Claude Haiku 4.5 vs Gemini 2.5 Flash Lite for Classification

What Classification demands: Accurate categorization and routing, consistent adherence to schemas, correct selection of labels or destinations, and predictable behavior on edge cases. Key LLM capabilities that matter: structured_output compliance (JSON/schema), tool_calling for routing or integration, faithfulness to source text, multilingual handling, and reasoning for multi-rule decisions. In our testing (internal 1–5 proxies), Claude Haiku 4.5 scores 4 on Classification vs Gemini 2.5 Flash Lite's 3. Supporting signals: both models score 4 on structured_output and 5 on tool_calling and faithfulness, so basic schema compliance and routing integration are strong for both. Haiku outperforms on strategic_analysis (5 vs 3) and agentic_planning (5 vs 4), which explains its edge on nuanced routing decisions and complex multi-step classification tasks. Note: there is no external benchmark (SWE-bench/MATH/AIME) provided for this specific Classification task in the payload; our internal scores are the primary evidence.

Use cases where Claude Haiku 4.5 shines: - Complex support-ticket routing with layered business rules: Haiku (Classification 4, strategic_analysis 5, agentic_planning 5) is more likely to apply conditional rules and route correctly. - Multi-language label normalization for enterprise datasets: Haiku’s Classification 4 plus multilingual 5 reduces mislabeling. - Schema-strict APIs requiring predictable JSON outputs: Haiku and Flash Lite both score structured_output 4 and tool_calling 5, but Haiku’s higher classification score favors accuracy-critical pipelines. Use cases where Gemini 2.5 Flash Lite shines: - High-volume, low-complexity label tasks where cost and throughput matter: Flash Lite’s input_cost_per_mtok 0.1 and output_cost_per_mtok 0.4 make it far cheaper than Haiku (input 1, output 5). - Multimodal pre-filtering of audio/video/file inputs before text-only processing: Flash Lite’s modality includes text+image+file+audio+video->text, enabling direct classification of diverse asset types. Concrete score-grounded comparisons: Claude Haiku 4.5 — Classification 4, strategic_analysis 5, agentic_planning 5, output_cost_per_mtok 5. Gemini 2.5 Flash Lite — Classification 3, strategic_analysis 3, agentic_planning 4, output_cost_per_mtok 0.4. Both tie on tool_calling (5) and faithfulness (5).

For Classification, choose Claude Haiku 4.5 if you need higher routing accuracy, complex multi-rule classification, or the best task rank in our tests (Classification 4 vs 3). Choose Gemini 2.5 Flash Lite if you need a much lower-cost, high-throughput classifier that accepts audio/video/file inputs and is sufficient for simpler labeling tasks (Classification 3) — Flash Lite costs input 0.1 / output 0.4 per mTok vs Haiku input 1 / output 5 per mTok.