hf.co/Edge-Quant/Nanbeige4.1-3B-Q8_0-GGUF:Q8_0

llama · 3.93B · unknown

THINKING MODEL

MacBook Pro (Apple M1 Pro)

16 GB · macOS 26.6.2

Tested on August 22, 2026
Top 87% Compare
Global Score
52 /100
Not Rec.
Hardware Fit
75/100
Quality
42/100

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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
43.5
Standard deviation
±0.0
First chunk latency
225 ms
Time to first token
30.0 s
Load time
2.7 s
Memory usage
8.2 GB (51%)
Total tokens
1445
Thinking tokens (est.)
~930

Score breakdown

Speed
50/50
Time to first token
0/20
Memory
25/30

Quality

Reasoning
13/20
Coding
1/20
Instruction following
7/20
Structured output
1/15
Math
13/15
Multilingual
7/10

Category levels

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

Metadata

Spec version
0.2.1
Runtime
Ollama 0.32.14
Model format
GGUF
Hardware profile
ENTRY
Result hash
656b5498c571c2b7e7b26bb376a6dc2c339967c92c02d9bcac353d51e6f74a74

Interpretation

Hardware fit: 75/100. Overall suitability: NOT RECOMMENDED (Global 52/100). Category profile: Reasoning: Adequate, Coding: Poor, Instruction Following: Weak, Structured Output: Poor, Math: Strong, Multilingual: Adequate.

Disqualifiers

  • Time to first token too high: 30000ms (maximum: 22068ms for ENTRY profile)

Bench Environment

Power: AC CPU load: avg 37% (peak 38%)

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