DTeval

A Collective Intelligence Project

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Analysis: Gd4 C10 Dtef Global Dialogues Gd4 Country%3Acanada C10 - Run f2365f0...

Global Dialogues GD4 - Canada (10 context Qs)

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

TAGS:

Global Dialogues Gd4

Instruction Following & Prompt Adherence

Factual Accuracy & Hallucination

Efficiency & Succinctness

Quantitative Analysis

Best Models (Coverage)

1.Claude Sonnet 4.5
76.6%
2.Claude Sonnet 4
76.1%
3.Claude 3.7 Sonnet
75.6%
4.GPT 4.1
74.5%
5.Claude Haiku 4.5
74.1%

🔀 Least Similar Models

Claude Sonnet 4.5vsGPT OSS 20b

74.8% similarity

👯 Most Similar Models

Claude Sonnet 4vsLlama 4 Maverick

89.3% 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		3rd 75.6%	5th 74.1%	2nd 76.1%	1st 76.6%	17th 68.8%	16th 71.2%	7th 73.7%	9th 73.3%	14th 71.6%	4th 74.5%	6th 73.8%	18th 68.5%	8th 73.5%	11th 71.9%	13th 71.6%	12th 71.8%	20th 67.8%	21st 63.9%	10th 72.4%	19th 68.3%	15th 71.4%
66.1%		77%	62%	65%	70%	68%	43%	65%	70%	68%	67%	58%	69%	64%	54%	73%	69%	69%	62%	66%	72%	78%
54.8%		63%	51%	54%	65%	74%	33%	44%	45%	58%	82%	57%	49%	74%	53%	74%	72%	38%	33%	41%		36%
72.9%		72%	72%	78%	81%	87%	73%	78%	72%	65%	70%	81%	67%	75%	71%	72%	74%	68%	67%	67%	68%	72%
65.0%		70%	67%	67%	67%	67%	64%	71%	65%	64%	71%	67%	61%	64%	66%	64%	64%	58%	59%	61%	61%	68%
64.8%		77%	72%	73%	77%	75%	54%	64%	66%	67%	65%	57%	66%	70%	58%	66%	65%	53%	53%	64%	50%	69%
76.0%		83%	80%	82%	83%	66%	78%	81%	83%	80%	76%	82%	66%	83%	82%	75%	78%	66%	52%	82%	58%	79%
60.7%		65%	75%	78%	76%	65%	56%	59%	55%	59%	55%	56%	63%	56%	52%		59%	54%	58%	52%	59%	63%
70.8%		76%	72%	76%	69%	68%	76%	76%	77%	70%	77%	72%	70%	69%	70%	71%	74%	71%	62%	55%	74%	62%
72.0%		70%	76%	62%	69%	63%	82%	74%	74%	70%	78%	79%	63%	74%	71%	70%	66%	78%	67%	69%	83%	74%
63.9%		52%	50%	67%	52%	73%	78%	70%	69%	51%	42%	64%	81%	74%	86%	47%	34%	70%	59%	77%	71%	75%
79.8%		84%	86%	84%	85%	79%	83%	76%	79%	78%	84%	84%	79%	83%	80%	80%	83%	81%	66%	79%	61%	82%
71.0%		88%	88%	85%	88%	82%	84%	64%	65%	65%	79%	81%	58%	66%	81%	81%	61%	45%	39%	63%	45%	83%
82.7%		76%	87%	76%	80%	77%	76%	72%	86%	89%	86%	84%	82%	84%	82%	92%	87%	88%	84%	79%	85%	85%
70.5%		71%	85%	82%	74%	69%	64%	73%	54%	71%	62%	68%	68%	73%	59%	77%	77%	73%	70%	71%	63%	77%
69.0%		63%	70%	73%	64%	7%	72%	78%	81%	67%	64%	78%	68%	74%	80%	68%	70%	74%	89%	88%	56%	64%
