qwen3.5-27b-claude-4.6-opus-distilled-mlx
qwen3_5 · 27B · 4bit
THINKING MODEL
Mac mini (Apple M4)
24 GB · macOS 26.3
Tested on March 10, 2026
Global Score
34 /100
Not Rec.
Hardware Fit
21/100
Quality
39/100
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Hardware
- Machine
- Mac mini
- CPU
- Apple M4
- Cores
- 10 total (4 perf + 6 eff)
- Frequency
- 2.4 GHz
- RAM
- 24 GB LPDDR5
- GPU
- Apple M4
- OS
- macOS 26.3
- Arch
- arm64
- Power Mode
- balanced
Performance
- Tokens/sec
- 6.1
- Standard deviation
- ±0.6
- First chunk latency
- 7 ms
- Time to first token
- 22.9 s
- Load time
- N/A
- Memory usage
- 19.8 GB (82%)
- Total tokens
- 1729
- Thinking tokens (est.)
- ~553
Score breakdown
Speed
12/50
Time to first token
0/20
Memory
9/30
Quality
Reasoning
1/20
Coding
14/20
Instruction following
5/20
Structured output
8/15
Math
4/15
Multilingual
7/10
Category levels
Reasoning: Poor Coding: Adequate Instruction Following: Weak Structured Output: Adequate Math: Poor Multilingual: Adequate
Metadata
- Spec version
- 0.2.1
- Runtime
- LM Studio 0.4.6+1
- Model format
- MLX
- Hardware profile
- ENTRY
- Result hash
- 9d2f7dbabebf5656b57cbc30df836ebc3a2b33c29ad4fa84231ce3aa3fc6bf52
Interpretation
Hardware fit: 21/100. Overall suitability: NOT RECOMMENDED (Global 34/100). Category profile: Reasoning: Poor, Coding: Adequate, Instruction Following: Weak, Structured Output: Adequate, Math: Poor, Multilingual: Adequate.
Warnings
- Model memory footprint is estimated via LM Studio CLI rather than measured from a fresh load.
Disqualifiers
- Time to first token too high: 22856ms (maximum: 21386ms for ENTRY profile)
Bench Environment
Power: AC CPU load: avg 9% (peak 14%)
Run yours now
$
npm install -g metrillm@latest$
metrillmRequires Node 20+ and Ollama or LM Studio running
Or run without installing: npx metrillm@latest