DTeval

A Collective Intelligence Project

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Analysis: Gd4 C10 Dtef Global Dialogues Gd4 Country%3Abrazil C10 - Run d7e682b...

Global Dialogues GD4 - Brazil (10 context Qs)

DTEF: Predict response distributions for Brazil. Source: Global Dialogues GD4 (https://github.com/collect-intel/global-dialogues)

TAGS:

Global Dialogues Gd4

Instruction Following & Prompt Adherence

Factual Accuracy & Hallucination

Efficiency & Succinctness

Social interaction

AI Safety & Robustness

Best Models (Coverage)

1.Claude Sonnet 4
76.7%
2.GPT 5.1
75.5%
3.Claude Sonnet 4.5
75.5%
4.Claude Haiku 4.5
75.1%
5.Claude 3.7 Sonnet
75.0%

🔀 Least Similar Models

Claude Sonnet 4.5vsGPT OSS 20b

75.4% similarity

👯 Most Similar Models

Mistral Large 2411vsGPT 4o

88.8% similarity

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Macro Coverage Overview

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

Pro Tip

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Color Scale - Simplified View (Avg. Coverage)

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Not Met

	Prompts vs. Models	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 4.1 Fast
Score		5th 75.0%	4th 75.1%	1st 76.7%	3rd 75.5%	19th 69.4%	17th 70.3%	9th 73.3%	10th 73.0%	13th 71.7%	11th 73.0%	8th 73.6%	20th 68.0%	6th 74.0%	14th 71.6%	7th 73.9%	2nd 75.5%	18th 69.6%	21st 67.7%	12th 72.3%	16th 70.6%	15th 71.1%
74.4%		83%	74%	81%	85%	82%	46%	65%	83%	69%	76%	62%	66%	80%	62%	79%	81%	81%	81%	69%	78%	79%
56.7%		72%	46%	56%	66%	72%	28%	48%	51%	62%	81%	59%	53%	71%	56%	68%	72%	47%	56%	45%	49%	32%
81.9%		88%	86%	86%	86%	71%	79%	83%	79%	91%	79%	88%	78%	91%	78%	82%	86%	86%	64%	73%	83%	82%
65.9%		71%	67%	69%	67%	58%	73%	61%	65%	58%	64%	69%	69%	70%	69%	63%	73%	66%	60%	63%	60%	69%
62.6%		74%	63%	69%	68%	65%	54%	64%	70%	68%	59%	58%	59%	73%	64%	59%	54%	51%	60%	61%	53%	69%
77.4%		85%	80%	85%	85%	53%	81%	78%	84%	76%	81%	87%	75%	83%	82%	70%	83%	60%	56%	81%	75%	86%
67.7%		72%	76%	81%	81%	76%	63%	74%	63%	66%	64%	62%	66%	66%	57%	69%	67%	61%	62%	66%	65%	64%
86.3%		84%	87%	90%	79%	84%	81%	86%	92%	88%	91%	92%	68%	93%	87%	92%	82%	91%	78%	89%	86%	92%
68.9%		75%	68%	85%	80%	46%	76%	77%	77%	65%	67%	50%	84%	78%	72%	81%	68%	66%	44%	71%	53%	63%
67.2%		53%	73%	61%	62%	65%	78%	62%	70%	63%	51%	46%	82%	82%	80%	46%	66%	85%	63%	85%	54%	85%
76.3%		83%	81%	81%	74%	59%	80%	76%	79%	69%	74%	80%	75%	76%	76%	78%	81%	73%	75%	78%	76%	78%