73.5%		82%	74%	78%	78%	73%	68%	78%	78%	78%	73%	79%	62%	75%	68%	80%	76%	47%	77%	67%	77%	75%
75.1%		73%	75%	73%	79%	80%	78%	71%	76%	76%	77%	76%	79%	76%	78%	68%	72%	76%	71%	76%	66%	82%
82.8%		86%	81%	79%	86%	78%	85%	81%	88%	80%	84%	76%	84%	89%	84%	84%	81%	79%	82%	86%	81%	85%
69.4%		79%	70%	79%	78%	74%	70%	70%	67%	69%	73%	73%	69%	66%	73%	64%	71%	52%	58%	66%	69%	67%
73.9%		74%	76%	66%	70%	73%	58%	78%	76%	70%	73%	76%	76%	73%	82%	79%	77%	77%	77%	76%	72%	72%
76.4%		76%	85%	81%	87%	71%	67%	77%	75%	78%	83%	77%	63%	77%	63%	84%	83%	67%	74%	80%	79%	77%
69.3%		80%	69%	73%	77%	63%	76%	69%	68%	76%	66%	73%	67%	61%	72%	71%	69%	72%	51%	69%	64%	69%
84.0%		83%	81%	91%	91%	43%	85%	91%	88%	93%	82%	69%	79%	91%	86%	87%	88%	90%	83%	89%	85%	88%
63.3%		75%	70%	73%	75%	89%	57%	64%	68%	68%	66%	57%	59%	70%	45%	48%	50%	62%	70%	54%	51%	59%
61.9%		71%	62%	59%	70%	72%	68%	78%	55%	54%	65%	63%	56%	61%	44%	71%	62%	53%	44%	58%	60%	74%
87.9%		88%	84%	92%	91%	90%	90%	86%	84%	90%	90%	90%	83%	90%	90%	85%	84%	80%	90%	90%	90%	89%
73.8%		76%	70%	71%	70%	76%	76%	73%	75%	76%	65%	76%	76%	72%	76%	72%	71%	76%	75%	76%	76%	76%
71.2%		82%	75%	74%	78%	79%	52%	82%	71%	72%	74%	75%	69%	72%	67%	73%	70%	65%	59%	67%	70%	70%
79.0%		88%	85%	91%	90%	62%	71%	83%	82%	85%	87%	88%	84%	80%	78%	83%	79%	65%	47%	80%	80%	72%
73.9%		80%	77%	81%	84%	82%	64%	70%	77%	71%	72%	66%	71%	71%	71%	75%	77%	68%	63%	75%	71%	86%
73.0%		78%	79%	79%	83%	66%	72%	80%	74%	71%	81%	74%	74%	78%	79%	83%	81%	60%	55%	84%	33%	70%
74.2%		81%	71%	62%	62%	69%	78%	71%	72%	74%	67%	84%	73%	77%	75%	81%	80%	80%	72%	80%	72%	77%
77.9%		88%	75%	76%	96%	68%	70%	74%	75%	82%	100%	70%	61%	69%	71%	84%	86%	86%	78%	68%	76%	83%
62.6%		64%	64%	67%	67%	67%	62%	69%	67%	67%	70%	66%	59%	62%	61%	71%	70%	33%	37%	56%	73%	62%
64.2%		65%	66%	77%	77%	29%	78%	73%	73%	62%	49%	54%	74%	65%	60%	59%	65%	65%	60%	70%	60%	67%
80.4%		82%	88%	89%	85%	67%	84%	89%	82%	83%	90%	84%	61%	81%	79%	80%	71%	82%	83%	89%	58%	82%
72.6%		76%	76%	75%	68%	68%	82%	64%	77%	74%	73%	85%	76%	73%	68%	70%	64%	70%	64%	69%	72%	80%
77.4%		78%	80%	78%	78%	75%	73%	71%	78%	69%	81%	72%	83%	75%	78%	81%	80%	74%	79%	85%	69%	88%
69.2%		75%	78%	74%	73%	47%	72%	74%	79%	69%	69%	77%	75%	69%	68%	58%	67%	71%	56%	74%	55%	73%
73.1%		74%	69%	69%	69%	71%	74%	61%	81%	71%	71%	73%	76%	65%	74%	77%	75%	68%	81%	91%	65%	81%
