hf.co/ornith-ai/Ornith-1.0-9B-GGUF:Q8_0

qwen35 · 8.95B · unknown

THINKING MODEL

MacBook Pro (Apple M1 Pro)

16 GB · macOS 26.6.2

Tested on August 23, 2026

Top 83% Compare

Global Score

57 /100

Marginal

Hardware Fit

81/100

Quality

46/100

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Ollama

ollama pull hf.co/ornith-ai/Ornith-1.0-9B-GGUF:Q8_0

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ollama.com/library/hf.co/ornith-ai/Ornith-1.0-9B-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: 18.6
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.0
First chunk latency Delay before the first streamed chunk arrives from runtime: 303 ms
Time to first token How fast the model starts responding — lower is better: 303 ms
Load time Time to load the model into memory before inference: 4.6 s
Memory usage RAM consumed during inference — percentage of total system memory: 10.1 GB (63%)
Total tokens Total number of tokens generated across all benchmark prompts: 1429

Score breakdown

Speed

42/50

Time to first token

20/20

Memory

19/30

Quality

Reasoning

14/20

Coding

13/20

Instruction following

5/20

Structured output

1/15

Math

13/15

Multilingual

0/10

Category levels

Reasoning: Adequate Coding: Adequate Instruction Following: Weak 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: 3dfb2d0050bce5e3213fc994b2f550f60268895592b6fe46945f7ff929908928

Interpretation

Hardware fit: 81/100. Overall suitability: MARGINAL (Global 57/100). Category profile: Reasoning: Adequate, Coding: Adequate, Instruction Following: Weak, Structured Output: Poor, Math: Strong, Multilingual: Poor.

Bench Environment

Power: AC CPU load: avg 21% (peak 43%)

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