Anthropic Cuts Claude Haiku 5.5 Price 75% Below Haiku 4.5
TL;DR
- The 90% price cut applies only below 100k tokens; above that threshold, rates jump 5x to $0.50/$2.50 per million input/output tokens.
- Artificial Analysis benchmarks clock Haiku 5.5 max mode at roughly 162k output tokens per task versus roughly 54k for GPT-6 Luna max, a 3x efficiency gap that compresses real-cost advantage on reasoning workloads.
- A new tokenizer generates roughly 30% more tokens per character than Haiku 4.5, narrowing effective savings further than the 75% average headline implies.
Anthropic has priced its new small model at $0.10 per million input tokens and $0.50 per million output tokens for prompts up to 100,000 tokens. On the launch page, the company says Haiku 5.5 "is priced 90% lower than Claude Haiku 4.5 for requests up to 100,000 tokens, and 50% lower for requests over 100,000 tokens," and "on average, it now costs around 75% less to run."
The pitch is narrow. Anthropic calls Haiku 5.5 "the cheapest, fastest, and most capable small model we've ever released" and tells developers it is "designed for high-volume, cost-sensitive tasks" like summaries, compactions, database queries and classification. It is also, Anthropic writes, the first Haiku-class model with an adjustable effort setting, so "users can decide whether to optimize for cost or intelligence."
The reported scores: 72.4% on OSWorld 2.1 (offline subset), 45.9% on Humanity's Last Exam without tools and 57.4% with them, and 39.2% on Terminal-Bench 4.0. Anthropic positions the model as a subagent for Opus 5.5 and Sonnet 5.5 on coding work, which fits a run of agent-shaped stories moving through our agents tracker this quarter.
Two other changes shipped in the same post. Sonnet 5.5 cache reads drop to $0.10 per million tokens from $0.20, which Anthropic says "means Sonnet 5.5 now runs around 20% cheaper on most agentic work." And paid-plan users get monthly API credits: "Max 5x users will get $100 in credits per month, Max 20x users will get $200, and Team subscribers will receive up to $500, pooled across their users."
The one customer figure Anthropic puts on the page is from Asana. "We saw over a 30% reduction in latency for task completions and up to 2.5x faster inference per agent turn," says Aaron Vinh, a Staff Software Engineer there. The launch page carries no direct comparison to OpenAI or other named competitors.
What others are reporting
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VentureBeat Read →
Adds customer validation from Box, Asana, and Rogo with specific throughput metrics; breaks down tiered pricing structure and flags the absence of tokens-per-second specs.
It's accurate enough that we'd trust it there and fast and cheap enough that we can run it a lot.
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Artificial Analysis Read →
Independent benchmark data quantifies the output-token efficiency gap versus GPT-6 Luna max and provides AA-Briefcase Elo, Terminal-Bench 4.0, and hallucination scores absent from Anthropic's release.
Haiku 5.5 (max) uses ~162k output tokens per Intelligence Index task, ~3x GPT-6 Luna (max)
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Yahoo Finance Read →
Frames the price cut as competitive necessity tied to Anthropic's pre-IPO positioning, citing $4.6B revenue against $42B in 2025 losses and a broader enterprise shift away from the tokenmaxxing era.
Haiku 5.5 costs an average of 75% less than Haiku 4.5
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AWS Machine Learning Blog Read →
First-party deployment context covering GovCloud availability, IAM and CloudTrail governance integration, and multi-region inference profiles across US, EU, AU, and JP.
Claude Haiku 5.5 is the fastest and most efficient model in the Claude 5.5 family, built for subagents and high-volume, cost-sensitive work.
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DataCamp Read →
Hands-on testing quantifies the tokenizer efficiency gap (30% more tokens than Haiku 4.5), explains the 90% vs 75% savings discrepancy, and documents the OSWorld 2.1 desktop-automation leap from 15.7% to 72.4%.
Shared on Bluesky by 3 AI experts
Originally reported by anthropic.com
Read the original article →Original headline: Anthropic Ships Claude Haiku 5.5 at 75% Lower Cost, Pairs With Sonnet Cache Cut and Max API Credits