| # Model token distribution per project |
|
|
| Per-project, per-model total token usage with breakdown by execution outcome. Only the mean total tokens are reported. Baseline vs maximum is computed from the overall mean aggregated across all three statuses. |
|
|
| ## Global Summary (All Projects Combined) |
|
|
| ### Overall per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 1270 | 38,411 | |
| | GPT-4o-mini | 1270 | 52,051 | |
| | DeepSeek-V3.1 | 1270 | 59,788 | |
| | DeepSeek-R1 | 1270 | 72,750 | |
| | Gemini-2.5 | 1270 | 53,359 | |
| | Gemini-2.5-NT | 1270 | 38,578 | |
| | Qwen3-235b | 1270 | 39,751 | |
|
|
| ### Baseline vs maximum (Overall per-model total tokens) |
| - Baseline (lowest mean): GPT-5 = 38,411 tokens |
| - Maximum (highest mean): DeepSeek-R1 = 72,750 tokens |
| - Delta: 34,340 (89.4%) |
|
|
| ## Series Aggregates (Aggregated by Base Task) |
|
|
| ### Series: BookWriter |
|
|
| #### Aggregated tokens for BookWriter |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 180 | 163,074 | |
| | GPT-4o-mini | 180 | 125,190 | |
| | DeepSeek-V3.1 | 180 | 199,265 | |
| | DeepSeek-R1 | 180 | 169,089 | |
| | Gemini-2.5 | 180 | 102,955 | |
| | Gemini-2.5-NT | 180 | 78,207 | |
| | Qwen3-235b | 180 | 101,878 | |
|
|
| #### Baseline vs maximum (Aggregated tokens for BookWriter) |
| - Baseline (lowest mean): Gemini-2.5-NT = 78,207 tokens |
| - Maximum (highest mean): DeepSeek-V3.1 = 199,265 tokens |
| - Delta: 121,058 (154.8%) |
|
|
| ### Series: EmailResponder |
|
|
| #### Aggregated tokens for EmailResponder |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 200 | 6,232 | |
| | GPT-4o-mini | 200 | 8,741 | |
| | DeepSeek-V3.1 | 200 | 8,506 | |
| | DeepSeek-R1 | 200 | 16,192 | |
| | Gemini-2.5 | 200 | 36,628 | |
| | Gemini-2.5-NT | 200 | 38,777 | |
| | Qwen3-235b | 200 | 6,667 | |
|
|
| #### Baseline vs maximum (Aggregated tokens for EmailResponder) |
| - Baseline (lowest mean): GPT-5 = 6,232 tokens |
| - Maximum (highest mean): Gemini-2.5-NT = 38,777 tokens |
| - Delta: 32,545 (522.2%) |
|
|
| ### Series: GameBuilder |
|
|
| #### Aggregated tokens for GameBuilder |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 50 | 22,665 | |
| | GPT-4o-mini | 50 | 32,909 | |
| | DeepSeek-V3.1 | 50 | 48,315 | |
| | DeepSeek-R1 | 50 | 44,694 | |
| | Gemini-2.5 | 50 | 74,145 | |
| | Gemini-2.5-NT | 50 | 59,373 | |
| | Qwen3-235b | 50 | 24,125 | |
|
|
| #### Baseline vs maximum (Aggregated tokens for GameBuilder) |
| - Baseline (lowest mean): GPT-5 = 22,665 tokens |
| - Maximum (highest mean): Gemini-2.5 = 74,145 tokens |
| - Delta: 51,480 (227.1%) |
|
|
| ### Series: LandingPageGenerator |
|
|
| #### Aggregated tokens for LandingPageGenerator |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 180 | 17,638 | |
| | GPT-4o-mini | 180 | 27,726 | |
| | DeepSeek-V3.1 | 180 | 26,392 | |
| | DeepSeek-R1 | 180 | 38,077 | |
| | Gemini-2.5 | 180 | 31,011 | |
| | Gemini-2.5-NT | 180 | 23,734 | |
| | Qwen3-235b | 180 | 16,749 | |
|
|
| #### Baseline vs maximum (Aggregated tokens for LandingPageGenerator) |
| - Baseline (lowest mean): Qwen3-235b = 16,749 tokens |
