I Gave GPT-5.6 Sol and Claude Fable 5 The SAME 4 Prompts (Not Close)

What is the Best AI Model: Chat GPT 5.6 vs. Claude Fable 5?

Introduction to the Models

• The new Chat GPT 5.6 Soul model has been released alongside Claude Fable 5, prompting a comparison of their capabilities and whether users should switch models.

• Four tests will be conducted: data processing, creative writing, game development, and front-end design to determine which model performs better overall.

Performance Metrics

• In terms of raw intelligence on benchmarks, Claude Fable ranks higher at 60 compared to GPT 5.6's score of 59. However, cost per task favors GPT as it is cheaper than Fable.

• Cost per intelligence shows GPT Soul at approximately 1.04 while Claude Fable stands at about 2.75, indicating that Fable is significantly more expensive for similar tasks.

User Experience and Integration

• The integration experience with GPT is less cohesive compared to Claude’s all-in-one interface for co-work and coding tasks; this fragmentation can hinder user efficiency in some cases.

• For collaborative work environments, Chat GPT Work may outperform Co-work due to its focus on teamwork features like shared spreadsheets and task management tools.

Game Development Test Results

• A prompt was given to both models to create a playable first-person endless runner game in HTML format; results showed significant differences in execution styles between the two models.

• Claude's version (Neon Rush) demonstrated strong graphics and gameplay mechanics while GPT's approach diverged into an unexpected car-based format rather than a runner game concept requested by the prompt, leading to a less favorable outcome for GPT in this test.

Data Processing Capabilities

• A messy sales data CSV was used as input for both models with instructions to clean data and build an HTML dashboard; discrepancies arose where Claude reported $32,000 revenue versus GPT's $86,688 revenue estimate—highlighting accuracy issues between the two models' interpretations of ambiguous data entries.

• Despite differing revenue assessments, both models acknowledged that Claude had made a more accurate initial assessment regarding duplicate orders within the dataset during follow-up prompts aimed at cross-verifying their outputs against each other’s findings.

Creative Writing Comparison

• Both models were tasked with generating viral content ideas from a podcast transcript; results indicated that while they produced quality outputs close in effectiveness, there were slight preferences noted towards how each structured their ideas—GPT being favored slightly for standalone post ideas but not overwhelmingly so over Claude’s output style overall.

Front-End Design Evaluation

• A landing page design prompt yielded impressive results from both models; however, personal impressions leaned towards Fable for its refined aesthetic despite acknowledging that GPT had eye-catching elements as well.

Conclusion on Model Usage

• The speaker concludes that while Fable remains superior for complex tasks requiring strategic reasoning or writing finesse due to its smarter architecture, improvements in GPT make it suitable for implementation tasks such as agentic coding or multi-day runs.