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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.
5.64
step-3.5-flash
5.00
Spread: 1.28 pts
—
Response time
80
8 total responses
Executive Insights
Key takeaways from this evaluation
Top Performer
step-3.5-flash
5.64
1.28 pts ahead of #2
Model Rankings
Ranked by overall performance score
step-3.5-flash
stepfun/step-3.5-flash
Average
Responses
4
Avg Latency
—
Cost
$0.0075
gemini-2.5-flash
google/gemini-2.5-flash
Below Average
Responses
4
Avg Latency
—
Cost
$0.0022
Evaluator Consensus
How 10 evaluator models ranked the candidates via blind comparison
split Agreement
Evaluators disagree on which model is best
gemini-2.5-flash
Avg Rank
1.5
Range
#1–2
#1 Votes
5/10
Latency
—
step-3.5-flash
Avg Rank
1.5
Range
#1–2
#1 Votes
5/10
Latency
—
gpt-5.4-mini
gemini-3.1-flash-lite-preview
claude-sonnet-4.6
minimax-m2.7
kimi-k2.5
deepseek-v3.2
grok-4.1-fast
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
step-3.5-flash
5.64
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
