AI
Claude Haiku 5.5
Publication: Simon Willison's Weblog
Author: Not available in collected metadata
Source published: 07/10/2026, 20:56:21 UTC
Briefing created: 19/10/2026, 01:20:23 UTC
Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 08/10/2026, 21:12:24 UTC.
Briefings
Anthropic released Claude Haiku 5.5, matching the price of OpenAI's GPT-6 Luna at $0.10/$0.50 per 100k tokens. The new model uses a less efficient tokenizer, increasing token costs by 25% for the same prompt length. While Haiku 5.5 defaults to medium reasoning and offers lower generation times, it lacks the ability to disable reasoning entirely. The release also introduced a significant API credit scheme for Max and Team subscribers, providing substantial monthly credits that offset subscription costs.
Key points
- Claude Haiku 5.5 matches the price of OpenAI's GPT-6 Luna at $0.10/$0.50 per 100,000 tokens, making it the most affordable option for workloads fitting within this token limit.
- Haiku 5.5 uses a less efficient tokenizer, resulting in approximately 25% higher token costs compared to Haiku 4.5 for identical prompts, despite offering faster generation times and defaulting to medium reasoning.
Context
Anthropic announced the release of Claude Haiku 5.5, a new fast and low-cost LLM model designed to compete with OpenAI's GPT-6 Luna. The pricing structure was adjusted to match Luna's cost per 100k tokens, though the new model incurs higher token costs due to a less generous tokenizer. This release also introduced a new API credit scheme for Max and Team subscribers, providing significant monthly credits to offset subscription costs.
Limitations
The evidence covers the release of Haiku 5.5 and its pricing/usage details but does not include information about the performance benchmarks of the new model compared to other recent models, nor does it provide data on the specific impact of the new tokenizer on different prompt lengths beyond the 100k token limit.
Generated by Bittrees-hosted qwen35-2b sha256:aaf42c8b7c3c on 19/10/2026, 01:20:23 UTC. Based on publisher-provided feed evidence; may not cover the full original article. Check the source for details.
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