| - Maximum (highest mean): DeepSeek-R1 = 38,077 tokens |
| - Delta: 21,328 (127.3%) |
|
|
| ### Series: MarkdownValidator |
|
|
| #### Aggregated tokens for MarkdownValidator |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 120 | 1,910 | |
| | GPT-4o-mini | 120 | 1,897 | |
| | DeepSeek-V3.1 | 120 | 2,006 | |
| | DeepSeek-R1 | 120 | 5,898 | |
| | Gemini-2.5 | 120 | 115,364 | |
| | Gemini-2.5-NT | 120 | 46,614 | |
| | Qwen3-235b | 120 | 1,924 | |
|
|
| #### Baseline vs maximum (Aggregated tokens for MarkdownValidator) |
| - Baseline (lowest mean): GPT-4o-mini = 1,897 tokens |
| - Maximum (highest mean): Gemini-2.5 = 115,364 tokens |
| - Delta: 113,466 (5980.0%) |
|
|
| ### Series: RecruitmentAssistant |
|
|
| #### Aggregated tokens for RecruitmentAssistant |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 180 | 32,358 | |
| | GPT-4o-mini | 180 | 92,274 | |
| | DeepSeek-V3.1 | 180 | 65,486 | |
| | DeepSeek-R1 | 180 | 78,894 | |
| | Gemini-2.5 | 180 | 63,570 | |
| | Gemini-2.5-NT | 180 | 48,983 | |
| | Qwen3-235b | 180 | 86,025 | |
|
|
| #### Baseline vs maximum (Aggregated tokens for RecruitmentAssistant) |
| - Baseline (lowest mean): GPT-5 = 32,358 tokens |
| - Maximum (highest mean): GPT-4o-mini = 92,274 tokens |
| - Delta: 59,916 (185.2%) |
|
|
| ### Series: SQLAssistant |
|
|
| #### Aggregated tokens for SQLAssistant |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 180 | 11,342 | |
| | GPT-4o-mini | 180 | 18,870 | |
| | DeepSeek-V3.1 | 180 | 26,307 | |
| | DeepSeek-R1 | 180 | 82,118 | |
| | Gemini-2.5 | 180 | 25,363 | |
| | Gemini-2.5-NT | 180 | 19,757 | |
| | Qwen3-235b | 180 | 16,464 | |
|
|
| #### Baseline vs maximum (Aggregated tokens for SQLAssistant) |
| - Baseline (lowest mean): GPT-5 = 11,342 tokens |
| - Maximum (highest mean): DeepSeek-R1 = 82,118 tokens |
| - Delta: 70,776 (624.0%) |
|
|
| ### Series: SocialMediaManager |
|
|
| #### Aggregated tokens for SocialMediaManager |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 180 | 32,102 | |
| | GPT-4o-mini | 180 | 83,075 | |
| | DeepSeek-V3.1 | 180 | 80,179 | |
| | DeepSeek-R1 | 180 | 110,777 | |
| | Gemini-2.5 | 180 | 15,376 | |
| | Gemini-2.5-NT | 180 | 10,850 | |
| | Qwen3-235b | 180 | 43,954 | |
|
|
| #### Baseline vs maximum (Aggregated tokens for SocialMediaManager) |
| - Baseline (lowest mean): Gemini-2.5-NT = 10,850 tokens |
| - Maximum (highest mean): DeepSeek-R1 = 110,777 tokens |
| - Delta: 99,927 (920.9%) |
|
|
| ## Individual Project Details |
|
|
| ### BookWriter-MCP |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 60 | 190,842 | |
| | GPT-4o-mini | 60 | 133,339 | |
| | DeepSeek-V3.1 | 60 | 184,315 | |
| | DeepSeek-R1 | 60 | 190,705 | |
| | Gemini-2.5 | 60 | 107,154 | |
| | Gemini-2.5-NT | 60 | 82,546 | |
| | Qwen3-235b | 60 | 110,716 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): Gemini-2.5-NT = 82,546 tokens |
| - Maximum (highest mean): GPT-5 = 190,842 tokens |
| - Delta: 108,296 (131.2%) |
|
|
| ### BookWriter-A2A |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 60 | 181,022 | |
| | GPT-4o-mini | 60 | 139,665 | |
| | DeepSeek-V3.1 | 60 | 272,275 | |