75.3%		78%	79%	79%	69%	52%	80%	81%	85%	64%	67%	79%	72%	77%	77%	74%	73%	80%	81%	73%	81%	81%
72.6%		78%	73%	74%	74%	78%	75%	74%	72%	78%	68%	71%	75%	73%	72%	63%	76%	73%	57%	69%	75%	77%
75.9%		81%	73%	78%	78%	83%	67%	75%	75%	77%	84%	78%	67%	71%	73%	81%	75%	77%	78%	77%	74%	72%
65.3%		70%	66%	73%	75%	70%	67%	71%	76%	65%	68%	60%	64%	73%	62%	54%	50%	55%	64%	66%	67%	55%
81.0%		83%	81%	87%	88%	85%	95%	95%	91%	66%	91%	79%	71%	81%	82%	73%	85%	67%	75%	84%	71%	71%
86.4%		88%	77%	95%	91%	92%	77%	92%	90%	91%	96%	88%	73%	92%	81%	79%	88%	82%	77%	96%	92%	77%
71.4%		68%	70%	73%	70%	63%	61%	73%	66%	71%	78%	74%	58%	72%	74%	77%	71%	75%	75%	78%	69%	83%
89.8%		92%	97%	89%	74%	86%	86%	96%	96%	96%	96%	96%	96%	96%	95%	71%	71%	83%	92%	96%	90%	91%
74.6%		73%	87%	88%	79%	34%	79%	90%	71%	80%	61%	82%	77%	56%	85%	68%	67%	85%	61%	67%	88%	89%
76.2%		80%	75%	84%	88%	87%	76%	67%	67%	78%	79%	81%	77%	78%	80%	70%	80%	64%	60%	79%	79%	71%
63.6%		69%	68%	73%	72%	62%	55%	66%	66%	62%	65%	62%	62%	66%	61%	69%	62%	57%	60%	59%	51%	69%
71.4%		79%	80%	80%	81%	29%	70%	69%	62%	74%	79%	62%	62%	73%	72%	78%	80%	75%	75%	60%	69%	90%
66.6%		76%	65%	75%	72%	69%	76%	72%	61%	61%	71%	61%	66%	73%	65%	69%	64%	37%	68%	65%	58%	75%
61.1%		78%	69%	66%	67%	75%	59%	69%	64%	70%	68%	63%	63%	69%	64%	64%	50%	41%	35%	57%	42%	50%
81.2%		88%	74%	88%	88%	74%	82%	79%	82%	81%	81%	83%	84%	80%	84%	81%	73%	79%	81%	84%	76%	83%
80.0%		90%	84%	81%	82%	77%	79%	81%	85%	82%	81%	78%	76%	79%	76%	80%	82%	80%	79%	70%		79%
52.4%		55%	46%	55%	49%	83%	36%	49%	67%	57%	54%	50%	31%	55%	56%	55%	65%	51%	38%	36%	58%	54%
71.8%		74%	77%	76%	75%	71%	71%	69%	72%	67%	76%	77%	68%	69%	78%	74%	74%	75%	70%	78%	46%	71%
63.2%		71%	61%	65%	80%	80%	55%	65%	65%	68%	81%	66%	47%	71%	54%	71%	74%	70%	27%	49%	46%	62%
61.4%		65%	70%	70%	71%	65%	73%	68%	70%	54%	54%	65%	57%	62%	55%	57%	51%	57%	46%	65%	57%	57%
66.0%		54%	64%	63%	68%	46%	78%	72%	70%	59%	63%	67%	68%	68%	70%	60%	64%	71%	68%	68%	72%	72%
64.0%		71%	62%	68%	68%	64%	50%	59%	72%	61%	67%	44%	62%	67%	56%	76%	72%	62%	65%	66%	68%	63%
82.4%		86%	88%	90%	89%	69%	89%	86%	89%	84%	89%	89%	81%	90%	67%	100%	91%	68%	72%	92%	38%	84%
73.9%		84%	73%	85%	84%	80%	76%	73%	73%	66%	80%	77%	72%	76%	64%	69%	76%	70%	61%	72%	75%	66%
80.4%		86%	73%	91%	92%	68%	77%	84%	76%	84%	92%	74%	57%	91%	90%	83%	91%	93%	55%	91%	50%	91%
73.0%		74%	71%	77%	77%	62%	77%	78%	76%	71%	77%	81%	77%	77%	79%	76%	72%	79%	25%	79%	72%	75%
