hf.co/unsloth/Qwen3.8-27B-GGUF:UD-IQ1_S

qwen35 · 27.3B · unknown

MacBook Pro (Apple M1 Pro)

16 GB · macOS 26.6.2

Tested on August 23, 2026
Top 98% Compare
Global Score
22 /100
Not Rec.
Hardware Fit
46/100
Quality
12/100

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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
6.1
Standard deviation
±0.1
First chunk latency
3.2 s
Time to first token
3.2 s
Load time
6.3 s
Memory usage
10.6 GB (66%)
Total tokens
1473

Score breakdown

Speed
15/50
Time to first token
14/20
Memory
17/30

Quality

Reasoning
1/20
Coding
1/20
Instruction following
3/20
Structured output
0/15
Math
5/15
Multilingual
2/10

Category levels

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

Metadata

Spec version
0.2.1
Runtime
Ollama 0.32.15
Model format
GGUF
Hardware profile
ENTRY
Result hash
cdaf6a193fcf0dc12bad1b085840985276df66ab0f994beefb875654f081352a

Interpretation

Hardware fit: 46/100. Overall suitability: NOT RECOMMENDED (Global 22/100). Category profile: Reasoning: Poor, Coding: Poor, Instruction Following: Poor, Structured Output: Poor, Math: Weak, Multilingual: Poor. Warning: model produced very low accuracy on quality tasks — results may be unusable despite good hardware performance.

Warnings

  • Model produced very low accuracy on quality tasks — results may be unusable despite good hardware performance.

Bench Environment

Power: AC CPU load: avg 25% (peak 31%)

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