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Haiku 5.5 Benchmark
Source-checked Haiku 5.5 Benchmark data: launch scores, price bands and published limits, with configuration and retrieval dates for every figure.
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Why This Haiku 5.5 Benchmark Breakdown Matters
Launch results, price tiers and per-effort costs, each recorded alongside the configuration it came from and its retrieval date.
- What the Launch Figures Really CaptureElo, partial-credit, coding and accuracy numbers sit on incompatible scales, so averaging them together means nothing.
- Small-Model Pricing for High-Volume WorkDesigned for extraction, classification and summarization tasks that run thousands of times over.
- Two Caveats That Reshape the Score TablesDiscount rates stop at 100K tokens, and the 72.4% computer-use figure is partial credit rather than a strict pass rate.
Reading the Haiku 5.5 Benchmark in Three Steps
A three-step method for converting published Haiku 5.5 benchmark numbers into a real workload decision.
Haiku 5.5 Benchmark: What the Numbers Show
Specifications, price tiers, coding outcomes, computer-use scores and third-party index data for Claude Haiku 5.5, all drawn from published sources.
Context Window and Output Ceiling
Inputs accept text plus images while output stays text, with adaptive thinking switched on. One million tokens of context and a 128,000-token output cap dwarf Haiku 4.5's 200,000 and 64,000.
Two Price Tiers Split by Prompt Length
Cross 100,000 prompt tokens and input, output and caching each move to a tier five times the cheap one. OpenAI's base Standard tier stretches to 272,000 input tokens.
Terminal-Bench 4.0 Completed Work
Haiku's 39.2% launch result clearly beats Luna yet stays below the published Sol rows. Task runs allow an eight-hour agent timeout, and 2.1 or 3.0 figures belong to an older experiment.
FrontierCode Mergeability and Cost per Effort
Grading spans correctness, tests, scope, style and repo conventions. Haiku reaches 46.4% at max effort and 41.6% at medium for $0.13 per rollout, while xhigh to max doubles spend for half a point.
OSWorld 2.1: Partial Credit vs Strict Pass
Eighty-two offline tasks, five attempts each, 1080p screenshots and a 500-step ceiling define the run. For a workflow that must finish, the 37.1% strict rate is the honest figure.
Third-Party Index Scores and Tool Gains
Artificial Analysis lists Haiku across all five efforts on Intelligence Index v4.3.2 with rounded task costs. HLE reads 45.9% without tools and 57.4% with them — a gain from the surrounding system.
Haiku 5.5 Benchmark: Frequently Asked Questions
Answers to common questions about Claude Haiku 5.5 benchmark scores, pricing tiers and published limits.
How does Haiku 5.5 stack up against GPT-6 Luna and GPT-6 Sol?
Across knowledge work, screenshot tasks and narrow coding, Haiku trades blows with Luna. Sol and Sol 6.1 charge more and earn it on coding, while Sonnet 5.5 still leads on most rows.
Why doesn't the 72.4% computer-use score equal a success rate?
The same run reports only 37.1% once every checkpoint must be satisfied. An agent can locate and edit the right file, then save it in the wrong format or stop before the final action. Add an end-state check.
At what point does Haiku 5.5 move to its higher price tier?
Only prompts up to 100,000 tokens receive the cheapest rates; beyond that, every category costs five times more. Anthropic's 90%, 50% and ~75% savings figures compare different baselines.
Can Haiku 5.5 run locally, and how much GPU memory would that require?
No parameter count, active-parameter figure, layer count or training compute is disclosed in the published specs. 'Small' describes a product tier, not an architecture, so local GPU estimates have no basis.
Does more reasoning effort always produce better results?
Not always. Sol 6.1 scores better at medium than at max, and Haiku's 0.2-point edge over Sonnet at max is too small to call a win. Extra effort brings more tokens, latency and chances to drift off task.
Why do identical models show different numbers across tables?
Sonnet reads 70.6% in Anthropic's launch table and 61.8% on the public leaderboard snapshot, where Haiku had no visible row. Artificial Analysis dropped its 'Default Fallback' label, yet Anthropic's migration guide still says no server-side fallback exists.
Put the Haiku 5.5 Benchmark to Work on Your Own Tasks
Choose a single workload, set the effort level, and measure Haiku 5.5 against your own quality floor.