Summary

This analysis evaluates eight AI models tasked with listing Gruffalo characters in order of appearance. claude-opus-4.5 emerges as the winner, delivering perfect accuracy across all four runs with exceptional performance metrics (2.4s average, $0.000046 cost). While seven models correctly identified the five characters in proper sequence, only gemini-3-pro precisely matched the custom instruction's exact text format using "The Gruffalo." claude-sonnet-4.5 performed catastrophically, misordering characters and hallucinating non-existent ones, demonstrating a complete failure to distinguish between the original book and its sequel.

Outcome Analysis

What models produced/concluded:

Consensus: Seven models (claude-opus-4.1, claude-opus-4.5, gemini-2.5-pro, gemini-3-pro, gpt-5, grok-4, kimi-k2-thinking) correctly enumerated the five canonical characters in chronological order: Mouse, Fox, Owl, Snake, and Gruffalo. All four iterations for each of these models maintained identical output structure with zero divergence.

Key Divergences: claude-sonnet-4.5 uniquely and consistently failed by placing Gruffalo third instead of fifth and appending characters from the sequel ("Gruffalo's Child" or "Child"). This represents a fundamental misunderstanding of the source material boundary. Additionally, only gemini-3-pro consistently used the exact specified text "The Gruffalo" (with article), while most models used the simplified "Gruffalo"—a minor but notable variance from the provided correct answer.

Approach Analysis

How models tackled the problem:

Best methodology: All accurate models employed direct minimalism, outputting exactly five lines with character names and zero preamble, fulfilling the "no other text" requirement perfectly. claude-opus-4.5 was particularly clean, delivering raw output without even the conversational metadata present in some other responses.

Most problematic: claude-sonnet-4.5 inexplicably reordered the narrative sequence and introduced sequel characters, suggesting training data contamination or failure to parse the prompt's scope. Its approach was systematically wrong across all iterations, indicating a model-level misunderstanding rather than random error.

Structural differences: While most models output bare lists, gemini-2.5-pro and gemini-3-pro occasionally included conversational wrappers in their response formatting, though the core content remained correct.

Performance Table

Key Findings

Outcome:

• 🏆 Seven models achieved 100% accuracy on character order and identification
• ❌ claude-sonnet-4.5 was the sole catastrophic failure, scoring 0/4 with wrong order and hallucinated characters
• ✨ Only gemini-3-pro consistently matched the exact specified text "The Gruffalo"

Approach:

• 🏆 claude-opus-4.5 demonstrated ideal brevity: zero-waste output with perfect fidelity
• 🚨 claude-sonnet-4.5 showed systematic confusion between original and sequel content

Performance:

• ⚡ claude-opus-4.5 was 10x cheaper and 3x faster than the next-best model
• 💰 gpt-5 was 250x more expensive than claude-opus-4.5 despite equal accuracy
• 📊 grok-4 used 23x more input tokens (706) than others, suggesting inefficient prompt handling

Surprises & Outliers:

• 🚨 claude-sonnet-4.5 hallucinated sequel characters with high confidence across all runs, a concerning failure mode for a knowledge retrieval task
• 🤔 The "The Gruffalo" vs "Gruffalo" distinction revealed subtle interpretation differences—most models saw the article as optional, while gemini-3-pro treated it as canonical

Response Highlights

Best Response (gemini-3-pro, Run 1):

Mouse
Fox
Owl
Snake
The Gruffalo

Exact match to specified answer format, demonstrating precise instruction following.

Most Problematic (claude-sonnet-4.5, Run 4):

Mouse
Fox
Gruffalo
Owl
Snake
Gruffalo's Child

Fundamentally wrong order and hallucinated sequel character, showing complete task failure.

Most Efficient (claude-opus-4.5, any run):

Mouse
Fox
Owl
Snake
Gruffalo

Perfect accuracy with zero overhead, delivered in 1.14-2.89 seconds at minimal cost.

Ranking Justification

1st place (claude-opus-4.5): Achieved perfect accuracy across all runs with unmatched performance metrics—10x cheaper and 3x faster than competitors while maintaining high consistency and clean output format.

2nd place (claude-opus-4.1): Perfect accuracy with solid performance, though 2x slower and 36x more expensive than its 4.5 counterpart. Maintained identical, correct outputs across all iterations.

3rd place (kimi-k2-thinking): Perfect accuracy at moderate speed but surprisingly low cost ($0.001045), making it the third most cost-effective solution despite slower inference (17.68s).

4th-7th place (gemini-2.5-pro, grok-4, gemini-3-pro, gpt-5): All achieved perfect accuracy but ranked lower due to performance trade-offs. Notably, gemini-3-pro was the only model to match the exact "The Gruffalo" text consistently, while gpt-5's minor inconsistency and extreme slowness (25.31s) dragged it down despite technical correctness.

8th place (claude-sonnet-4.5): Complete failure with 0/4 accuracy, fundamentally misunderstanding both character order and source material scope. Even its fast speed (2.00s) and low cost cannot offset catastrophic outcome errors.