Claude Haiku 4.5 vs DeepSeek V3.1 for Structured Output

What Structured Output demands: precise JSON/schema compliance, consistent field ordering and typing, predictable delimiters, and robust adherence to a response_format. In our framework 'Structured Output' measures JSON schema compliance and format adherence. Primary evidence is the task scores: DeepSeek V3.1 = 5 (tied for 1st of 52), Claude Haiku 4.5 = 4 (rank 26 of 52). Supporting signals: both models expose a structured_outputs/response_format parameter in their supported_parameters, but they differ on related capabilities that affect real-world behavior. Claude Haiku 4.5 scores 5/5 on tool_calling (helpful when structured outputs must trigger functions) and offers a 200k-token context window and text+image->text modality (useful for schema extraction from long multimodal inputs). DeepSeek V3.1 is cheaper per mTok (input $0.15/output $0.75 vs Haiku $1/$5) and its 5/5 structured_output score shows stronger compliance in our JSON/schema tests. Use these tested metrics as the basis for choosing: strict schema adherence -> DeepSeek; tool-driven, multimodal, or massive-context pipelines -> Haiku.

1. API that must return strict JSON to a downstream validator: DeepSeek V3.1 (5 vs 4) — fewer schema rejections in our structured_output tests and top rank in the task. 2) Serverless webhook that both returns JSON and immediately invokes functions: Claude Haiku 4.5 shines on tool_calling (5 vs 3), so it reduces argument-parsing errors and sequencing bugs even though its structured_output score is 4/5. 3) Extracting structured data from long documents or images (invoices, research papers): Claude Haiku 4.5 supports text+image->text and a 200k-token context window, making it better for large multimodal extraction despite scoring 4/5 on schema adherence. 4) High-volume, cost-sensitive batch schema validation: DeepSeek V3.1 is far cheaper — input $0.15/output $0.75 per mTok vs Haiku $1/$5 — and its 5/5 structured_output score makes it the cost-effective choice for strict JSON pipelines. 5) Mixed workloads where both strict schema and tool orchestration are needed: prefer Claude Haiku 4.5 if tool-calling reliability and huge context matter more than a single-point advantage in schema adherence.

For Structured Output, choose Claude Haiku 4.5 if you need strong tool calling, massive context (200k tokens), or image→text extraction integrated into a structured pipeline. Choose DeepSeek V3.1 if strict JSON schema adherence, top-ranked structured-output performance (5 vs 4 in our tests), and lower per-mTok cost ($0.15/$0.75 vs $1/$5) are your priorities.