58.0%		62%	70%	65%	63%	50%	65%	60%	54%	58%	63%	67%	49%	57%	67%	53%	65%	47%	46%	66%	46%	46%
85.2%		92%	89%	91%	91%	83%	83%	84%	84%	82%	78%	86%	84%	89%	85%	90%	87%	75%	84%	82%	82%	88%
54.4%		62%	70%	73%	60%	64%	42%	56%	41%	52%	57%	57%	38%	55%	47%	67%	61%	53%	34%	53%	44%	57%
58.3%		61%	56%	53%	57%	30%	56%	63%	73%	63%	76%	53%	55%	45%	64%	68%	61%	63%	52%	56%	65%	55%
81.5%		87%	81%	79%	86%	77%	67%	84%	84%	90%	86%	82%	72%	84%	79%	84%	90%	90%	94%	64%	76%	75%
80.1%		87%	89%	87%	87%	89%	83%	79%	83%	76%	79%	81%	60%	81%	72%	79%	82%	73%	78%	82%	64%	91%
67.2%		71%	70%	79%	74%	74%	67%	78%	71%	69%	72%	73%	43%	75%	57%	64%	65%	58%	62%	71%		50%
64.0%		61%	57%	62%	69%	54%	72%	54%	52%	59%	57%	67%	64%	56%	70%	65%	75%	64%	73%	87%	50%	77%
79.5%		82%	85%	79%	82%	79%	60%	86%	80%	70%	76%	83%	79%	76%	82%	86%	83%	82%	85%	70%	82%	82%
77.9%		76%	84%	81%	79%	80%	78%	84%	78%	83%	86%	78%	53%	81%	68%	81%	80%	76%	77%	79%	73%	80%
86.0%		88%	93%	94%	88%	74%	90%	77%	96%	94%	84%	81%	88%	81%	88%	85%	92%	83%	74%	82%	86%	87%
75.9%		88%	72%	79%	84%	52%	77%	82%	80%	83%	76%	79%	58%	86%	84%	87%	90%	73%	65%	58%	61%	80%
47.4%		60%	49%	49%	47%	64%	40%	43%	50%	52%	52%	42%	41%	58%	31%	44%	43%	40%	56%	41%	52%	41%
74.7%		71%	83%	79%	75%	53%	79%	69%	76%	72%	78%	78%	84%	73%	73%	77%	78%	78%	80%	93%	58%	61%
82.3%		86%	82%	84%	90%	82%	82%	81%	71%	82%	82%	89%	82%	82%	82%	89%	72%	74%	82%	82%	82%	90%
77.7%		83%	87%	83%	82%	80%	70%	87%	78%	74%	83%	74%	66%	84%	66%	81%	79%	79%	79%	82%	66%	69%
74.9%		85%	77%	78%	81%	72%	52%	79%	75%	74%	84%	76%	70%	75%	72%	83%	76%	73%	67%	68%		80%
70.8%		67%	76%	83%	86%	71%	83%	70%	58%	66%	67%	88%	67%	56%	92%	66%	65%	61%	85%	82%	39%	59%
58.7%		64%	61%	65%	63%	61%	50%	63%	56%	59%	62%	58%	57%	64%	53%	64%	58%	51%	58%	56%	52%	57%
75.3%		78%	83%	84%	69%	72%	75%	77%	80%	84%	73%	80%	77%	76%	77%	73%	75%	65%	57%	83%	77%	67%
80.0%		78%	84%	85%	85%	75%	68%	89%	83%	75%	75%	69%	80%	82%	79%	79%	88%	80%	81%	79%	86%	79%
56.0%		69%	49%	55%	63%	64%	38%	51%	49%	60%	58%	52%	52%	52%	53%	66%	64%	52%	63%	46%	57%	62%
63.6%		64%	59%	60%	68%	86%	52%	74%	67%	74%	73%	64%	44%	67%	62%	64%	67%	46%	62%	50%	67%	65%
73.0%		62%	90%	85%	72%	39%	82%	81%	80%	68%	60%	69%	83%	78%	68%	62%	74%	74%	74%	85%	86%	62%
76.3%		84%	80%	86%	76%	76%	79%	76%	74%	78%	81%	74%	59%	81%	79%	80%	81%	62%	74%	78%	61%	84%
77.1%		69%	83%	85%	89%	84%	77%	85%	71%	77%	69%	67%	79%	87%	75%	80%	87%	78%	65%	85%	72%	55%