73.5%		81%	81%	81%	80%	76%	68%	84%	73%	60%	80%	77%	68%	80%	68%	73%	77%	69%	59%	65%	71%	73%
68.1%		72%	73%	74%	74%	63%	64%	70%	55%	65%	66%	69%	54%	63%	67%	72%	71%	70%	72%	81%	67%	68%
67.0%		75%	69%	79%	78%	65%	67%	65%	60%	71%	75%	64%	53%	67%	71%	58%	58%	79%	69%	64%	62%	58%
60.8%		59%	55%	55%	63%	59%	51%	63%	62%	64%	65%	55%	67%	68%	62%	57%	57%	72%	54%	58%	58%	72%
76.0%		83%	80%	81%	79%	72%	77%	83%	71%	71%	90%	78%	69%	80%	74%	74%	76%	77%	47%	74%	80%	80%
75.6%		79%	78%	75%	68%	46%	85%	80%	84%	78%	75%	75%	76%	80%	80%	71%	75%	75%	72%	76%	80%	80%
74.5%		75%	70%	81%	72%	64%	79%	74%	77%	68%	77%	81%	77%	73%	79%	80%	73%	76%	75%	75%	70%	68%
69.7%		79%	75%	74%	77%	76%	59%	69%	70%	71%	77%	66%	54%	76%	77%	69%	67%	61%	64%	63%	77%	63%
67.7%		81%	69%	77%	75%	58%	67%	71%	75%	60%	75%	75%	70%	66%	64%	58%	66%	66%	52%	63%	72%	62%
69.3%		72%	69%	76%	76%	53%	77%	76%	71%	63%	61%	74%	69%	64%	72%	64%	77%	71%	67%	67%	84%	53%
78.0%		79%	82%	90%	88%	82%	87%	82%	81%	70%	77%	84%	73%	77%	81%	66%	74%	70%	67%	77%	74%	78%
78.3%		78%	78%	83%	91%	85%	66%	83%	74%	79%	85%	83%	75%	76%	81%	79%	80%	65%	56%	81%	83%	84%
75.7%		81%	80%	83%	81%	65%	83%	75%	76%	72%	75%	85%	69%	75%	73%	75%	72%	80%	72%	65%	76%	76%
85.0%		94%	86%	90%	87%	86%	86%	86%	85%	84%	89%	80%	85%	85%	83%	93%	84%	76%	82%	92%	83%	70%
62.4%		63%	65%	58%	62%	71%	58%	63%	61%	67%	64%	65%	57%	65%	66%	58%	65%	65%	50%	58%		66%
63.7%		59%	82%	73%	90%	76%	87%	60%	61%	61%	68%	79%	51%	72%	82%	38%	62%	38%	45%	77%	38%	38%
69.8%		66%	75%	74%	60%	58%	78%	68%	74%	59%	64%	76%	84%	76%	76%	70%	61%	76%	61%	79%	68%	63%
63.9%		71%	69%	74%	75%	37%	70%	68%	61%	71%	64%	69%	62%	53%	69%	59%	50%	69%	53%	61%	63%	74%
74.5%		71%	86%	82%	71%	78%	75%	78%	77%	78%	71%	78%	65%	82%	78%	82%	87%	59%	58%	78%	68%	63%
83.2%		91%	88%	91%	83%	76%	87%	83%	88%	84%	83%	84%	83%	86%	85%	78%	81%	79%	70%	88%	76%	84%
58.2%		66%	58%	68%	68%	66%	68%	61%	60%	58%	52%	65%	50%	54%	60%	48%	59%	43%	33%	67%	61%	58%
50.2%		52%	61%	57%	61%	40%	58%	48%	44%	50%	60%	57%	39%	50%	57%	48%	54%	31%	63%	55%	39%	30%
71.2%		82%	75%	83%	79%	70%	71%	74%	85%	74%	80%	75%	46%	78%	71%	73%	64%	50%	45%	77%	74%	70%
73.6%		74%	88%	78%	78%	78%	84%	100%	75%	92%	86%	75%	47%	87%	94%	47%	49%	67%	55%	78%	62%	52%
67.6%		74%	63%	66%	67%	80%	57%	72%	67%	72%	73%	73%	71%	72%	69%	69%	73%	72%	70%	66%	23%	70%
