 GHz
RAM: 24 GB LPDDR5
GPU: Apple M4
OS: macOS 26.3
Arch: arm64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 51.8
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±2.1
First chunk latency Delay before the first streamed chunk arrives from runtime: 10 ms
Time to first token How fast the model starts responding — lower is better: 503 ms
Load time Time to load the model into memory before inference: N/A
Memory usage RAM consumed during inference — percentage of total system memory: 17.5 GB (73%)
Total tokens Total number of tokens generated across all benchmark prompts: 1348

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

14/30

Quality

Reasoning

11/20

Coding

12/20

Instruction following

16/20

Structured output

13/15

Math

8/15

Multilingual

9/10

Category levels

Reasoning: Adequate Coding: Adequate Instruction Following: Strong Structured Output: Strong Math: Adequate Multilingual: Strong

Metadata

Spec version: 0.2.1
Runtime: LM Studio 0.4.8+1
Model format: MLX
Hardware profile: ENTRY
Result hash: 3cb843afd0eef2f2ee9bcd07af6d27cb9705016f187696adac3bd191856ef917

Interpretation

Hardware fit: 84/100. Overall suitability: GOOD (Global 74/100). Category profile: Reasoning: Adequate, Coding: Adequate, Instruction Following: Strong, Structured Output: Strong, Math: Adequate, Multilingual: Strong.

Warnings

Model memory footprint is estimated via LM Studio CLI rather than measured from a fresh load.

Bench Environment

Power: AC CPU load: avg 30% (peak 32%)

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