Claude Haiku 4.5 vs Gemini 2.5 Flash for Classification

What Classification demands: accurate categorization and routing, reliable structured outputs (schema compliance), consistent handling of long or multilingual inputs, and safe refusal/accept decisions when needed. Because no external benchmark is provided for Classification here, we rely on our internal task scores: Claude Haiku 4.5 scores 4/5 (taskScoreA) and ranks 1/52; Gemini 2.5 Flash scores 3/5 and ranks 31/52. Supporting proxies: both models tie on structured_output (4) and tool_calling (5), which matter for producing machine-readable labels and invoking downstream routers. Claude’s higher faithfulness (5 vs 4) and strategic_analysis (5 vs 3) explain its better classification accuracy in our tests — it sticks to source material and handles nuanced tradeoffs. Gemini’s stronger safety_calibration (4 vs 2) means our testing found it better at refusing or rerouting harmful/ambiguous inputs. Cost and modality differ: Gemini is cheaper ($0.3/$2.5 vs $1/$5) and supports wider multimodal inputs in its spec, which can matter for file/audio/video classification pipelines.

Where Claude Haiku 4.5 shines: 1) High-accuracy routing for legal or medical triage — our tests show Claude’s classification score 4/5 and faithfulness 5/5, reducing hallucinated labels. 2) Complex multilingual label mapping with large context — Claude’s long_context 5 and multilingual 5 support accurate decisions when classifiers must use long transcripts or documents. 3) Integration needing precise reasoning about edge cases — strategic_analysis 5 helps resolve ambiguous categories. Where Gemini 2.5 Flash shines: 1) Large-scale, cost-sensitive pipelines — Gemini’s input $0.3/output $2.5 is ~half the per-mTok output cost vs Claude ($5), making it cheaper for high-throughput classification. 2) Safety-sensitive routing — safety_calibration 4 vs Claude’s 2 means Gemini better handled refusal/reroute in our safety tests. 3) Multimodal classification involving files/audio/video (Gemini’s modality includes file/audio/video->text), useful when labels must derive from non-text inputs. Concrete numeric differences to guide choices: Classification score 4 vs 3 (Claude vs Gemini), faithfulness 5 vs 4, safety_calibration 2 vs 4, and costs $1/$5 vs $0.3/$2.5 (input/output per mTok).

For Classification, choose Claude Haiku 4.5 if you need the highest accuracy, faithfulness to source material, and top-ranked categorization (score 4/5, rank 1/52). Choose Gemini 2.5 Flash if you need a lower-cost production classifier or stronger safety refusal behavior (score 3/5 but safety_calibration 4/5) and multimodal input support.