| | DeepSeek-R1 | 60 | 186,678 | |
| | Gemini-2.5 | 60 | 110,126 | |
| | Gemini-2.5-NT | 60 | 86,249 | |
| | Qwen3-235b | 60 | 118,406 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): Gemini-2.5-NT = 86,249 tokens |
| - Maximum (highest mean): DeepSeek-V3.1 = 272,275 tokens |
| - Delta: 186,026 (215.7%) |
|
|
| ### BookWriter-H-A2A |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 60 | 117,358 | |
| | GPT-4o-mini | 60 | 102,564 | |
| | DeepSeek-V3.1 | 60 | 141,204 | |
| | DeepSeek-R1 | 60 | 129,883 | |
| | Gemini-2.5 | 60 | 91,585 | |
| | Gemini-2.5-NT | 60 | 65,826 | |
| | Qwen3-235b | 60 | 76,512 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): Gemini-2.5-NT = 65,826 tokens |
| - Maximum (highest mean): DeepSeek-V3.1 = 141,204 tokens |
| - Delta: 75,378 (114.5%) |
|
|
| ### EmailResponder |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 100 | 5,562 | |
| | GPT-4o-mini | 100 | 8,044 | |
| | DeepSeek-V3.1 | 100 | 7,431 | |
| | DeepSeek-R1 | 100 | 16,982 | |
| | Gemini-2.5 | 100 | 35,189 | |
| | Gemini-2.5-NT | 100 | 42,421 | |
| | Qwen3-235b | 100 | 5,900 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): GPT-5 = 5,562 tokens |
| - Maximum (highest mean): Gemini-2.5-NT = 42,421 tokens |
| - Delta: 36,859 (662.8%) |
|
|
| ### EmailResponder-MCP |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 100 | 6,903 | |
| | GPT-4o-mini | 100 | 9,437 | |
| | DeepSeek-V3.1 | 100 | 9,580 | |
| | DeepSeek-R1 | 100 | 15,403 | |
| | Gemini-2.5 | 100 | 38,066 | |
| | Gemini-2.5-NT | 100 | 35,133 | |
| | Qwen3-235b | 100 | 7,434 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): GPT-5 = 6,903 tokens |
| - Maximum (highest mean): Gemini-2.5 = 38,066 tokens |
| - Delta: 31,163 (451.4%) |
|
|
| ### GameBuilder |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 25 | 22,904 | |
| | GPT-4o-mini | 25 | 17,823 | |
| | DeepSeek-V3.1 | 25 | 41,341 | |
| | DeepSeek-R1 | 25 | 44,536 | |
| | Gemini-2.5 | 25 | 72,772 | |
| | Gemini-2.5-NT | 25 | 67,964 | |
| | Qwen3-235b | 25 | 24,212 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): GPT-4o-mini = 17,823 tokens |
| - Maximum (highest mean): Gemini-2.5 = 72,772 tokens |
| - Delta: 54,949 (308.3%) |
|
|
| ### GameBuilder-MCP |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 25 | 22,425 | |
| | GPT-4o-mini | 25 | 47,996 | |
| | DeepSeek-V3.1 | 25 | 55,289 | |
| | DeepSeek-R1 | 25 | 44,851 | |
| | Gemini-2.5 | 25 | 75,519 | |
| | Gemini-2.5-NT | 25 | 50,782 | |
| | Qwen3-235b | 25 | 24,039 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): GPT-5 = 22,425 tokens |
| - Maximum (highest mean): Gemini-2.5 = 75,519 tokens |
| - Delta: 53,093 (236.8%) |
|
|
| ### LandingPageGenerator-MCP |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 60 | 12,653 | |
| | GPT-4o-mini | 60 | 19,250 | |
| | DeepSeek-V3.1 | 60 | 15,866 | |
| | DeepSeek-R1 | 60 | 28,371 | |
| | Gemini-2.5 | 60 | 26,527 | |
| | Gemini-2.5-NT | 60 | 33,428 | |
| | Qwen3-235b | 60 | 14,478 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): GPT-5 = 12,653 tokens |
| - Maximum (highest mean): Gemini-2.5-NT = 33,428 tokens |
| - Delta: 20,775 (164.2%) |
