exaone-3.5-2.4b-instruct-mlx

exaone · 2.4B · 8bit

MacBook Air (Apple M4)

32 GB · macOS 26.3

Tested on March 4, 2026

Top 31% Compare

Global Score

75 /100

Good

Hardware Fit

100/100

Quality

64/100

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Hardware

Machine: MacBook Air
CPU: Apple M4
Cores: 10 total (4 perf + 6 eff)
Frequency: 2.4 GHz
RAM: 32 GB LPDDR5
GPU: Apple M4
OS: macOS 26.3
Arch: arm64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 37.0
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±1.5
First chunk latency Delay before the first streamed chunk arrives from runtime: 288 ms
Time to first token How fast the model starts responding — lower is better: 288 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: 2.4 GB (8%)
Total tokens Total number of tokens generated across all benchmark prompts: 1252

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

9/20

Coding

13/20

Instruction following

15/20

Structured output

14/15

Math

5/15

Multilingual

8/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: LM Studio 0.4.6+1
Model format: MLX
Hardware profile: BALANCED
Result hash: f36fbfe6cb33e1df9a126a11b7a85c5c115eafa58faafe79a9acf4515305d305

Interpretation

Hardware fit: 100/100. Overall suitability: GOOD (Global 75/100). Category profile: Reasoning: Weak, Coding: Adequate, Instruction Following: Strong, Structured Output: Strong, Math: Weak, Multilingual: Strong.

Bench Environment

Power: AC CPU load: avg 15% (peak 18%)

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