
Claude Sonnet 5 continues Anthropic's pattern of hiding price increases behind unchanged token rates
Quick Answer
Claude Sonnet 5, ranking fifth in the AI Analysis Intelligence Index, consumes 40% more tokens per task than its predecessor, leading to hidden cost increases despite unchanged list prices from Anthropic.
Quick Take
Claude Sonnet 5, ranking fifth in the AI Analysis Intelligence Index, consumes 40% more tokens per task than its predecessor, leading to hidden cost increases despite unchanged list prices from Anthropic. This trend of concealing price hikes behind token rates is becoming a pattern for the company.
Key Points
- Claude Sonnet 5 scores 53 points in the AI Analysis Intelligence Index.
- It outperforms the more expensive Opus 4.8 in some tasks.
- The model's token consumption is 40% higher than its predecessor.
- Real costs nearly double despite unchanged list prices.
- Anthropic's pattern of hidden price increases is becoming evident.
Article Excerpt
From source RSS / original summaryClaude Sonnet 5 ranks fifth in the Artificial Analysis Intelligence Index with 53 points and even beats the pricier Opus 4. 8 on some agent-based tasks. But the model chews through about 40 percent more tokens per task than its predecessor, nearly doubling real costs despite identical list prices. Anthropic's hidden price hikes are becoming a pattern. The article Claude Sonnet 5 continues Anthropic's pattern of hiding price increases behind unchanged token rates appeared first on The Decoder.
Want this in your inbox every morning?
Daily brief at your local 8am — bilingual EN/中文, free.
More from The Decoder
See more →
An AI model programmed nonstop for 19 days on a single MirrorCode task that cost $2,600 to run
Epoch AI's MirrorCode benchmark reveals Claude Opus 4.7 as the leader with a 56% solve rate, reconstructing a 16,000-line toolkit in 14 hours. Despite this, all models tested struggle with the most complex tasks, highlighting limitations in current AI capabilities. The single task consumed $2,600 over 19 days, raising questions about cost-effectiveness in AI development.