64.0%		69%	69%	66%	66%	67%	49%	60%	69%	64%	62%	64%	62%	64%	51%	72%	65%	68%	55%	67%	65%	69%
60.0%		70%	77%	64%	73%	23%	54%	42%	62%	56%	51%	46%	58%	58%	48%	60%	53%	59%	83%	89%	69%	64%
57.5%		57%	59%	67%	75%	67%	59%	62%	54%	57%	64%	59%	49%	57%	60%	53%	50%	40%	49%	61%	58%	51%
71.2%		69%	79%	82%	82%	83%	83%	85%	70%	74%	64%	70%	80%	69%	65%	63%	66%	54%	57%	76%	63%	61%
70.2%		75%	69%	73%	74%	67%	73%	64%	75%	69%	72%	69%	68%	71%	69%	75%	71%	69%	66%	69%	68%	68%
61.3%		61%	51%	67%	76%	50%	62%	57%	60%	47%	64%	72%	63%	61%	64%	75%	70%	52%	50%	58%		66%
80.6%		85%	80%	80%	85%	75%	75%	86%	85%	81%	78%	87%	75%	85%	85%	77%	85%	82%	72%	73%	85%	76%
70.1%		70%	69%	71%	74%	76%	55%	71%	75%	73%	75%	76%	65%	73%	65%	77%	77%	66%	65%	62%	73%	65%
67.0%		78%	73%	78%	61%	76%	59%	67%	61%	64%	78%	75%	56%	75%	55%	56%	62%	46%	72%	58%	73%	84%
68.5%		67%	77%	69%	64%	7%	80%	71%	69%	62%	71%	79%	73%	72%	83%	70%	73%	79%	62%	81%	70%	59%
80.0%		79%	72%	73%	78%	81%	76%	70%	86%	76%	76%	77%	82%	81%	82%	89%	89%	86%	84%	74%	82%	86%
82.6%		83%	80%	84%	83%	85%	84%	78%	87%	92%	77%	88%	84%	73%	87%	80%	84%	88%	72%	82%	82%	81%
85.7%		89%	91%	89%	91%	83%	79%	89%	91%	87%	89%	95%	74%	95%	93%	79%	77%	93%	74%	95%	59%	88%
72.4%		78%	77%	81%	91%	79%	74%	74%	72%	76%	80%	75%	75%	77%	79%	66%	65%	51%	52%	70%	75%	54%
76.8%		81%	61%	67%	75%	59%	68%	86%	74%	90%	87%	84%	78%	85%	87%	84%	85%	76%	64%	67%	73%	81%
77.7%		71%	84%	80%	78%	56%	68%	77%	86%	81%	78%	83%	61%	80%	85%	83%	90%	84%	80%	74%	85%	67%
67.3%		82%	68%	68%	76%	82%	42%	68%	68%	72%	94%	67%	62%	80%	64%	84%	84%	37%	45%	59%	72%	39%
74.9%		80%	81%	78%	71%	78%	82%	83%	82%	78%	82%	81%	79%	73%	74%	61%	75%	68%	52%	79%	65%	71%
81.1%		86%	83%	82%	92%	90%	80%	77%	80%	79%	100%	79%	68%	77%	75%	84%	82%	81%	80%	78%	77%	74%
63.4%		62%	65%	74%	68%	68%	70%	65%	67%	61%	68%	64%	64%	59%	56%	65%	63%	52%	57%	63%	61%	59%
66.1%		57%	65%	66%	63%	72%	70%	71%	69%	65%	67%	70%	68%	69%	67%	61%	58%	61%	57%	72%	71%	69%
82.0%		85%	82%	79%	91%	79%	68%	80%	83%	75%	79%	85%	90%	85%	69%	85%	88%	79%	80%	85%	85%	90%
81.5%		79%	88%	87%	87%	68%	84%	87%	85%	81%	87%	90%	75%	84%	73%	77%	88%	84%	65%	83%	75%	84%
80.9%		85%	86%	84%	83%	80%	75%	83%	83%	85%	83%	83%	75%	85%	73%	80%	83%	78%	74%	89%	80%	71%
80.7%		80%	84%	85%	80%	88%	91%	90%	75%	67%	76%	89%	88%	79%	88%	67%	78%	61%	87%	81%	86%	74%

Model Similarity Dendrogram

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