internlm2:7b

internlm2 · 7.7B · Q4_0

MacBook Air (Apple M4)

32 GB · macOS 26.3

Tested on March 6, 2026

Top 24% Compare

Global Score

77 /100

Good

Hardware Fit

95/100

Quality

69/100

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Ollama

ollama pull internlm2:7b

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ollama.com/library/internlm2

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GGUF versions & quantizations

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: 22.7
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.2
First chunk latency Delay before the first streamed chunk arrives from runtime: 250 ms
Time to first token How fast the model starts responding — lower is better: 250 ms
Load time Time to load the model into memory before inference: 0.7 s
Memory usage RAM consumed during inference — percentage of total system memory: 10.6 GB (33%)
Total tokens Total number of tokens generated across all benchmark prompts: 1209

Score breakdown

Speed

45/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

12/20

Coding

10/20

Instruction following

13/20

Structured output

14/15

Math

11/15

Multilingual

9/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.17.6
Model format: GGUF
Hardware profile: BALANCED
Result hash: d65e1529605981f2151c61ef42a298d7f9230295e74e326f63900a7004e29d6b

Interpretation

Hardware fit: 95/100. Overall suitability: GOOD (Global 77/100). Category profile: Reasoning: Adequate, Coding: Adequate, Instruction Following: Adequate, Structured Output: Strong, Math: Adequate, Multilingual: Strong.

Bench Environment

Power: AC CPU load: avg 5% (peak 11%)

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$ npm install -g metrillm@latest

$ metrillm

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Or run without installing: npx metrillm@latest