qwen3.5:0.8b

qwen35 · 873.44M · Q8_0

MacBook Pro (Apple M1 Max)

32 GB · macOS 26.3

Tested on March 5, 2026 · Submitted by alph0x

Top 62% Compare

Global Score

62 /100

Good

Hardware Fit

100/100

Quality

46/100

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Ollama

ollama pull qwen3.5:0.8b

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ollama.com/library/qwen3.5

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GGUF versions & quantizations

Hardware

Machine: MacBook Pro
CPU: Apple M1 Max
Cores: 10 total (8 perf + 2 eff)
Frequency: 2.4 GHz
RAM: 32 GB LPDDR5
GPU: Apple M1 Max
OS: macOS 26.3
Arch: arm64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 65.8
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.4
First chunk latency Delay before the first streamed chunk arrives from runtime: 230 ms
Time to first token How fast the model starts responding — lower is better: 230 ms
Load time Time to load the model into memory before inference: 1.5 s
Memory usage RAM consumed during inference — percentage of total system memory: 2.6 GB (8%)
Total tokens Total number of tokens generated across all benchmark prompts: 980

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

9/20

Coding

4/20

Instruction following

11/20

Structured output

13/15

Math

3/15

Multilingual

6/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.17.6
Model format: GGUF
Hardware profile: BALANCED
Result hash: ce95edb0992b95672c41cd10134abc77ed205d74f001930baa342d38d13bd24f

Interpretation

Hardware fit: 100/100. Overall suitability: GOOD (Global 62/100). Category profile: Reasoning: Weak, Coding: Poor, Instruction Following: Adequate, Structured Output: Strong, Math: Poor, Multilingual: Adequate.

Bench Environment

Power: AC CPU load: avg 30% (peak 36%)

Run yours now

$ npm install -g metrillm@latest

$ metrillm

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Or run without installing: npx metrillm@latest