R1 0528 vs GPT-4o

Overview: In our 12-test suite R1 0528 wins 9 categories, GPT-4o wins none, and three categories tie. R1 advantages (scores): - Long context: R1 5 vs GPT-4o 4 — R1 is tied for 1st of 55 models on long_context, indicating superior retrieval/accuracy across 30K++ tokens. - Tool calling: R1 5 vs GPT-4o 4 — R1 is tied for 1st of 54 on tool_calling, so it selects and sequences functions more reliably in our tests. - Agentic planning: R1 5 vs GPT-4o 4 — R1 tied for 1st of 54, showing stronger goal decomposition and failure recovery. - Faithfulness: R1 5 vs GPT-4o 4 — R1 tied for 1st of 55, meaning fewer hallucinations in source-constrained tasks. - Persona consistency, multilingual, classification: ties or R1 ties for 1st (persona_consistency 5 tied; classification 4 tied). R1 also outscored GPT-4o on strategic_analysis (4 vs 2), constrained_rewriting (4 vs 3), creative_problem_solving (4 vs 3), and safety_calibration (4 vs 1). Rankings context: R1 ranks tied for 1st on many core categories (persona_consistency, faithfulness, long_context, tool_calling, agentic_planning, multilingual) while GPT-4o sits much lower on safety_calibration (rank 32/55) and strategic_analysis (rank 44/54). External math benchmarks (Epoch AI): R1 scores 96.6% on MATH Level 5 and 66.4% on AIME 2025 (Epoch AI), versus GPT-4o's 53.3% and 6.4% respectively (Epoch AI). For coding, GPT-4o reports a SWE-bench Verified score of 31% (Epoch AI) and ranks 12/12 on that suite; R1 has no SWE-bench Verified entry in the payload. Practical meaning: choose R1 for long-context retrieval, tool-driven workflows, multilingual and faithful outputs. GPT-4o's strengths in this payload are limited; its multimodal input support (text+image+file) may still matter for specific image/file-in → text tasks, but on core reasoning, safety, and long-context benchmarks R1 outperforms.

Pricing (per the payload): R1 0528 input $0.50 / M-token, output $2.15 / M-token; GPT-4o input $2.50 / M-token, output $10.00 / M-token. Assuming a 50/50 input/output split and mtok = 1,000,000 tokens, monthly costs: - 1M tokens: R1 ≈ $1.33, GPT-4o ≈ $6.25. - 10M tokens: R1 ≈ $13.25, GPT-4o ≈ $62.50. - 100M tokens: R1 ≈ $132.50, GPT-4o ≈ $625.00. The payload's priceRatio (0.215) aligns: R1 costs ~21.5% of GPT-4o for comparable token usage. Who should care: any product with sustained traffic (10M+/month) will see large absolute savings with R1; cost-sensitive startups and high-volume APIs benefit most. Teams that prioritize OpenAI integrations or need GPT-4o's multimodal inputs should budget for the higher per-M-token fees.

Choose R1 0528 if: - You need low per-token cost at scale (R1 input $0.50 / M, output $2.15 / M) and expect 10M+ tokens/month. - Your app relies on long-context accuracy, reliable tool calling/agentic planning, multilingual outputs, or faithfulness. - You can handle R1 quirks (it uses reasoning tokens, requires high max completion tokens and can return empty responses on structured_output unless configured). Choose GPT-4o if: - You require multimodal inputs (text+image+file->text as listed in the payload) or specific OpenAI ecosystem features and are willing to pay substantially more (GPT-4o output $10 / M, input $2.50 / M). - You need a capped max_output_tokens (GPT-4o exposes 16,384) or prefer OpenAI's runtime/supported SDKs. In short: R1 for cheaper, higher-performing long-context and tool-driven tasks; GPT-4o only when multimodal input or OpenAI integrations justify the higher price.