qwen3.8-27b-fable-fusion-f711-gain-mlx
qwen3_5 · 27B · MXFP4
THINKING MODEL
MacBook Pro (Apple M4 Max)
128 GB · macOS 26.5.2
Tested on August 20, 2026 · Submitted by Jujube
Global Score
88 /100
Excellent
Hardware Fit
70/100
Quality
96/100
Get this model
Hardware
- Machine
- MacBook Pro
- CPU
- Apple M4 Max
- Cores
- 16 total (12 perf + 4 eff)
- Frequency
- 2.4 GHz
- RAM
- 128 GB LPDDR5
- GPU
- Apple M4 Max
- OS
- macOS 26.5.2
- Arch
- arm64
- Power Mode
- balanced
Performance
- Tokens/sec
- 30.4
- Standard deviation
- ±0.4
- First chunk latency
- 27 ms
- Time to first token
- 4.4 s
- Load time
- N/A
- Memory usage
- 19.9 GB (16%)
- Total tokens
- 1598
- Thinking tokens (est.)
- ~600
Score breakdown
Speed
34/50
Time to first token
6/20
Memory
30/30
Quality
Reasoning
19/20
Coding
19/20
Instruction following
18/20
Structured output
15/15
Math
15/15
Multilingual
10/10
Category levels
Reasoning: Strong Coding: Strong Instruction Following: Strong Structured Output: Strong Math: Strong Multilingual: Strong
Metadata
- Spec version
- 0.2.1
- Runtime
- LM Studio 0.4.12+1
- Model format
- MLX
- Hardware profile
- HIGH-END
- Result hash
- 2beca356929b7a3dc9ec48e8f1ac47df98d6fc49bb8a001d98b29626707e7300
Interpretation
Hardware fit: 70/100. Overall suitability: EXCELLENT (Global 88/100). Category profile: Reasoning: Strong, Coding: Strong, Instruction Following: Strong, Structured Output: Strong, Math: Strong, Multilingual: Strong.
Warnings
- Model memory footprint is estimated via LM Studio CLI rather than measured from a fresh load.
Bench Environment
Power: AC CPU load: avg 12% (peak 13%)
Run yours now
$
npm install -g metrillm@latest$
metrillmRequires Node 20+ and Ollama or LM Studio running
Or run without installing: npx metrillm@latest