64.6%		65%	65%	70%	70%	74%	61%	51%	72%	56%	75%	66%	49%	56%	63%	73%	79%	71%	49%	66%	61%	64%
79.4%		79%	85%	80%	69%	83%	87%	79%	84%	82%	70%	85%	85%	84%	78%	77%	72%	72%	82%	81%	80%	74%
70.0%		76%	64%	72%	81%	80%	78%	65%	78%	10%	74%	70%	81%	64%	74%	83%	80%	71%	54%	78%	63%	75%
79.7%		80%	85%	78%	91%	79%	64%	84%	78%	86%	88%	81%	62%	85%	82%	83%	84%	77%	80%	68%	80%	79%
69.1%		74%	72%	77%	71%	71%	82%	80%	76%	74%	58%	70%	66%	63%	66%	69%	74%	47%	46%	75%	80%	61%
70.3%		79%	73%	74%	74%	69%	66%	66%	73%	72%	68%	77%	62%	64%	71%	73%	72%	71%	62%	69%	76%	66%
75.4%		78%	59%	68%	81%	79%	65%	82%	83%	76%	67%	61%	71%	87%	69%	62%	61%	93%	84%	76%	92%	89%
69.1%		71%	82%	71%	66%	79%	86%	81%	79%	68%	65%	62%	69%	61%	58%	68%	80%	55%	60%	75%	71%	45%
78.4%		67%	91%	79%	83%	76%	69%	79%	78%	72%	83%	80%	69%	81%	78%	73%	79%	78%	73%	84%	83%	92%
66.6%		72%	73%	71%	69%	72%	65%	74%	68%	67%	67%	68%	41%	69%	61%	75%	69%	50%	62%	64%	75%	67%
80.6%		86%	78%	91%	91%	63%	69%	78%	75%	75%	94%	78%	74%	85%	82%	88%	89%	93%	66%	77%	79%	82%
76.7%		74%	78%	82%	74%	64%	82%	82%	72%	80%	70%	72%	77%	71%	77%	83%	83%	80%	75%	68%	87%	80%
68.3%		78%	65%	73%	77%	66%	75%	64%	47%	61%	73%	72%	57%	64%	76%	72%	71%	68%	65%	72%	62%	77%
75.7%		80%	71%	68%	87%	80%	77%	65%	57%	65%	77%	72%	54%	73%	80%	84%	88%	77%	84%	81%	83%	87%
68.2%		80%	71%	71%	75%	73%	57%	76%	69%	77%	68%	63%	42%	65%	63%	71%	73%	80%	66%	53%	68%	71%
57.6%		69%	58%	66%	69%	70%	51%	43%	55%	50%	65%	61%	42%	60%	50%	60%	64%	50%	63%	56%	51%	57%
80.8%		75%	86%	86%	82%	57%	80%	83%	83%	83%	79%	88%	88%	87%	88%	77%	86%	80%	76%	81%	75%	76%
72.0%		76%	74%	78%	74%	69%	74%	75%	71%	75%	73%	73%	70%	67%	73%	71%	75%	67%	67%	73%	73%	65%
72.0%		77%	72%	77%	80%	81%	61%	73%	67%	78%	74%	67%	66%	66%	66%	78%	81%	74%	64%	65%	67%	77%
43.4%		53%	32%	37%	34%	72%	28%	44%	57%	41%	57%	37%	28%	53%	26%	73%	69%	42%	37%	28%	36%	27%
68.9%		69%	76%	74%	67%	69%	72%	70%	65%	64%	65%	69%	69%	64%	78%	69%	74%	72%	66%	77%	69%	48%
58.0%		67%	57%	59%	72%	85%	42%	63%	61%	66%	80%	61%	45%	69%	52%	68%	73%	31%	32%	41%	39%	55%
57.5%		49%	67%	61%	57%	54%	80%	65%	68%	48%	51%	60%	62%	60%	53%	50%	55%	57%	52%	63%	48%	47%
75.8%		74%	84%	91%	80%	45%	77%	84%	86%	77%	69%	82%	82%	78%	76%	36%	70%	82%	80%	83%	74%	82%
67.2%		69%	66%	73%	70%	69%	54%	72%	70%	63%	72%	48%	66%	69%	61%	70%	67%	66%	62%	67%	67%	90%
87.8%		84%	92%	95%	95%	84%	91%	90%	91%	100%	94%	91%	76%	95%	89%	87%	89%	72%	76%	89%	72%	92%
76.5%		83%	81%	79%	75%	87%	78%	70%	80%	73%	75%	79%	77%	79%	75%	78%	79%	67%	80%	74%	80%	57%
