hf.co/ornith-ai/Ornith-1.0-9B-GGUF:Q4_K_M

qwen35 · 8.95B · unknown

THINKING MODEL

MacBook Pro (Apple M1 Pro)

16 GB · macOS 26.6.2

Tested on August 23, 2026
Top 76% Compare
Global Score
62 /100
Good
Hardware Fit
96/100
Quality
47/100

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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
22.3
Standard deviation
±0.0
First chunk latency
324 ms
Time to first token
324 ms
Load time
3.2 s
Memory usage
6.9 GB (43%)
Total tokens
1429

Score breakdown

Speed
49/50
Time to first token
20/20
Memory
27/30

Quality

Reasoning
16/20
Coding
14/20
Instruction following
3/20
Structured output
1/15
Math
13/15
Multilingual
0/10

Category levels

Reasoning: Strong Coding: Adequate 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
8d7c18ebe1ae4a87273fbdef6125474a8c2670816a9f30be8d0bfcd4d3185cae

Interpretation

Hardware fit: 96/100. Overall suitability: GOOD (Global 62/100). Category profile: Reasoning: Strong, Coding: Adequate, Instruction Following: Poor, Structured Output: Poor, Math: Strong, Multilingual: Poor.

Bench Environment

Power: AC CPU load: avg 16% (peak 18%)

Run yours now

$ npm install -g metrillm@latest
$ metrillm

Requires Node 20+ and Ollama or LM Studio running

Or run without installing: npx metrillm@latest