Anthropic claims its new Claude Opus 5 delivers near-Fable 5 performance at half the token price
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Anthropic claims its new Claude Opus 5 delivers near-Fable 5 performance at half the token price

July 24, 202610 views2 min read

Anthropic's Claude Opus 5 achieves near-Fable 5 performance at half the token price, excelling in coding and problem-solving benchmarks.

Anthropic has unveiled its latest AI model, Claude Opus 5, claiming it delivers performance nearly on par with Fable 5—while significantly reducing costs. The company asserts that Opus 5 achieves top-tier results in coding and knowledge-intensive tasks, all at half the token price of its competitor.

Performance Benchmarking

According to Anthropic, Claude Opus 5 has posted a score of 30.2 percent on ARC-AGI-3, a challenging benchmark designed to test novel problem-solving capabilities. This performance marks a significant leap, nearly four times higher than GPT-5.6 Sol, another leading model in the field. The results suggest that Opus 5 is not only competitive but potentially superior in handling complex reasoning tasks.

Cost Efficiency Advantage

One of the most compelling aspects of Claude Opus 5 is its cost-effectiveness. By halving the token rate compared to Fable 5, Anthropic positions its model as an attractive option for enterprises and developers looking to maximize performance without incurring excessive costs. This efficiency could be a game-changer in an industry where computational expenses are rapidly escalating.

Implications for the AI Landscape

With this latest development, Anthropic continues to assert its leadership in the AI space, especially in the high-end model segment. As companies increasingly rely on AI for critical operations, models like Claude Opus 5 offer a compelling balance of capability and affordability. This could reshape how businesses approach AI deployment, especially in resource-intensive domains such as software development and research.

As the race for superior AI performance intensifies, Anthropic's announcement underscores the growing importance of both performance and cost-efficiency in the next generation of AI models.

Source: The Decoder

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