Anthropic's new tokenizer for Claude models (Sonnet 5, Opus 4.8, Fable 5) produces approximately 30% more tokens from the same code than the previous tokenizer while maintaining the same list price. On identical TypeScript files, Claude's new tokenizer generates 1.73 times more tokens than GPT's o200k tokenizer, making Opus 4.8's effective price approximately $7.50/$37.50 rather than the listed $5.00/$25.00. Users comparing model prices must account for tokenizer differences rather than relying on published per-token rates, as the same work costs 32% more on Claude's newer models despite identical list pricing.
Anthropic has introduced localized pricing for Claude in India, its largest market outside the United States. The company adjusted its pricing structure to reflect local purchasing power in the Indian market. This enables broader adoption of Claude's AI services among Indian developers and businesses with pricing more aligned to regional economics.
Anthropic localized Claude pricing in India, its largest market outside the U.S. The company adjusted pricing to reflect local purchasing power in the Indian market. This move makes Claude more accessible to Indian developers and businesses by aligning costs with regional economic conditions.
Anthropic extended free access to Claude Fable 5 for paid subscribers through July 19, 2026, instead of switching to pay-per-use billing today. Subscribers can allocate up to 50 percent of their weekly usage limit to Fable 5 at no additional cost during this period. The extension reflects competitive pressure from OpenAI's GPT-5.6 Sol and lower-cost alternatives, as Fable 5 consumes usage quota faster than other Claude models.
Anthropic accused Alibaba of using 25,000 fraudulent accounts to extract capabilities from Claude through unauthorized API access. The alleged extraction campaign used coordinated accounts, proxy services, and repetitive prompts to harvest reasoning, tool-use, and reinforcement-learning data that could be used to train competing models. The distinction matters because legitimate distillation of intentionally released models should remain permitted, while covert extraction through fraud should face enforcement at the access layer rather than through restrictions on open AI.
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