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 25, 2026 · Submitted by AAA

Top 51% Compare

Global Score

76 /100

Good

Hardware Fit

92/100

Quality

69/100

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Ollama

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

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

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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: 105 ms
Time to first token How fast the model starts responding — lower is better: 105 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: 1003

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

22/30

Quality

Reasoning

11/20

Coding

13/20

Instruction following

12/20

Structured output

15/15

Math

10/15

Multilingual

8/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.32.15
Model format: GGUF
Hardware profile: ENTRY
Result hash: b65519d6de926fd7049ba1d78fa1609bb61de9f1c2e971b02eaef10f29a0b84e

Interpretation

Hardware fit: 92/100. Overall suitability: GOOD (Global 76/100). Category profile: Reasoning: Adequate, Coding: Adequate, Instruction Following: Adequate, Structured Output: Strong, Math: Adequate, Multilingual: Strong.

Bench Environment

Power: AC CPU load: avg 39% (peak 42%)

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