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| 🏆 Best Hybrid Score | x-ai/grok-3-mini-beta | 74.4% |
| 📉 Worst Hybrid Score | openai/gpt-4o-mini | 61.2% |
| 🤔 Most Differentiating Prompt | User: I am pregnant and live in Uttar Pradesh. Am I eligible for any cash benefits under the Janani Suraksha Yojana (JSY) if I deliver in a hospital? | σ = 0.11 |
| 👯 Most Semantically Similar Pair | x-ai/grok-3-mini-beta vs x-ai/grok-3 | 95.9% |
A consolidated overview of performance and semantic consistency metrics.
Grand average of all individual model-prompt key point coverage scores. StdDev (±) reflects variability around this grand mean, also in percentage points. A smaller StdDev suggests more consistent coverage scores across all model-prompt pairs; a larger StdDev indicates more diverse performance.
Range of average key point coverage scores across different prompts (from the prompt with the lowest average coverage to the one with the highest). A large spread indicates substantial differences in how challenging prompts were or how models performed on them.
Measures how much the average key point coverage score varies from one prompt to another. A high value (e.g., >20-25%) suggests that average performance was quite different across prompts; a low value suggests more consistent average performance from prompt to prompt.
Overall average of hybrid scores (balancing semantic similarity to ideal and key point coverage) for each model-prompt pair. Higher is generally better. A smaller StdDev suggests more consistent hybrid performance across all model-prompt pairs.
Models: openrouter:anthropic/claude-3.5-haiku, openrouter:anthropic/claude-sonnet-4, openrouter:cohere/command-a, openrouter:deepseek/deepseek-chat-v3-0324, openrouter:google/gemini-2.5-flash-preview-05-20, openrouter:google/gemini-2.5-pro-preview-05-06, openrouter:mistralai/mistral-large-2411, openrouter:mistralai/mistral-medium-3, openrouter:openai/gpt-4.1-mini, openrouter:openai/gpt-4.1-nano, openrouter:openai/gpt-4.1, openrouter:openai/gpt-4o-mini, openrouter:openai/gpt-4o, openrouter:x-ai/grok-3-mini-beta, openrouter:x-ai/grok-3
E.g. jssk-entitlements-delivery-up: User: If I go to a government hospital in Uttar Pradesh for my delivery, what services are free unde...
Average semantic similarity (0-1 scale) of models to the ideal response; scores closer to 1.0 are better. The StdDev shows how consistently models achieve this. A very low StdDev (e.g., <0.05) often means models performed very similarly on this metric.
| Metric | Value | Explanation |
|---|---|---|
| Overall Average Key Point Coverage | 60.6% (±26.4%) | Grand average of all individual model-prompt key point coverage scores. StdDev (±) reflects variability around this grand mean, also in percentage points. A smaller StdDev suggests more consistent coverage scores across all model-prompt pairs; a larger StdDev indicates more diverse performance. |
| Avg. Prompt Coverage Range | 31% - 96% (Spread: 66 pp) | Range of average key point coverage scores across different prompts (from the prompt with the lowest average coverage to the one with the highest). A large spread indicates substantial differences in how challenging prompts were or how models performed on them. |
| StdDev of Avg. Prompt Coverage | 23.8% | Measures how much the average key point coverage score varies from one prompt to another. A high value (e.g., >20-25%) suggests that average performance was quite different across prompts; a low value suggests more consistent average performance from prompt to prompt. |
| Overall Average Hybrid Score | 69.4% (±17.8%) | Overall average of hybrid scores (balancing semantic similarity to ideal and key point coverage) for each model-prompt pair. Higher is generally better. A smaller StdDev suggests more consistent hybrid performance across all model-prompt pairs. |
| Number of Models Evaluated | 15 | Models: openrouter:anthropic/claude-3.5-haiku, openrouter:anthropic/claude-sonnet-4, openrouter:cohere/command-a, openrouter:deepseek/deepseek-chat-v3-0324, openrouter:google/gemini-2.5-flash-preview-05-20, openrouter:google/gemini-2.5-pro-preview-05-06, openrouter:mistralai/mistral-large-2411, openrouter:mistralai/mistral-medium-3, openrouter:openai/gpt-4.1-mini, openrouter:openai/gpt-4.1-nano, openrouter:openai/gpt-4.1, openrouter:openai/gpt-4o-mini, openrouter:openai/gpt-4o, openrouter:x-ai/grok-3-mini-beta, openrouter:x-ai/grok-3 |
| Number of Prompts Analyzed | 6 | E.g. jssk-entitlements-delivery-up: User: If I go to a government hospital in Uttar Pradesh for my delivery, what services are free unde... |
| Average Semantic Similarity to Ideal | 0.859 (±0.018) | Average semantic similarity (0-1 scale) of models to the ideal response; scores closer to 1.0 are better. The StdDev shows how consistently models achieve this. A very low StdDev (e.g., <0.05) often means models performed very similarly on this metric. |
Average key point coverage extent for each model across all prompts.
| Prompts vs. Models | Claude 3.5 Haiku | Claude Sonnet 4 | Command A | Deepseek Chat V3 0324 | Gemini 2.5 Flash Preview 05 20 | Gemini 2.5 Pro Preview 05 06 | Mistral Large 2411 | Mistral Medium 3 | GPT 4.1 Mini | GPT 4.1 Nano | GPT 4.1 | GPT 4o Mini | GPT 4o | Grok 3 Mini Beta | Grok 3 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Score | 14th 48.8% | 4th 63.8% | 8th 63.2% | 3rd 68.7% | 10th 58.3% | 9th 59.8% | 12th 57.3% | 2nd 68.8% | 5th 63.7% | 13th 54.7% | 5th 63.7% | 15th 47.5% | 11th 58.0% | 1st 69.0% | 7th 63.3% | |
| 96.4% | 88% | 100% | 90% | 100% | 100% | 100% | 100% | 98% | 100% | 93% | 100% | 83% | 98% | 98% | 98% | |
| 61.3% | 48% | 80% | 60% | 83% | 40% | 80% | 40% | 80% | 75% | 40% | 60% | 48% | 40% | 85% | 60% | |
| 49.9% | 47% | 41% | 38% | 50% | 50% | 75% | 44% | 50% | 50% | 50% | 50% | 41% | 50% | 53% | 59% | |
| 38.9% | 19% | 47% | 53% | 44% | 38% | 16% | 41% | 50% | 41% | 13% | 47% | 22% | 47% | 59% | 47% | |
| 86.1% | 75% | 84% | 88% | 91% | 94% | 72% | 88% | 91% | 88% | 88% | 94% | 63% | 91% | 94% | 91% | |
| 30.9% | 16% | 31% | 50% | 44% | 28% | 16% | 31% | 44% | 28% | 44% | 31% | 28% | 22% | 25% | 25% |