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Haiku 5.5 Benchmark
Check Haiku 5.5 Benchmark scores, price bands and hard limits — every figure tied to its source, config and retrieval date. No hands-on test claimed.
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What the Haiku 5.5 Benchmark Results Actually Cover
Launch scores, pricing tiers and per-effort spend, each stored alongside the configuration and the date it was pulled.
- What the Launch Scores Really CaptureElo ratings, partial credit, coding and accuracy metrics sit on different scales, so averaging them is meaningless.
- Economics of a Small Model at VolumeSuited to extraction, classification and summarisation jobs that run thousands of times over.
- Two Footnotes That Reshape the TablesLow rates apply only below 100K tokens, and the 72.4% computer-use figure is partial credit rather than a strict pass rate.
Turning the Haiku 5.5 Numbers Into a Decision
Three moves that convert published figures into a practical call for your own workload.
Haiku 5.5 Benchmark: What the Specs Show
Specs, pricing tiers, coding outcomes, computer-use results and third-party index readings for Claude Haiku 5.5.
Context Window and Output Ceiling
It takes text and images in, returns text, and runs with adaptive thinking enabled. A million-token context and a 128,000-token output limit far exceed Haiku 4.5's 200,000 and 64,000.
Two Price Bands by Prompt Length
Past 100,000 prompt tokens, input, output and caching all shift into a tier priced five times higher. OpenAI's base Standard tier extends to 272,000 input tokens.
Terminal-Bench 4.0 Finished Tasks
The 39.2% launch result clears Luna by a clear margin yet trails the published Sol entries. Runs allow an eight-hour agent timeout, while 2.1 and 3.0 scores come from an earlier experiment.
FrontierCode Mergeability and Cost per Effort
Scoring weighs correctness, tests, scope, style and repository conventions. Haiku reaches 46.4% at max effort and 41.6% at medium for $0.13 per rollout, yet going from xhigh to max doubles cost for half a point.
OSWorld 2.1: Partial Credit vs Strict Pass
The run covers 82 offline tasks, five attempts each, 1080p screenshots and a 500-step cap. When a workflow has to complete, the 37.1% strict figure is the one to trust.
Third-Party Index Scores and Tool Gains
Artificial Analysis lists Haiku across all five effort levels on Intelligence Index v4.3.2 with rounded task costs. HLE shows 45.9% bare and 57.4% with tools — a lift that comes from the surrounding system.
Haiku 5.5 Benchmark: Common Questions
Answers on Claude Haiku 5.5 results, pricing tiers and the limits that shape both.
Where does Haiku 5.5 sit next to GPT-6 Luna and GPT-6 Sol?
Across knowledge work, screenshot tasks and small coding jobs, Haiku matches Luna blow for blow. Sol and Sol 6.1 charge more and justify it on coding, yet Sonnet 5.5 still tops most rows.
Why isn't the 72.4% computer-use figure a success rate?
Require every checkpoint and the same run drops to 37.1%. An agent may find and edit the right file, then save it in the wrong format or halt before the final action — so add an end-state check.
At what point does Haiku 5.5 move into the pricier band?
The lowest rates apply only up to 100,000 prompt tokens; beyond that every category costs five times as much. Anthropic's 90%, 50% and ~75% savings claims rest on different baselines.
Could Haiku 5.5 run locally, and how much GPU memory would that take?
The published specs give no parameter count, active-parameter figure, layer count or training compute. 'Small' describes a product tier rather than an architecture, so any local GPU estimate has nothing to stand on.
Does more reasoning effort always produce better results?
No. Sol 6.1 actually scores higher at medium than at max, and Haiku's 0.2-point lead over Sonnet at max is too slim to count as a win. More effort means more tokens, more latency and more room to wander off task.
Why do identical models post different numbers across tables?
Sonnet shows 70.6% in Anthropic's launch table but 61.8% on the public leaderboard snapshot, where Haiku had no visible row. Artificial Analysis removed its 'Default Fallback' tag, while Anthropic's migration guide still states no server-side fallback exists.
Put the Haiku 5.5 Benchmark Up Against Your Own Workload
Choose a single workload, set the effort level, and see whether Haiku 5.5 clears the quality bar you already use.