qwen3.8-27b-claude-opus-reasoning-distilled
qwen35 · 27B · Q4_K_M
THINKING MODEL
MacBook Pro (Apple M4 Max)
128 GB · macOS 26.5.2
Tested on August 20, 2026 · Submitted by Jujube
Global Score
80 /100
Excellent
Hardware Fit
63/100
Quality
87/100
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
- 24.0
- Standard deviation
- ±1.8
- First chunk latency
- 20 ms
- Time to first token
- 4.5 s
- Load time
- N/A
- Memory usage
- 15.7 GB (12%)
- Total tokens
- 1553
- Thinking tokens (est.)
- ~491
Score breakdown
Speed
27/50
Time to first token
6/20
Memory
30/30
Quality
Reasoning
19/20
Coding
18/20
Instruction following
11/20
Structured output
15/15
Math
14/15
Multilingual
10/10
Category levels
Reasoning: Strong Coding: Strong Instruction Following: Adequate Structured Output: Strong Math: Strong Multilingual: Strong
Metadata
- Spec version
- 0.2.1
- Runtime
- LM Studio 0.4.12+1
- Model format
- GGUF
- Hardware profile
- HIGH-END
- Result hash
- 4df413c984e474ba2ac87a15a8f593ee44298c5f7188b104b579c49cd20bec19
Interpretation
Hardware fit: 63/100. Overall suitability: EXCELLENT (Global 80/100). Category profile: Reasoning: Strong, Coding: Strong, Instruction Following: Adequate, 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 9% (peak 10%)
Run yours now
$
npm install -g metrillm@latest$
metrillmRequires Node 20+ and Ollama or LM Studio running
Or run without installing: npx metrillm@latest