Claude Haiku 4.5 vs GPT-5.4 Mini

We tested 12 tasks. Wins, losses, ties (our 12-test suite):

• Claude Haiku 4.5 wins tool_calling (5 vs 4). Ranking: Haiku tied for 1st ("tied for 1st with 16 other models") while GPT-5.4 Mini ranks 18 of 54. Practical impact: Haiku is better at function selection, argument accuracy and sequencing — useful when the model must call external tools reliably.
• Claude Haiku 4.5 wins agentic_planning (5 vs 4). Ranking: Haiku tied for 1st (with 14 others) vs GPT rank 16. Impact: Haiku is stronger at goal decomposition and failure recovery in our tests.
• GPT-5.4 Mini wins structured_output (5 vs 4). Ranking: GPT tied for 1st (with 24 others) vs Haiku rank 26. Impact: GPT-5.4 Mini is superior at JSON/schema compliance and strict format adherence — important for programmatic parsing.
• GPT-5.4 Mini wins constrained_rewriting (4 vs 3). Ranking: GPT rank 6 of 53 vs Haiku rank 31. Impact: GPT-5.4 Mini handles hard character/length limits and aggressive compression more reliably. Ties (both models performed identically in our tests): strategic_analysis (5/5, both tied for 1st), creative_problem_solving (4/4, both rank 9), faithfulness (5/5, both tied for 1st), classification (4/4, both tied for 1st), long_context (5/5, both tied for 1st), safety_calibration (2/2, both rank 12), persona_consistency (5/5, both tied for 1st), multilingual (5/5, both tied for 1st). Practical meaning: on many core reasoning, long-context retrieval, multilingual, and faithfulness measures the models are equivalent in our testing. Use the two clear differentiators — tool_calling/agentic planning (Claude Haiku 4.5) vs structured-output/constrained rewriting (GPT-5.4 Mini) — to pick for specific workflows.

Token pricing (per mTok): Claude Haiku 4.5 input $1.00, output $5.00; GPT-5.4 Mini input $0.75, output $4.50. Output-only cost examples: 1M output tokens = $5,000 (Haiku) vs $4,500 (GPT) — $500 difference. 10M = $50,000 vs $45,000 — $5,000 difference. 100M = $500,000 vs $450,000 — $50,000 difference. If you also pay for inputs, add $1,000 vs $750 per 1M input tokens. Teams with high-throughput workloads (>=10M tokens/month), embedded billing constraints, or tight unit economics should prefer GPT-5.4 Mini for the 11.1% output-cost savings; teams where correct tool orchestration avoids expensive downstream failures should consider the higher cost of Claude Haiku 4.5.

Choose Claude Haiku 4.5 if: you need best-in-class tool-calling and agentic planning from our suite (score 5 vs 4), or you prefer Haiku’s behavior for orchestrating functions and recovery despite ~11% higher token output cost. Choose GPT-5.4 Mini if: you prioritize strict structured-output (JSON/schema) and constrained rewriting (scores 5 and 4), a larger context window (400k vs 200k), and lower token cost ($4.50 vs $5.00 per mTok) for high-volume production.