rnj-1:8b

gemma3 · 8.3B · Q4_K_M

MacBook Pro (Apple M1 Pro)

16 GB · macOS 26.6.2

Tested on August 24, 2026 · Submitted by AAA

Top 39% Compare

Global Score

80 /100

Excellent

Hardware Fit

93/100

Quality

74/100

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Ollama

ollama pull rnj-1:8b

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ollama.com/library/rnj-1

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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: 22.3
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: 404 ms
Time to first token How fast the model starts responding — lower is better: 404 ms
Load time Time to load the model into memory before inference: 3.7 s
Memory usage RAM consumed during inference — percentage of total system memory: 8.3 GB (52%)
Total tokens Total number of tokens generated across all benchmark prompts: 1014

Score breakdown

Speed

49/50

Time to first token

20/20

Memory

24/30

Quality

Reasoning

12/20

Coding

19/20

Instruction following

15/20

Structured output

5/15

Math

14/15

Multilingual

9/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.32.15
Model format: GGUF
Hardware profile: ENTRY
Result hash: b20464663ad4e8e2674d280dc85d115a0ad20b70f95f587b3017bf9fe15f6348

Interpretation

Hardware fit: 93/100. Overall suitability: EXCELLENT (Global 80/100). Category profile: Reasoning: Adequate, Coding: Strong, Instruction Following: Strong, Structured Output: Weak, Math: Strong, Multilingual: Strong.

Bench Environment

Power: AC CPU load: avg 25% (peak 28%)

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