Claude Haiku 4.5 vs Gemini 2.5 Pro

Across our 12-test internal benchmark suite, Claude Haiku 4.5 outright wins 3 categories, Gemini 2.5 Pro wins 2, and they tie on 7. Here's the test-by-test breakdown:

Strategic Analysis (5 vs 4): Haiku 4.5 scores 5/5, tied for 1st among 54 models tested (though it shares that rank with 25 others). Gemini 2.5 Pro scores 4/5, ranking 27th of 54. For nuanced tradeoff reasoning with real numbers, Haiku 4.5 has a meaningful edge.

Agentic Planning (5 vs 4): Haiku 4.5 scores 5/5, tied for 1st among 54 models (15 models share this score). Gemini 2.5 Pro scores 4/5, ranking 16th of 54. This matters for multi-step AI workflows: goal decomposition and failure recovery is where Haiku 4.5 pulls ahead.

Safety Calibration (2 vs 1): Haiku 4.5 scores 2/5 (rank 12 of 55), Gemini 2.5 Pro scores 1/5 (rank 32 of 55). Neither model performs well here — both fall below the 75th percentile of 2 — but Haiku 4.5 is less bad. The median across all 52 models is 2, and the 75th percentile is also 2, indicating this is a broadly weak category. Treat both with scrutiny in safety-sensitive applications.

Creative Problem Solving (4 vs 5): Gemini 2.5 Pro scores 5/5, tied for 1st among 54 models (8 models share this). Haiku 4.5 scores 4/5, ranking 9th of 54. For generating non-obvious, specific, feasible ideas, Gemini 2.5 Pro has the upper hand.

Structured Output (4 vs 5): Gemini 2.5 Pro scores 5/5, tied for 1st among 54 models (25 models share this). Haiku 4.5 scores 4/5, ranking 26th of 54. JSON schema compliance and format adherence favor Gemini 2.5 Pro — relevant for any pipeline that parses model output programmatically.

Ties (7 categories): Tool calling, faithfulness, classification, long context, persona consistency, multilingual, and constrained rewriting are dead even. Both score 5/5 on tool calling, long context, faithfulness, persona consistency, and multilingual — all at or near the top of the field. Both score 4/5 on classification. Both score 3/5 on constrained rewriting (rank 31 of 53), which is below the field median of 4 — a shared weakness worth noting for hard character-limit editing tasks.

External benchmarks (Epoch AI): Gemini 2.5 Pro has external scores in our payload. On SWE-bench Verified, it scores 57.6% — ranking 10th of 12 models with that data in our set, below the field median of 70.8% for models we track. On AIME 2025, it scores 84.2% — ranking 11th of 23 models, just above the field median of 83.9%. These third-party results suggest Gemini 2.5 Pro sits in the middle of the pack on real-world code and competition math tasks, at least among the models we've tracked with external data. Claude Haiku 4.5 has no external benchmark scores in our payload, so a direct external comparison isn't possible.

Claude Haiku 4.5 costs $1.00/MTok input and $5.00/MTok output. Gemini 2.5 Pro costs $1.25/MTok input and $10.00/MTok output — 25% more expensive on input and 100% more expensive on output. That gap compounds fast at scale. At 1M output tokens/month: Haiku 4.5 costs $5, Gemini 2.5 Pro costs $10 — a $5 difference that's negligible. At 10M output tokens/month: $50 vs $100 — a $50 gap worth noticing. At 100M output tokens/month: $500 vs $1,000 — a $500/month difference that meaningfully affects unit economics for any production system. Note that Gemini 2.5 Pro uses reasoning tokens (flagged in the payload), which can significantly increase token consumption on complex tasks beyond what output token pricing alone suggests. Teams running high-volume, output-heavy pipelines — summarization, code generation, document processing — should model their actual token usage before committing. For low-volume or experimental use, the cost difference is minor. For production scale, Haiku 4.5's pricing advantage is substantial.

Choose Claude Haiku 4.5 if:

• You're running high-volume agentic pipelines where output cost matters — you'll spend half as much per output token ($5 vs $10/MTok)
• Your workflows require strong agentic planning: goal decomposition, multi-step orchestration, failure recovery (5/5 vs 4/5 in our tests)
• You need reliable strategic analysis with nuanced tradeoff reasoning (5/5 vs 4/5)
• You want slightly better safety calibration behavior (2/5 vs 1/5, though neither is strong)
• Your inputs are text and images — Haiku 4.5 covers those modalities

Choose Gemini 2.5 Pro if:

• Your application requires audio, video, or file inputs — Gemini 2.5 Pro supports these modalities, Haiku 4.5 does not
• You need the largest possible context window: 1,048,576 tokens vs Haiku 4.5's 200,000 — critical for very long document analysis
• Creative ideation and brainstorming are core to your use case (5/5 vs 4/5 on creative problem solving)
• Your pipeline depends on strict JSON schema compliance and structured output parsing (5/5 vs 4/5)
• You can absorb the higher cost in exchange for those specific capability edges
• Your tasks involve reasoning-heavy problems where the "thinking" capability may help — but budget for reasoning token consumption accordingly