hf.co/bloomer010/Ling-3.0-tiny-GGUF:Q8_0

bailingmoe3 · 7.89B · unknown

MacBook Pro (Apple M1 Pro)

16 GB · macOS 26.6.2

Tested on August 23, 2026

Top 65% Compare

Global Score

68 /100

Good

Hardware Fit

94/100

Quality

57/100

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Ollama

ollama pull hf.co/bloomer010/Ling-3.0-tiny-GGUF:Q8_0

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ollama.com/library/hf.co/bloomer010/Ling-3.0-tiny-GGUF

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GGUF versions & quantizations

Hardware

Machine: MacBook Pro
CPU: Apple M1 Pro
Cores: 10 total (8 perf + 2 eff)
Frequency: 2.4 GHz
RAM: 16 GB LPDDR5
GPU: Apple M1 Pro
OS: macOS 26.6.2
Arch: arm64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 58.4
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: 220 ms
Time to first token How fast the model starts responding — lower is better: 220 ms
Load time Time to load the model into memory before inference: 0.0 s
Memory usage RAM consumed during inference — percentage of total system memory: 8.4 GB (53%)
Total tokens Total number of tokens generated across all benchmark prompts: 1452

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

24/30

Quality

Reasoning

19/20

Coding

17/20

Instruction following

3/20

Structured output

1/15

Math

15/15

Multilingual

2/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.32.15
Model format: GGUF
Hardware profile: ENTRY
Result hash: 63c34c1a8aebcca5cef7bba81bf2b3b77555e2e6f9bdb572018a255ded8f92c0

Interpretation

Hardware fit: 94/100. Overall suitability: GOOD (Global 68/100). Category profile: Reasoning: Strong, Coding: Strong, Instruction Following: Poor, Structured Output: Poor, Math: Strong, Multilingual: Poor.

Bench Environment

Power: AC CPU load: avg 36% (peak 41%)

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