DTeval

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Analysis: Gd3 Ctx Dtef Global Dialogues Gd3 AiConcern%3Aequally Concerned And Excited Ctx - Run d561711...

Global Dialogues GD3 - Equally concerned and excited (with context)

DTEF: Predict response distributions for Equally concerned and excited. Source: Global Dialogues GD3 (https://github.com/collect-intel/global-dialogues)

TAGS:

Instruction Following & Prompt Adherence

Factual Accuracy & Hallucination

Reasoning

Problem solving

Knowledge, learning and memory

Best Models (Coverage)

1.GPT 5
86.4%
2.Claude Sonnet 4.5
85.8%
3.GPT 5.1
85.4%
4.Llama 4 Maverick
84.5%
5.Claude Sonnet 4
84.5%

🔀 Least Similar Models

Claude Sonnet 4.5vsGPT OSS 20b

68.7% similarity

👯 Most Similar Models

Claude 3.7 SonnetvsClaude Sonnet 4

89.7% similarity

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Macro Coverage Overview

Average key point coverage extent for each model across all prompts.

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Not Met

	Claude 3.7 Sonnet	Claude Haiku 4.5	Claude Sonnet 4	Claude Sonnet 4.5	Gemini 2.5 Flash	Gemma 3 12b It	Llama 4 Maverick	Mistral Large 2411	Mistral Medium 3	GPT 4.1	GPT 4.1 Mini	GPT 4.1 Nano	GPT 4o	GPT 4o Mini	GPT 5	GPT 5.1	GPT OSS 120b	GPT OSS 20b	Qwen3 30b A3B Instruct 2507	Qwen3 32b	Grok 4
Score	13th 82.1%	12th 82.8%	5th 84.5%	2nd 85.8%	6th 84.0%	21st 77.5%	4th 84.5%	9th 83.0%	11th 83.0%	7th 83.8%	9th 83.0%	20th 78.5%	14th 82.0%	17th 80.1%	1st 86.4%	3rd 85.4%	16th 80.2%	19th 78.7%	18th 79.7%	15th 81.8%	8th 83.4%
82.0%		82%	86%	84%	85%	78%	81%	80%	87%	82%	86%	73%	83%	75%	84%	80%	87%	74%	83%	90%	80%
82.2%		85%	75%	86%	78%	84%	86%	84%	80%	86%	85%	80%	79%	92%	89%	79%	63%	80%	87%	92%	73%
71.6%		72%	60%	68%	71%	71%	93%	65%	64%	71%	71%	95%	62%	93%	72%	72%	68%	71%	48%	72%	72%
91.0%	95%	86%	94%	93%	91%	83%	92%	92%	93%	92%	96%	92%	93%	86%	92%	91%	89%	87%	90%	92%	93%
81.4%		78%	81%	90%	78%	78%	86%	85%	81%	88%	78%	78%	78%	78%	90%	90%	73%	78%	78%	78%	84%
87.6%		91%	88%	90%	99%	96%	88%	95%	89%	81%	88%	89%	83%	93%	81%	86%	80%	86%	79%	82%	88%
85.8%		79%	89%	94%	87%	78%	84%	87%	85%	81%	82%	82%	85%	87%	91%	92%	89%	93%	76%	83%	92%
78.2%		78%	82%	82%	75%	67%	77%	88%	77%	87%	87%	73%	73%	73%	82%	80%	81%	73%	69%	78%	82%
79.5%		54%	72%	80%	91%	63%	78%	95%	86%	82%	83%	90%	85%	69%	82%	85%	79%	86%	69%	83%	78%
90.3%		94%	93%	95%	92%	92%	81%	92%	92%	91%	84%	91%	98%	92%	89%	92%	74%	85%	92%		97%
82.5%		91%	92%	94%	88%	71%	81%	92%	83%	82%	92%	92%	77%	74%	90%	86%	63%	54%	92%	73%
87.1%		92%	90%	96%	83%	77%	84%	94%	90%	87%	88%	94%	89%	94%	83%	91%	82%	74%	90%	75%	89%
92.5%		97%	93%	93%	96%	87%	93%	97%	92%	93%	96%	96%	89%	96%	94%	91%	85%	90%	96%	87%	90%
