The gap between Anthropic’s premium and budget LLMs just narrowed significantly for routine enterprise tasks. RanThis published a benchmark on October 24, 2026, comparing Claude Haiku 5.5 and Claude Sonnet 5.5 across three specific office workflows. The results are stark: both models achieved a perfect 15/15 accuracy score on code-graded checks, yet Haiku executed the tasks 18 times cheaper and faster. This data suggests that for structured extraction and templated writing, the 'premium' tier may be overkill for many developers.

The Benchmark Methodology

The test, conducted on October 13, 2026, utilized the direct Claude API with models claude-haiku-5-5 and claude-sonnet-5-5. RanThis designed three tasks with known ground-truth answers: extracting invoice details from a messy email, calculating tiered sales commissions with specific bonus rules, and drafting a customer apology email under strict constraints. Each task was run once, and responses were graded by code rather than human judgment. The prompts were written in Vietnamese to test non-English performance, adding a layer of complexity to the standard English-centric benchmarks.

Performance and Cost Analysis

Haiku 5.5 completed all three tasks in 11.7 seconds, compared to Sonnet 5.5’s 15.7 seconds. The cost differential was even more pronounced: Haiku cost $0.00129 for the full test suite, while Sonnet cost $0.02357. This represents an 18x cost gap, slightly less than the 20x price difference listed on Anthropic’s pricing page. The discrepancy arises because Haiku used slightly more output tokens (including thinking tokens) than Sonnet in this specific run. Scaled to 1,000 runs, the cost difference balloons to approximately $1.30 for Haiku versus $23.60 for Sonnet.

Accuracy and Instruction Following

Both models nailed the factual content. In the invoice task, both correctly identified the pre-tax amount of 12,450,000 VND, ignoring a mistyped figure, and calculated the correct total of 13,446,000 VND. For the commission calculation, both correctly applied the 2%/4%/6% tiers and accurately withheld the 1 million VND bonus for a salesperson who fell 500,000 VND short of the threshold. However, both models slipped on formatting instructions: Sonnet ignored a 'No explanation' constraint, while Haiku added an unrequested company signature. These minor errors did not affect the 15/15 score but highlight that neither model is perfectly compliant with negative constraints.

Key Takeaways

  • Haiku 5.5 is viable for high-volume, structured tasks: The model matched Sonnet’s accuracy on extraction and calculation, making it a strong candidate for cost-sensitive production environments.
  • Speed is a secondary benefit: Haiku finished the test suite 4 seconds faster, a non-trivial advantage for latency-sensitive applications.
  • Long-context caveats apply: Haiku’s pricing jumps for prompts over 100,000 tokens, narrowing the cost advantage for large-document analysis.
  • Testing is essential: The RanThis team recommends writing code to verify outputs, as instruction-following flaws exist in both tiers.

The Bottom Line

For short, well-defined office tasks like extraction and rule-based calculation, Haiku 5.5 is the obvious choice, offering Sonnet-level accuracy at a fraction of the cost. Developers should default to Haiku for these workloads and only upgrade to Sonnet if their use case involves complex, multi-step reasoning or large-context analysis that this benchmark did not cover.