78.8%		86%	73%	82%	79%	93%	81%	77%	88%	84%	78%	81%	79%	83%	80%	74%	83%	69%	54%	88%	63%	79%
84.6%		86%	88%	93%	92%	62%	84%	79%	89%	72%	79%	94%	86%	92%	95%	82%	75%	90%	81%	90%	87%	80%
61.2%		59%	60%	70%	65%	43%	76%	60%	57%	48%	55%	65%	73%	59%	73%	60%	51%	60%	63%	70%	55%	63%
78.8%		85%	90%	87%	84%	69%	81%	74%	72%	81%	72%	87%	72%	80%	67%	84%	83%	81%	85%	68%	76%	76%
68.4%		68%	70%	71%	67%	66%	71%	68%	72%	72%	66%	73%	70%	69%	74%	67%	68%	57%	60%	69%	65%	73%
76.2%		69%	87%	87%	78%	63%	79%	76%	59%	62%	73%	88%	86%	74%	80%	79%	84%	68%	76%	83%	63%	86%
78.6%		79%	71%	80%	78%	65%	93%	81%	73%	75%	81%	79%	89%	81%	72%	83%	79%	80%	75%	83%	88%	65%
65.5%		61%	73%	66%	66%	39%	75%	69%	74%	59%	59%	61%	80%	73%	71%	61%	60%	73%	67%	76%	55%	58%
83.2%		94%	84%	84%	91%	84%	72%	68%	95%	88%	86%	93%	54%	93%	74%	88%	87%	94%	83%	70%	83%	83%
73.2%		74%	71%	81%	71%	83%	58%	71%	84%	85%	83%	67%	40%	79%	73%	75%	75%	76%	74%	66%	69%	82%
67.0%		75%	70%	69%	59%	63%	72%	68%	69%	53%	65%	69%	65%	70%	68%	66%	60%	66%	66%	71%	72%	72%
74.3%		77%	80%	85%	81%	55%	78%	84%	74%	79%	74%	78%	77%	77%	77%	76%	74%	81%	27%	73%	77%	76%
66.7%		65%	72%	69%	66%	53%	72%	70%	69%	66%	66%	66%	71%	71%	71%	68%	66%	64%	67%	71%	64%	54%
81.5%		76%	79%	90%	82%	71%	75%	89%	79%	84%	86%	94%	82%	82%	87%	80%	85%	72%	74%	89%	81%	74%
84.2%		93%	91%	95%	80%	47%	91%	85%	95%	74%	78%	94%	88%	95%	91%	75%	93%	74%	88%	85%	86%	71%
75.6%		71%	77%	79%	72%	85%	81%	86%	72%	76%	75%	72%	71%	68%	76%	83%	82%	70%	70%	75%	81%	65%
91.9%		81%	99%	88%	95%	96%	84%	90%	95%	93%	100%	93%	92%	94%	95%	92%	93%	93%	94%	87%	91%	85%
70.0%		70%	72%	85%	82%	76%	77%	71%	66%	71%	67%	80%	63%	75%	81%	62%	71%	55%	61%	74%	55%	55%
76.8%		75%	84%	81%	81%	55%	89%	76%	74%	68%	65%	73%	90%	79%	86%	68%	75%	71%	76%	84%	82%	81%
81.4%		86%	85%	94%	84%	74%	89%	81%	80%	85%	87%	94%	83%	74%	83%	87%	84%	79%	64%	71%	88%	58%
67.6%		56%	85%	67%	57%	71%	78%	78%	62%	78%	71%	74%	79%	60%	75%	62%	60%	52%	59%	64%	79%	52%
77.7%		86%	82%	82%	74%	59%	80%	78%	83%	73%	75%	82%	81%	80%	78%	74%	79%	78%	81%	83%	68%	75%
61.1%		60%	64%	64%	61%	56%	67%	65%	56%	63%	55%	69%	49%	55%	58%	55%	54%	74%	55%	71%	68%	64%
60.4%		60%	68%	66%	60%	51%	69%	64%	51%	63%	66%	65%	60%	56%	75%	58%	62%	54%	59%	73%	45%	44%
60.4%		68%	67%	72%	69%	76%	58%	55%	76%	58%	61%	52%	30%	66%	47%	65%	62%	47%	46%	71%	67%	55%
81.8%		82%	93%	93%	90%	90%	75%	89%	83%	81%	93%	88%	52%	87%	75%	72%	72%	76%	77%	81%	85%	83%