90.4%		96%	95%	95%	93%	84%	92%	90%	91%	92%	96%	73%	92%	82%	90%	95%	87%	89%	94%	94%	88%
95.1%		97%	97%	97%	95%	92%	97%	94%	97%	97%	95%	95%	97%	95%	93%	92%	92%	94%	93%	96%	96%
91.9%		92%	96%	89%	95%	97%	96%	91%	95%	89%	97%	69%	95%	92%	91%	89%	98%	88%	95%	91%	93%
75.6%		89%	83%	84%	76%	75%	71%	48%	75%	85%	90%	75%	60%	75%	85%	84%	83%	61%	86%	83%	45%
83.5%		77%	86%	84%	87%	87%	80%	85%	85%	78%	85%	73%	86%	81%	81%	85%	93%	91%	83%	83%	81%
66.2%		54%	64%	66%	79%	49%	64%	64%	69%	82%	59%	49%	67%	65%	90%	76%	74%	63%	53%	73%	64%
88.5%		86%	93%	94%	96%	78%	93%	95%	95%	98%	74%	76%	86%	84%	81%	96%	91%	86%	98%	80%	90%
87.5%		91%	89%	90%	95%	91%	95%	84%	91%	96%	90%	87%	95%	74%	94%	82%	83%	72%	86%	79%	87%
90.1%		90%	84%	91%	87%	87%	90%	93%	91%	89%	88%	87%	90%	87%	94%	92%	89%	95%	92%	95%	91%
79.4%	82%	74%	79%	79%	90%	74%	91%	84%	89%	90%	79%	66%	69%	79%	76%	75%	78%	84%	83%	73%	74%
91.3%		81%	95%	89%	96%	89%	96%	85%	91%	94%	94%	96%	92%	96%	89%	90%	92%	92%	96%	96%	76%
91.6%		91%	90%	97%	95%	82%	93%	94%	93%	94%	96%	72%	92%	95%	96%	96%	94%	84%	93%	95%	91%
75.3%		81%	80%	82%	85%	68%	74%	66%	74%	78%	75%	73%	71%	63%	80%	77%	66%	68%	87%	74%	84%
81.5%		75%	89%	88%	81%	84%	86%	88%	78%	81%	71%	70%	87%	80%	84%	80%	83%	79%	78%	80%	88%
78.8%		80%	86%	81%	90%	67%	77%	88%	87%	79%	76%	56%	84%	69%	90%	92%	78%	71%	72%	78%	75%
76.7%	79%	92%	85%	83%	80%	79%	80%	74%	70%	69%	78%	66%	76%	66%	84%	79%	67%	73%	79%	78%	74%
81.8%		81%	84%	90%	95%	78%	87%	88%	78%	78%	80%	91%	82%	74%	82%	76%	72%	75%	79%	83%	84%
93.3%	96%	94%	92%	95%	89%	91%	93%	93%	91%	93%	94%	93%	94%	93%	95%	94%	96%	93%	94%	93%
61.5%		57%	61%	65%	76%	42%	57%	73%	76%	57%	60%	53%	76%	42%	57%	57%	68%	76%	45%	76%	57%
66.1%		64%	65%	65%	65%	65%	93%	58%	59%	65%	65%	87%	55%	93%	64%	63%	61%	65%	42%	64%	64%
82.1%	91%	73%	88%	91%	76%	81%	80%	85%	83%	84%	78%	76%	81%	76%	91%	84%	83%	85%	73%		83%
76.1%	82%	92%	87%	82%	56%	65%	70%	63%	62%	63%	69%	79%	75%	80%	89%	84%	78%	61%	96%	71%	94%
85.2%		93%	90%	90%	80%	81%	86%	91%	93%	91%	90%	74%	90%	77%	88%	80%	83%	77%	70%		94%
93.3%		96%	96%	93%	89%	90%	93%	85%	93%	90%	96%	93%	94%	93%	93%	94%	97%	92%	97%	97%	95%
83.1%		87%	90%	82%	80%	78%	87%	88%	87%	91%	90%	78%	84%	78%	87%	88%	70%	73%	78%	79%	88%
84.1%		81%	92%	91%	90%	79%	91%	87%	85%	89%	87%	77%	86%	77%	90%	85%	75%	81%	77%	77%	86%
84.7%		91%	100%	99%	76%	76%	90%	98%	90%	90%	76%	76%	71%	65%	90%	90%	90%	71%	76%	90%	90%
79.8%		71%	78%	85%	94%	60%	77%	86%	83%	80%	91%	57%	87%	78%	82%	89%	82%	82%	53%	93%	88%
53.1%	50%	63%	41%	43%	41%	48%	70%	39%	35%	54%	44%	44%	44%	44%	100%	100%	41%	41%	41%	33%	100%
86.0%		94%	82%	84%	69%	92%	82%	67%	82%	85%	91%	91%	93%	89%	92%	92%	90%	90%	89%	83%	83%

Model Similarity Dendrogram

Hierarchical clustering of models based on response similarity. Models grouped closer are more similar.