Claude Haiku 4.5 vs R1 0528 for Faithfulness

What Faithfulness demands: accurate extraction and reproduction of source facts, conservative refusal when evidence is missing, strict adherence to structured schemas when required, and effective use of long context and tool outputs. Capabilities that matter most: (1) safety_calibration — refusal and constraint behavior directly reduce hallucinations; (2) long_context — retrieval accuracy across long documents (both models score 5 in our tests); (3) tool_calling and structured_output — correct function selection and JSON/schema compliance (both models score tool_calling 5 and structured_output 4 in our tests); (4) modality and context window — multimodal sources and larger windows help fidelity when sources include images or very long documents (Claude Haiku 4.5 supports text+image->text and a 200,000-token window; R1 0528 is text-only with a 163,840-token window). In our testing the core faithfulness metric is tied (5/5 each), so we use adjacent benchmarks (notably safety_calibration: R1 0528 = 4, Claude Haiku 4.5 = 2) and operational factors (cost and known quirks) as tie-breakers to explain which model will deliver more reliable, actionable fidelity in production.

1. Long legal or technical document extraction where schema fidelity matters: Both models score 5 on long_context and 4 on structured_output, so either can retrieve and format facts from 30K+ tokens. Preference: Claude Haiku 4.5 if you must ingest images (it supports text+image->text) or need the largest window (200,000). 2) Clinical triage or high-risk fact-checking where refusals matter: R1 0528 is preferable — in our testing its safety_calibration is 4 vs Claude Haiku 4.5's 2, which means R1 is likelier to refuse or hedge unsupported claims, reducing hallucination risk. 3) Strict JSON API responses with short budgets: Both models have structured_output = 4, but R1 0528 has a documented quirk — "Returns empty responses on structured_output, constrained_rewriting, and agentic_planning — reasoning tokens consume output budget on short tasks" — that can cause empty outputs on short tasks unless you allocate large completion tokens. Claude Haiku 4.5 is less likely to hit that specific failure mode. 4) Cost-sensitive bulk verification jobs: R1 0528 costs $0.50 input / $2.15 output per mTok versus Claude Haiku 4.5 at $1.00 input / $5.00 output per mTok in our data — R1 yields the same 5/5 faithfulness at materially lower cost.

For Faithfulness, choose Claude Haiku 4.5 if you need multimodal source fidelity (text+image->text), the very largest context window (200,000 tokens), or fewer failure modes on short structured responses. Choose R1 0528 if you need a safer refusal profile (safety_calibration 4 vs 2 in our tests), identical faithfulness (5/5), and materially lower output cost ($2.15 vs $5.00 per mTok); be mindful of R1's structured_output quirk and plan token budgets accordingly.