DTeval

Loading analysis results...

Please wait while we prepare the detailed comparison.

Loading blueprint versions...

Please wait while we gather all the unique runs for this blueprint.

Analysis: Gd3 C10 Dtef Global Dialogues Gd3 AiConcern%3Amore Concerned Than Excited C10 - Run 5714ab8...

Global Dialogues GD3 - More concerned than excited (10 context Qs)

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

TAGS:

Instruction Following & Prompt Adherence

Factual Accuracy & Hallucination

Efficiency & Succinctness

Reasoning

Problem solving

Best Models (Coverage)

1.Grok 4
85.4%
2.GPT 5.1
84.5%
3.Claude 3.7 Sonnet
84.5%
4.GPT 5
83.4%
5.Claude Haiku 4.5
82.5%

🔀 Least Similar Models

Claude Haiku 4.5vsGPT 4.1 Nano

70.4% similarity

👯 Most Similar Models

Claude Sonnet 4.5vsClaude Sonnet 4

90.5% similarity

View Blueprint

Select Prompt:

Macro Coverage Overview

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

Pro Tip

Click on any result cell to open a detailed view.

Advanced view

Highlight best performers

Sort prompts by

Sort models by

Color Scale - Simplified View (Avg. Coverage)

Perfect

Excellent

Good

Fair

Poor

Bad

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	3rd 84.5%	5th 82.5%	11th 79.3%	8th 82.1%	12th 77.7%	15th 74.9%	9th 81.1%	7th 82.2%	6th 82.2%	10th 80.5%	17th 73.9%	21st 51.6%	14th 75.9%	20th 71.9%	4th 83.4%	2nd 84.5%	13th 77.4%	19th 72.6%	16th 74.1%	18th 73.7%	1st 85.4%
81.3%	87%	92%	83%	78%	84%	78%	84%	92%	90%	91%	70%	38%	93%	66%	86%	87%	78%	73%	84%	91%
82.7%	86%	81%	87%	90%	81%	87%	82%	89%	97%	89%	71%	16%	95%	79%	81%	90%	95%	86%	83%	89%
50.4%	59%	55%	39%	74%	59%	31%	69%	69%	59%	52%	53%	11%	11%	97%	59%	53%	47%	43%	25%	43%
90.0%	96%	75%	91%	92%	94%	85%	93%	93%	93%	95%	91%	94%	89%	81%	88%	91%	91%	91%	82%	95%
89.4%	96%	97%	97%	97%	88%	95%	95%	80%	91%	89%	83%	77%	91%	77%	95%	88%	88%	81%	92%	90%
84.3%	93%	94%	93%	93%	93%	95%	75%	78%	78%	71%	73%	99%	78%	79%	81%	92%	88%	86%	77%	70%
82.4%	84%	87%	73%	85%	71%	82%	82%	88%	87%	80%	79%	74%	87%	90%	86%	84%	85%	85%	83%	87%	72%
72.5%	81%	86%	69%	72%	63%	49%	82%	85%	84%	77%	69%	28%	85%	67%	83%	91%	83%	73%	65%	59%
79.3%	87%	84%	74%	70%	93%	68%	83%	78%	83%	83%	79%	73%	76%	68%	85%	86%	90%	62%	74%	90%
91.6%	94%	94%	94%	96%	94%	94%	92%	88%	94%	94%	82%	95%	88%	94%	90%	92%	83%	82%	94%		98%
76.8%	91%	90%	86%	85%	78%	78%	79%	82%	83%	78%	74%	83%	71%	59%	73%	79%	63%	58%	80%	67%
86.4%	86%	93%	95%	96%	91%	83%	90%	94%	90%	78%	88%	95%	79%	81%	85%	78%	88%	74%	96%	67%
79.3%	82%	73%	84%	81%	91%	89%	77%	73%	79%	79%	86%	85%	71%	85%	70%	77%	68%	80%	88%	68%
88.9%	91%	92%	90%	91%	88%	90%	89%	93%	93%	95%	90%	56%	92%	86%	95%	93%	93%	80%	95%	86%
