Claude Haiku 4.5 vs DeepSeek V3.1 for Faithfulness

What Faithfulness demands: sticking to source material without inventing facts, accurately invoking tools and returning verified outputs, and preserving provenance and required formats. When an external benchmark is absent (externalBenchmark is null) we rely on our internal task scores and supporting proxies. Both models score 5/5 on our Faithfulness test (tie). To break that tie, examine related capabilities in our testing: tool_calling (Claude Haiku 4.5: 5, DeepSeek V3.1: 3) matters for accurate function selection and argument correctness; structured_output (Claude Haiku 4.5: 4, DeepSeek V3.1: 5) matters for JSON/schema fidelity; safety_calibration (Claude Haiku 4.5: 2, DeepSeek V3.1: 1) affects refusal and risk of confident hallucinations. Long_context (both 5) and persona_consistency (both 5) support faithful retrieval and consistent framing. Use these supporting scores to choose based on the specific failure modes you need to avoid.

1. Tool-driven data retrieval (APIs, DBs): Claude Haiku 4.5 shines — tool_calling 5 vs 3 — in our tests it more reliably picked the correct function and constructed accurate arguments, reducing downstream hallucinations. 2) Regulatory report generation with strict JSON schema: DeepSeek V3.1 is better — structured_output 5 vs 4 — if you must pass machine-validated JSON to downstream systems. 3) High-risk refusal scenarios (medical triage prompts, ambiguous claims): Claude Haiku 4.5 has a small advantage (safety_calibration 2 vs 1) in our testing, so it more often avoided unsafe or invented answers. 4) Bulk, cost-sensitive batch labeling: DeepSeek V3.1 is much cheaper — output cost $0.75 per mTok vs Claude Haiku 4.5 at $5.00 per mTok — making DeepSeek preferable when cost per token is the dominant constraint while still delivering top-tier faithfulness on simpler tasks. 5) Long documents and provenance tracing: both models scored 5 on long_context, so either handles long-source grounding similarly in our tests.

For Faithfulness, choose Claude Haiku 4.5 if you need faithful tool integrations, lower hallucination risk when invoking external functions, or stronger refusal behavior. Choose DeepSeek V3.1 if you need strict schema/JSON compliance or are optimizing for much lower token costs ($0.75 vs $5.00 per output mTok) while still getting a 5/5 faithfulness score in our tests.