hf.co/bartowski/ai9stars_G9v3-3B-GGUF:BF16

llama · 2.99B · BF16

MacBook Pro (Apple M1 Pro)

16 GB · macOS 26.6.2

Tested on August 26, 2026 · Submitted by AAA

Top 74% Compare

Global Score

64 /100

Good

Hardware Fit

92/100

Quality

52/100

Get this model

🦙

Ollama

ollama pull hf.co/bartowski/ai9stars_G9v3-3B-GGUF:BF16

View on Ollama Library

ollama.com/library/hf.co/bartowski/ai9stars_G9v3-3B-GGUF

Get it in LM Studio

Search and download models directly from the app

🤗

Find on HuggingFace

GGUF versions & quantizations

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 Tokens generated per second — higher is better: 29.9
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.1
First chunk latency Delay before the first streamed chunk arrives from runtime: 108 ms
Time to first token How fast the model starts responding — lower is better: 108 ms
Load time Time to load the model into memory before inference: 3.4 s
Memory usage RAM consumed during inference — percentage of total system memory: 8.9 GB (56%)
Total tokens Total number of tokens generated across all benchmark prompts: 1349

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

22/30

Quality

Reasoning

17/20

Coding

14/20

Instruction following

6/20

Structured output

0/15

Math

14/15

Multilingual

1/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.32.15
Model format: GGUF
Hardware profile: ENTRY
Result hash: 5240d66d787d05f2f94330e3e21c4f991d481fbfb0e038d058c69827666987f3

Interpretation

Hardware fit: 92/100. Overall suitability: GOOD (Global 64/100). Category profile: Reasoning: Strong, Coding: Adequate, Instruction Following: Weak, Structured Output: Poor, Math: Strong, Multilingual: Poor.

Bench Environment

Power: AC CPU load: avg 35% (peak 39%)

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