aiprompt.fyi
Student

I Audited Sam Altman's Public Prompt — V-Index 2.1 ☠️

How a 142-token CEO prompt burns $0.84 per call when it should cost $0.06.

V-Index Transformation
Before
2.1
+6.6
Delta
After
8.7
Original prompt · V-Index 2.1

Write me a comprehensive analysis of the current state of artificial intelligence including all major companies, their products, market positioning, technical capabilities, recent announcements, regulatory concerns, and what you think will happen next year — be thorough and don't leave anything out.

Audited rewrite · V-Index 8.7

Summarise the 2026 frontier-LLM landscape in 5 bullets: (1) GPT-5 vs Claude 4.6 vs Gemini 3 Ultra positioning, (2) one regulatory headline per region (US, EU, China), (3) the single biggest open question for Q3. Max 180 words. No preamble.

Auditor's diagnosis

Vague scope, no token budget, no output structure. Routed to GPT-5 it consumes 4× the necessary tokens and triggers Claude's verbosity penalty. The rewrite caps tokens, demands structure, and forces the model into a comparison frame — V-Index jumps from 2.1 to 8.7.

Live audit of the rewrite
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Audit Report

Ref · 2026-08-05
Best Value · Winning Model
DeepSeek V3.2
V-Index
28.93
DeepSeek · 60 tokens · $0.000017 on this prompt
Best V-Index
28.93
DeepSeek V3.2 · DeepSeek
Detected Task · Tokens
summarization
60 tokens · $0.000017 on best value
CO₂ · This Prompt
54.0 mg
On DeepSeek V3.2 · est. grams of CO₂
Hallucination Risk
Low
On DeepSeek V3.2 for this task

Leading LLMs · This Prompt

8 compared
  • DeepSeek V3.2Best Value
    DeepSeek
    V-Index
    28.93
    Cost
    $0.000017
    CO₂
    54.0 mg
    Quality
    8.1
    Accuracy
    High
  • Qwen 3 Max
    Alibaba
    V-Index
    20.50
    Cost
    $0.000024
    CO₂
    90.0 mg
    Quality
    8.2
    Accuracy
    High
  • Llama 4 Maverick
    Meta
    V-Index
    16.60
    Cost
    $0.000030
    CO₂
    72.0 mg
    Quality
    8.3
    Accuracy
    High
  • Gemini 3 Ultra
    Google
    V-Index
    5.93
    Cost
    $0.000090
    CO₂
    228.0 mg
    Quality
    8.9
    Accuracy
    High
  • Mistral Large 3
    Mistral
    V-Index
    4.72
    Cost
    $0.000108
    CO₂
    210.0 mg
    Quality
    8.5
    Accuracy
    High
  • Grok 4.20
    xAI
    V-Index
    4.20
    Cost
    $0.000120
    CO₂
    240.0 mg
    Quality
    8.4
    Accuracy
    Medium
  • GPT-5
    OpenAI
    V-Index
    3.68
    Cost
    $0.000150
    CO₂
    270.0 mg
    Quality
    9.2
    Accuracy
    High
  • Claude 4.6
    Anthropic
    V-Index
    3.13
    Cost
    $0.000180
    CO₂
    312.0 mg
    Quality
    9.4
    Accuracy
    High

V-Index = Quality (1–10) ÷ $/1M tokens · higher is better.Accuracy reflects model reliability for the detected task type. Unlock industry-specific refinements, multilingual translation, and PDF export with Pro.

Total CO₂ Footprint · This Query
Total (all models)
1.48 g
Average / model
184.5 mg
Greenest
54.0 mg
DeepSeek V3.2
Heaviest
312.0 mg
Claude 4.6

Switching from Claude 4.6 to DeepSeek V3.2 on this prompt cuts 258.0 mg of CO₂ (83% reduction). Estimates based on model size and disclosed energy mix.

Summary. For this summarization prompt (60 tokens), DeepSeek V3.2 wins on value with a V-Index of 28.93. Quality leader: Claude 4.6. Cheapest viable: DeepSeek V3.2.

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