|
|
| ### LandingPageGenerator-A2A |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 60 | 14,965 | |
| | GPT-4o-mini | 60 | 20,340 | |
| | DeepSeek-V3.1 | 60 | 28,814 | |
| | DeepSeek-R1 | 60 | 28,657 | |
| | Gemini-2.5 | 60 | 21,256 | |
| | Gemini-2.5-NT | 60 | 22,826 | |
| | Qwen3-235b | 60 | 18,142 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): GPT-5 = 14,965 tokens |
| - Maximum (highest mean): DeepSeek-V3.1 = 28,814 tokens |
| - Delta: 13,849 (92.5%) |
|
|
| ### LandingPageGenerator-H-A2A |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 60 | 25,296 | |
| | GPT-4o-mini | 60 | 43,589 | |
| | DeepSeek-V3.1 | 60 | 34,496 | |
| | DeepSeek-R1 | 60 | 57,203 | |
| | Gemini-2.5 | 60 | 45,250 | |
| | Gemini-2.5-NT | 60 | 14,949 | |
| | Qwen3-235b | 60 | 17,628 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): Gemini-2.5-NT = 14,949 tokens |
| - Maximum (highest mean): DeepSeek-R1 = 57,203 tokens |
| - Delta: 42,254 (282.6%) |
|
|
| ### MarkdownValidator |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 60 | 1,853 | |
| | GPT-4o-mini | 60 | 1,853 | |
| | DeepSeek-V3.1 | 60 | 1,948 | |
| | DeepSeek-R1 | 60 | 5,912 | |
| | Gemini-2.5 | 60 | 135,224 | |
| | Gemini-2.5-NT | 60 | 31,330 | |
| | Qwen3-235b | 60 | 1,854 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): GPT-5 = 1,853 tokens |
| - Maximum (highest mean): Gemini-2.5 = 135,224 tokens |
| - Delta: 133,372 (7199.5%) |
|
|
| ### MarkdownValidator-MCP |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 60 | 1,967 | |
| | GPT-4o-mini | 60 | 1,942 | |
| | DeepSeek-V3.1 | 60 | 2,063 | |
| | DeepSeek-R1 | 60 | 5,885 | |
| | Gemini-2.5 | 60 | 95,503 | |
| | Gemini-2.5-NT | 60 | 61,899 | |
| | Qwen3-235b | 60 | 1,994 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): GPT-4o-mini = 1,942 tokens |
| - Maximum (highest mean): Gemini-2.5 = 95,503 tokens |
| - Delta: 93,561 (4819.0%) |
|
|
| ### RecruitmentAssistant-MCP |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 60 | 32,411 | |
| | GPT-4o-mini | 60 | 99,933 | |
| | DeepSeek-V3.1 | 60 | 65,748 | |
| | DeepSeek-R1 | 60 | 84,686 | |
| | Gemini-2.5 | 60 | 64,864 | |
| | Gemini-2.5-NT | 60 | 54,402 | |
| | Qwen3-235b | 60 | 87,098 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): GPT-5 = 32,411 tokens |
| - Maximum (highest mean): GPT-4o-mini = 99,933 tokens |
| - Delta: 67,523 (208.3%) |
|
|
| ### RecruitmentAssistant-A2A |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 60 | 31,991 | |
| | GPT-4o-mini | 60 | 74,951 | |
| | DeepSeek-V3.1 | 60 | 65,662 | |
| | DeepSeek-R1 | 60 | 72,968 | |
| | Gemini-2.5 | 60 | 68,719 | |
| | Gemini-2.5-NT | 60 | 55,660 | |
| | Qwen3-235b | 60 | 97,717 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): GPT-5 = 31,991 tokens |
| - Maximum (highest mean): Qwen3-235b = 97,717 tokens |
| - Delta: 65,726 (205.5%) |
|
|
| ### RecruitmentAssistant-H-A2A |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 60 | 32,672 | |
| | GPT-4o-mini | 60 | 101,936 | |
| | DeepSeek-V3.1 | 60 | 65,048 | |
| | DeepSeek-R1 | 60 | 79,028 | |
| | Gemini-2.5 | 60 | 57,128 | |
| | Gemini-2.5-NT | 60 | 36,887 | |
