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Haiku 5.5 Benchmark
Claude Haiku 5.5 Benchmark figures, pulled from published evaluations — launch scores, price bands and hard limits, each tied to its source.
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Why These Haiku 5.5 Benchmark Figures Matter
Launch-day results, pricing tiers and per-effort spend, all stored alongside the exact configuration and the date each figure was pulled.
- How the Launch Scores Are MeasuredElo, partial-credit, coding and accuracy scores sit on incompatible scales, so averaging them together is meaningless.
- Low-Cost Economics for High-Volume JobsDesigned for extraction, classification and summarisation loops that run thousands of times a day.
- Two Footnotes That Rewrite the Score TablesDiscount pricing ends at 100K tokens, and the 72.4% computer-use figure is partial credit rather than a pass rate.
Putting Haiku 5.5 Benchmark Numbers to Work
A three-step method for translating published figures into a real workload decision.
What the Haiku 5.5 Benchmark Data Shows
Specs, pricing tiers, coding outcomes, computer-use figures and third-party index scores — the substance behind every Claude Haiku 5.5 claim.
Context Window and Output Ceiling
Text-and-image input, text output, adaptive thinking enabled. A one-million-token context and a 128,000-token output cap make Haiku 4.5's 200,000 and 64,000 look modest.
Pricing Splits at the 100K Prompt Mark
Once a prompt passes 100,000 tokens, input, output and caching all move to a tier five times the cheap rate. OpenAI's base Standard tier, by contrast, reaches 272,000 input tokens.
Terminal-Bench 4.0: Finished Task Runs
The 39.2% launch number clears Luna with room to spare yet trails the published Sol rows. Each run allows an eight-hour agent timeout, and figures labelled 2.1 or 3.0 come from an earlier experiment.
FrontierCode: Mergeability and Cost per Effort Level
Scoring weighs correctness, tests, scope, style and repository conventions. Max effort returns 46.4% and medium 41.6% at $0.13 per rollout, while climbing from xhigh to max doubles spend for half a point.
OSWorld 2.1: Partial Credit vs Strict Pass
The run covers 82 offline tasks with five attempts each, 1080p screenshots and a 500-step cap. When a workflow has to complete end to end, 37.1% under strict scoring is the figure to trust.
Third-Party Index Scores and Tool Gains
Artificial Analysis lists Haiku at all five effort levels on Intelligence Index v4.3.2, with rounded per-task costs. HLE scores 45.9% unaided and 57.4% with tools — an uplift that comes from the surrounding system.
Haiku 5.5 Benchmark: Questions Answered
Straight answers on Claude Haiku 5.5 scores, pricing bands and hard limits.
How does Claude Haiku 5.5 stack up against GPT-6 Luna and Sol?
Across knowledge work, screenshot handling and narrow coding, Haiku and Luna trade wins. Sol and Sol 6.1 charge more and justify it on coding, and Sonnet 5.5 still tops most rows.
Why doesn't the 72.4% computer-use figure count as a success rate?
Demand every checkpoint and the same run drops to 37.1%. An agent may find and edit the correct file, then save it in the wrong format or quit before the final step. Add an end-state check to catch that.
At what point does Claude Haiku 5.5 move to the higher price band?
The cheapest rates apply to prompts of up to 100,000 tokens; past that line, every category costs five times more. Anthropic's 90%, 50% and ~75% savings claims each measure against a different baseline.
Is local deployment of Claude Haiku 5.5 possible, and how much GPU memory would it 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 rests on nothing.
Do higher reasoning-effort settings always pay off?
No. Sol 6.1 scores higher at medium than at max, and Haiku's 0.2-point lead over Sonnet at max is too thin to count as a win. More effort buys more tokens, more latency and more chances to drift off task.
Why do identical models post different numbers in different tables?
Sonnet shows 70.6% in Anthropic's launch table but 61.8% on the public leaderboard snapshot, where Haiku had no visible row at all. Artificial Analysis removed its 'Default Fallback' tag, while Anthropic's migration guide still states that no server-side fallback exists.
Run the Haiku 5.5 Benchmark Against Your Own Tasks
Choose a single task, fix the effort level, and see whether Haiku 5.5 clears the quality bar you actually need.