parable-qwen3-4b-claude-fable-5
qwen3 · 4B · Q4_K_M
Gigabyte Technology Co., Ltd. H310M S2 2.0 (Intel Core™ i3-9100F)
16 GB · Майкрософт Windows 10 Pro 10.0.19045
Tested on October 24, 2026
Global Score
67 /100
Good
Hardware Fit
66/100
Quality
67/100
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Hardware
- Machine
- Gigabyte Technology Co., Ltd. H310M S2 2.0
- CPU
- Intel Core™ i3-9100F
- Cores
- 4 total (4 perf)
- Frequency
- 3.6 GHz
- RAM
- 16 GB DDR4
- GPU
- Virtual Desktop Monitor, NVIDIA GeForce GTX 1650
- OS
- Майкрософт Windows 10 Pro 10.0.19045
- Arch
- x64
- Power Mode
- balanced
Performance
- Tokens/sec
- 4.3
- Standard deviation
- ±0.2
- First chunk latency
- 13 ms
- Time to first token
- 1.9 s
- Load time
- N/A
- Memory usage
- 3.0 GB (19%)
- Total tokens
- 1120
Score breakdown
Speed
16/50
Time to first token
20/20
Memory
30/30
Quality
Reasoning
12/20
Coding
12/20
Instruction following
13/20
Structured output
15/15
Math
5/15
Multilingual
10/10
Category levels
Reasoning: Adequate Coding: Adequate Instruction Following: Adequate Structured Output: Strong Math: Weak Multilingual: Strong
Metadata
- Spec version
- 0.2.1
- Runtime
- LM Studio 0.4.11+1
- Model format
- GGUF
- Hardware profile
- ENTRY
- Result hash
- c5375e7dc4547bd60f9ddd0b28621f8488ddf14bcd6c097e758f71ae51ffe3c7
Interpretation
Hardware fit: 66/100. Overall suitability: GOOD (Global 67/100). Category profile: Reasoning: Adequate, Coding: Adequate, Instruction Following: Adequate, Structured Output: Strong, Math: Weak, Multilingual: Strong.
Warnings
- Model memory footprint is estimated via LM Studio CLI rather than measured from a fresh load.
Bench Environment
Swap delta:
+0.0 GB
CPU load: avg 32% (peak 38%)
Run yours now
$
npm install -g metrillm@latest$
metrillmRequires Node 20+ and Ollama or LM Studio running
Or run without installing: npx metrillm@latest