hf.co/InternScience/Agents-A1-4B-Q8_0-GGUF:Q8_0

qwen35 · 4.21B · unknown

THINKING MODEL

MacBook Pro (Apple M1 Pro)

16 GB · macOS 26.6.2

Tested on August 22, 2026

Top 81% Compare

Global Score

59 /100

Marginal

Hardware Fit

97/100

Quality

43/100

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ollama.com/library/hf.co/InternScience/Agents-A1-4B-Q8_0-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: 30.9
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.0
First chunk latency Delay before the first streamed chunk arrives from runtime: 891 ms
Time to first token How fast the model starts responding — lower is better: 891 ms
Load time Time to load the model into memory before inference: 3.6 s
Memory usage RAM consumed during inference — percentage of total system memory: 6.6 GB (41%)
Total tokens Total number of tokens generated across all benchmark prompts: 2634

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

27/30

Quality

Reasoning

13/20

Coding

15/20

Instruction following

2/20

Structured output

0/15

Math

13/15

Multilingual

0/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.32.14
Model format: GGUF
Hardware profile: ENTRY
Result hash: cbda9e8bd44d9db3542abee159026c091a8e98d794d7dd5a8f76b929c3ccfba6

Interpretation

Hardware fit: 97/100. Overall suitability: MARGINAL (Global 59/100). Category profile: Reasoning: Adequate, Coding: Adequate, Instruction Following: Poor, Structured Output: Poor, Math: Strong, Multilingual: Poor.

Bench Environment

Power: AC CPU load: avg 32% (peak 61%)

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