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Coding Performance with 10 Evaluators — Run
Comprehensive evaluation of 2 language models across 1 system prompt with rigorous benchmarking and scoring criteria.
8.29
glm-5.3
5.00
Spread: 6.58 pts
2114ms
Response time
80
8 total responses
Executive Insights
Key takeaways from this evaluation
Top Performer
glm-5.3
8.29
6.58 pts ahead of #2
Model Rankings
Ranked by overall performance score
glm-5.3
z-ai/glm-5.3
Derived from how judges ranked this response against the others — not an absolute quality rating.
Responses
4
Avg Latency
473ms
Cost
$0.0205
qwen3.8-max-0902
qwen/qwen3.8-max-0902
Derived from how judges ranked this response against the others — not an absolute quality rating.
Responses
4
Avg Latency
3754ms
Cost
$0.0211
Evaluator Consensus
How 9 evaluator models ranked the candidates via blind comparison
unanimous Agreement
All 9 evaluators agree on the top model
glm-5.3
Avg Rank
1.0
Range
#1
#1 Votes
9/9
Latency
473ms
qwen3.8-max-0902
Avg Rank
2.0
Range
#2
#1 Votes
0/9
Latency
3754ms
gpt-5.4-mini
gemini-3.1-flash-lite-preview
claude-sonnet-4.6
minimax-m2.7
kimi-k2.5
deepseek-v3.2
mistral-small-2603
qwen3.5-27b
nova-2-lite-v1
Score Comparison
Visual comparison of all model scores
Performance by System Prompt
How each model performs across different evaluation contexts
Top Performer
glm-5.3
8.29
Performance by Test Prompt
Model results broken down by individual test prompts
| Test Prompt | Avg Score |
|---|---|
Javascript Function 2 responses | 5.00 |
Write an Interval Merge Function 2 responses | 5.00 |
Debug Python 2 responses | 5.00 |
Refactor Javascript 2 responses | 5.00 |
About This Evaluation
Methodology, criteria weights, and evaluation confidence
8
Total Responses
80
Total Evaluations