| | Qwen3-235b | 60 | 73,259 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): GPT-5 = 32,672 tokens |
| - Maximum (highest mean): GPT-4o-mini = 101,936 tokens |
| - Delta: 69,264 (212.0%) |
|
|
| ### SQLAssistant-MCP |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 60 | 13,881 | |
| | GPT-4o-mini | 60 | 24,241 | |
| | DeepSeek-V3.1 | 60 | 25,637 | |
| | DeepSeek-R1 | 60 | 80,522 | |
| | Gemini-2.5 | 60 | 19,110 | |
| | Gemini-2.5-NT | 60 | 15,014 | |
| | Qwen3-235b | 60 | 17,232 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): GPT-5 = 13,881 tokens |
| - Maximum (highest mean): DeepSeek-R1 = 80,522 tokens |
| - Delta: 66,641 (480.1%) |
|
|
| ### SQLAssistant-A2A |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 60 | 11,189 | |
| | GPT-4o-mini | 60 | 18,635 | |
| | DeepSeek-V3.1 | 60 | 36,805 | |
| | DeepSeek-R1 | 60 | 96,469 | |
| | Gemini-2.5 | 60 | 32,531 | |
| | Gemini-2.5-NT | 60 | 25,782 | |
| | Qwen3-235b | 60 | 17,381 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): GPT-5 = 11,189 tokens |
| - Maximum (highest mean): DeepSeek-R1 = 96,469 tokens |
| - Delta: 85,280 (762.2%) |
|
|
| ### SQLAssistant-H-A2A |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 60 | 8,956 | |
| | GPT-4o-mini | 60 | 13,734 | |
| | DeepSeek-V3.1 | 60 | 16,479 | |
| | DeepSeek-R1 | 60 | 69,364 | |
| | Gemini-2.5 | 60 | 24,448 | |
| | Gemini-2.5-NT | 60 | 18,476 | |
| | Qwen3-235b | 60 | 14,779 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): GPT-5 = 8,956 tokens |
| - Maximum (highest mean): DeepSeek-R1 = 69,364 tokens |
| - Delta: 60,408 (674.5%) |
|
|
| ### SocialMediaManager-MCP |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 60 | 38,940 | |
| | GPT-4o-mini | 60 | 108,089 | |
| | DeepSeek-V3.1 | 60 | 95,721 | |
| | DeepSeek-R1 | 60 | 109,146 | |
| | Gemini-2.5 | 60 | 12,749 | |
| | Gemini-2.5-NT | 60 | 11,480 | |
| | Qwen3-235b | 60 | 46,557 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): Gemini-2.5-NT = 11,480 tokens |
| - Maximum (highest mean): DeepSeek-R1 = 109,146 tokens |
| - Delta: 97,666 (850.7%) |
|
|
| ### SocialMediaManager-A2A |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 60 | 40,570 | |
| | GPT-4o-mini | 60 | 97,814 | |
| | DeepSeek-V3.1 | 60 | 87,367 | |
| | DeepSeek-R1 | 60 | 124,960 | |
| | Gemini-2.5 | 60 | 12,955 | |
| | Gemini-2.5-NT | 60 | 11,429 | |
| | Qwen3-235b | 60 | 55,866 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): Gemini-2.5-NT = 11,429 tokens |
| - Maximum (highest mean): DeepSeek-R1 = 124,960 tokens |
| - Delta: 113,531 (993.3%) |
|
|
| ### SocialMediaManager-H-A2A |
|
|
| #### Per-model total tokens |
| | Model | n | Mean | |
| | --- | --- | --- | |
| | GPT-5 | 60 | 16,796 | |
| | GPT-4o-mini | 60 | 43,322 | |
| | DeepSeek-V3.1 | 60 | 57,449 | |
| | DeepSeek-R1 | 60 | 98,225 | |
| | Gemini-2.5 | 60 | 20,423 | |
| | Gemini-2.5-NT | 60 | 9,642 | |
| | Qwen3-235b | 60 | 29,440 | |
|
|
| #### Baseline vs maximum (Per-model total tokens) |
| - Baseline (lowest mean): Gemini-2.5-NT = 9,642 tokens |
| - Maximum (highest mean): DeepSeek-R1 = 98,225 tokens |
| - Delta: 88,583 (918.7%) |