76.1%		86%	73%	72%	76%	81%	60%	83%	79%	82%	78%	81%	72%	76%	80%	73%	85%	49%	84%	72%	78%	78%
61.6%		58%	76%	66%	65%	65%	34%	48%	50%	49%	47%	82%	54%	62%	40%	76%	76%	73%	50%	50%	86%	86%
70.4%		80%	70%	88%	84%	45%	64%	68%	81%	76%	66%	62%	65%	64%	64%	82%	89%	61%	66%	74%	63%	67%
77.0%		80%	79%	80%	79%	79%	70%	78%	81%	77%	71%	85%	71%	83%	72%	73%	77%	77%	79%	73%	78%	75%
57.8%		50%	61%	65%	53%	62%	68%	63%	59%	59%	50%	58%	62%	58%	52%	54%	55%	49%	51%	68%	58%	58%
80.4%		71%	85%	86%	88%	87%	79%	83%	75%	79%	75%	86%	80%	77%	75%	84%	86%	81%	74%	86%	69%	82%
70.5%		71%	70%	76%	76%	49%	75%	67%	76%	68%	77%	76%	80%	77%	74%	68%	66%	69%	50%	74%	72%	69%
84.0%		89%	90%	91%	91%	59%	72%	85%	90%	91%	75%	84%	79%	90%	79%	85%	91%	92%	73%	81%	85%	91%
79.7%		89%	81%	82%	80%	77%	59%	87%	79%	91%	78%	84%	73%	82%	87%	91%	86%	70%	63%	79%	84%	72%
80.9%		82%	86%	81%	66%	94%	77%	74%	74%	72%	86%	91%	75%	91%	74%	83%	89%	73%	76%	80%	85%	89%
70.6%		81%	68%	74%	91%	38%	67%	65%	85%	61%	88%	59%	58%	73%	49%	76%	82%	94%	72%	48%	75%	78%
79.2%		83%	82%	84%	86%	83%	74%	81%	78%	79%	78%	78%	75%	74%	77%	81%	78%	78%	80%	75%	82%	78%
73.5%		83%	81%	73%	80%	81%	77%	72%	72%	81%	65%	77%	81%	56%	71%	74%	74%	58%	60%	81%	67%	79%
71.8%		73%	73%	68%	70%	80%	59%	73%	67%	80%	77%	77%	58%	75%	74%	68%	71%	75%	84%	75%	58%	72%
74.4%		69%	73%	72%	73%	69%	83%	74%	68%	74%	71%	86%	80%	71%	86%	69%	66%	69%	82%	88%	84%	55%
72.6%		66%	74%	83%	83%	37%	52%	83%	68%	70%	76%	84%	66%	82%	66%	85%	85%	78%	56%	59%	86%	85%
69.2%		95%	76%	62%	74%	84%	39%	60%	54%	73%	87%	72%	42%	83%	60%	86%	85%	67%	55%	56%	62%	82%
72.7%		88%	65%	69%	80%	79%	50%	77%	69%	85%	85%	78%	64%	82%	72%	87%	86%	72%	66%	59%	60%	54%
72.2%		76%	71%	74%	73%	72%	72%	78%	70%	74%	77%	75%	75%	66%	68%	71%	77%	75%	64%	72%	70%	66%
82.7%		81%	88%	87%	77%	67%	79%	83%	88%	89%	79%	89%	89%	82%	81%	88%	88%	81%	81%	79%	79%	81%
67.6%		63%	66%	74%	75%	73%	72%	67%	69%	60%	74%	57%	68%	68%	57%	71%	65%	61%	73%	71%	67%	69%
73.6%		68%	77%	72%	66%	78%	74%	72%	76%	72%	72%	72%	79%	78%	78%	75%	81%	66%	73%	79%	67%	71%
82.0%		91%	76%	78%	82%	82%	73%	86%	98%	78%	81%	82%	82%	82%	82%	80%	83%	77%	87%	82%	79%	82%
78.1%		85%	83%	84%	74%	60%	85%	79%	84%	78%	75%	76%	76%	82%	78%	85%	79%	68%	68%	79%	88%	74%
74.0%		70%	66%	77%	77%	91%	75%	77%	71%	79%	76%	70%	63%	67%	76%	83%	81%	75%	55%	64%	80%	82%
71.6%		65%	68%	72%	59%	70%	84%	66%	59%	59%	59%	77%	72%	73%	79%	77%	77%	74%	77%	71%	85%	80%

Model Similarity Dendrogram

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