# 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%)