Claude Haiku 4.5 vs DeepSeek V3.2 for Math

Math demands precise multi-step reasoning, faithful intermediate steps, strict output formats (LaTeX/JSON), symbolic manipulation, and, in some pipelines, tool use (calculators or CAS). The external MATH Level 5 benchmark (Epoch AI) would be the primary signal if scores were available, but neither model has a reported math_level_5 score here. Therefore we rely on our internal Math-relevant probes: strategic_analysis (nuanced numeric reasoning) and structured_output (JSON/schema compliance and format adherence). In our testing both models score 5/5 on strategic_analysis, indicating equal capability on numeric tradeoffs and high-level reasoning. DeepSeek V3.2 scores 5/5 on structured_output vs Claude Haiku 4/5 in our testing — showing DeepSeek is superior at producing exact, machine-parseable math outputs. Other supporting factors: both models score 5/5 on faithfulness and long_context (useful for long derivations), but Claude Haiku 4.5 scores 5/5 on tool_calling vs DeepSeek 3/5 in our testing, which favors Claude for workflows that require external calculators or execution. Claude also supports text+image→text, helpful for scanned problems; DeepSeek is text→text only. Finally, cost and context: Claude Haiku 4.5 has a larger context window (200,000 vs 163,840 tokens) and higher per-mTok costs (input 1 / output 5) versus DeepSeek (input 0.26 / output 0.38).

1. Automated grading / strict output pipelines: DeepSeek V3.2 excels. In our testing it scores 5/5 on structured_output vs Claude Haiku 4/5 — fewer format fixes and higher JSON/LaTeX compliance when exporting solutions to graders or downstream parsers. 2) Multi-step olympiad-style problems: Tie on high-level reasoning — both score 5/5 on strategic_analysis in our testing — so either model can plan multi-step proofs; DeepSeek has the edge when the answer must be machine-validated. 3) Tool-driven numeric verification: Claude Haiku 4.5 is preferable if you rely on external calculators/CAS because it scores 5/5 on tool_calling vs DeepSeek 3/5 in our testing. 4) Image-based math (scanned worksheets, photos of equations): Claude Haiku 4.5 supports text+image→text (DeepSeek is text→text), making Haiku better when you must OCR and reason from images. 5) Cost-sensitive bulk workloads: DeepSeek V3.2 is far cheaper (input_cost_per_mtok 0.26, output_cost_per_mtok 0.38) compared to Claude Haiku 4.5 (input 1, output 5) — choose DeepSeek for heavy, structured-math generation at scale.

For Math, choose DeepSeek V3.2 if you need strict, machine-parseable answers and automated grading (it scores 5 vs 4 on structured_output in our testing and ties on strategic_analysis). Choose Claude Haiku 4.5 if your workflow depends on strong tool-calling (5 vs 3 in our testing) or multimodal input (text+image→text) despite higher cost and slightly weaker structured output.