80.9%	86%	91%	79%	87%	87%	80%	94%	93%	92%	88%	76%	8%	90%	73%	85%	91%	88%	75%	74%	80%
79.0%	81%	87%	78%	82%	83%	83%	72%	92%	86%	87%	65%	38%	86%	60%	78%	90%	85%	76%	86%	85%
53.6%	63%	75%	66%	66%	48%	46%	57%	48%	53%	50%	44%	36%	39%	37%	64%	77%	34%	60%	41%	68%
67.2%	76%	76%	69%	67%	71%	58%	64%	81%	83%	70%	50%	52%	80%	46%	69%	68%	70%	59%	75%	60%
70.0%	76%	58%	77%	73%	72%	65%	63%	68%	72%	80%	63%	56%	72%	80%	79%	80%	73%	71%	51%	72%	70%
81.2%	84%	85%	85%	83%	84%	76%	86%	75%	81%	88%	86%	72%	83%	75%	83%	83%	77%	74%	77%		86%
81.2%	84%	81%	81%	81%	84%	77%	86%	86%	87%	93%	80%	16%	92%	80%	86%	90%	86%	83%	86%	84%	83%
84.0%	85%	89%	82%	82%	91%	76%	85%	87%	88%	94%	90%	17%	92%	87%	89%	94%	90%	86%	92%	84%
80.5%	79%	80%	77%	76%	83%	81%	82%	82%	78%	83%	83%	78%	79%	81%	81%	84%	80%	77%	83%	82%
81.7%	80%	84%	82%	80%	79%	73%	84%	87%	89%	87%	82%	62%	81%	83%	87%	84%	85%	82%	86%	77%
88.2%	90%	89%	89%	87%	80%	88%	85%	89%	91%	96%	89%	55%	92%	81%	94%	96%	92%	92%	97%	91%
77.9%	82%	81%	81%	79%	85%	83%	82%	72%	80%	86%	81%	25%	76%	78%	79%	84%	87%	72%	84%	81%
74.6%	86%	84%	78%	78%	73%	65%	75%	89%	84%	82%	65%	38%	83%	61%	86%	85%	72%	65%	75%	69%
72.9%	86%	88%	69%	82%	81%	71%	79%	89%	78%	62%	55%	48%	74%	49%	94%	85%	61%	80%	60%	68%
76.6%	85%	81%	84%	88%	91%	66%	85%	72%	72%	72%	75%	66%	70%	71%	81%	77%	71%	71%	79%	76%
69.8%	85%	79%	74%	81%	71%	93%	70%	91%	77%	69%	46%	53%	78%	40%	76%	78%	50%	56%	56%	73%
77.8%	81%	79%	83%	77%	83%	82%	82%	78%	84%	83%	83%	7%	83%	81%	83%	82%	85%	72%	84%	83%
80.9%	94%	98%	85%	78%	94%	75%	83%	83%	94%	99%	100%	49%	49%	56%	99%	94%	92%	89%	68%	39%
47.6%	55%	51%	35%	69%	55%	27%	71%	65%	55%	48%	49%	7%	7%	92%	55%	55%	56%	39%	21%	39%
77.3%	91%	73%	80%	86%	95%	67%	72%	84%	78%	82%	70%	72%	75%	68%	84%	79%	80%	69%	70%	72%
79.9%	85%	86%	82%	91%	55%	79%	80%	76%	73%	74%	74%	81%	86%	85%	83%	86%	86%	74%	82%	80%
79.1%	88%	87%	94%	92%	38%	84%	89%	93%	86%	92%	69%	34%	87%	67%	82%	90%	72%	72%	67%	90%	89%
80.2%	86%	88%	82%	85%	82%	87%	88%	92%	90%	87%	72%	11%	89%	72%	89%	85%	84%	73%	77%	85%
88.4%	94%	79%	98%	95%	80%	95%	93%	93%	92%	94%	89%	65%	90%	76%	96%	94%	83%	97%	74%	91%
74.6%	87%	87%	77%	74%	86%	66%	86%	84%	80%	78%	62%	31%	82%	55%	87%	84%	75%	73%	58%	80%
77.4%	95%	90%	73%	90%	95%	63%	94%	94%	95%	87%	88%	40%	40%	67%	92%	88%	82%	77%	57%	40%
72.2%	91%	92%	87%	90%	37%	84%	94%	93%	92%	73%	60%	37%	77%	48%	93%	89%	75%	29%	67%	36%
64.6%	100%	49%	55%	57%	57%	53%	63%	57%	54%	65%	51%	52%	54%	62%	100%	100%	48%	59%	53%	67%	100%
73.1%	64%	89%	72%	73%	51%	75%	73%	61%	71%	63%	94%	89%	70%	71%	76%	81%	69%	64%	87%	69%

Model Similarity Dendrogram

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