Anthropic releases Claude Opus 4.7 Fast with 6x pricing for higher output speed
Anthropic has released Claude Opus 4.7 Fast, a speed-optimized variant of its Opus 4.7 model. The fast-mode version delivers identical capabilities with higher output speed at premium pricing: $30 per 1M input tokens and $150 per 1M output tokens, representing a 6x increase over standard pricing.
Claude Opus 4.7 (Fast) — Quick Specs
Anthropic Releases Claude Opus 4.7 Fast with 6x Pricing for Higher Output Speed
Anthropic has released Claude Opus 4.7 Fast, a speed-optimized variant of its Opus 4.7 model that prioritizes output speed over cost efficiency.
Pricing and Specifications
The fast-mode variant is priced at:
- Input: $30 per 1M tokens
- Output: $150 per 1M tokens
- Context window: 1 million tokens
According to OpenRouter's listing, this represents a 6x premium over standard Opus 4.7 pricing.
Technical Details
Claude Opus 4.7 Fast maintains identical capabilities to the standard Opus 4.7 model. The only difference is the prioritization of higher output speed, allowing for faster token generation at the expense of increased cost per token.
The model is available through OpenRouter's API, which routes requests to available providers and normalizes requests and responses across different endpoints. OpenRouter supports reasoning-enabled functionality, allowing the model to show step-by-step thinking processes through the reasoning parameter.
Availability
The model is currently accessible through OpenRouter's platform at https://openrouter.ai/models/anthropic/claude-opus-4.7-fast. According to the listing, there is not yet enough usage data to display activity statistics or uptime metrics.
What This Means
This release follows the broader industry trend of offering speed tiers for the same underlying model capabilities. The 6x pricing premium indicates Anthropic is targeting use cases where latency matters more than cost—likely real-time applications, interactive chat interfaces, or production systems where user experience depends on response speed. The 1M token context window matches other recent long-context releases, suggesting this is now table stakes for frontier models. However, the lack of benchmark scores or independent verification makes it unclear whether "fast mode" achieves meaningful latency improvements or simply prioritizes certain requests in Anthropic's inference queue.
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