R1 0528 vs GPT-5.4 Mini

All benchmark claims below are from our testing on a 12-test suite. Summary: R1 0528 wins tool_calling (5 vs 4), safety_calibration (4 vs 2), and agentic_planning (5 vs 4); GPT-5.4 Mini wins structured_output (5 vs 4) and strategic_analysis (5 vs 4); the remaining seven tests tie. Detailed walk-through: 1) Tool calling — R1 0528 scores 5 and is tied for 1st (tied with 16 others out of 54), while GPT-5.4 Mini scores 4 and ranks 18/54. That means in our testing R1 better selects functions, arguments, and sequencing for agentic workflows. 2) Safety calibration — R1 scores 4 (rank 6/55) vs GPT’s 2 (rank 12/55), so R1 more reliably refuses harmful prompts in our suite. 3) Agentic planning — R1 scores 5 (tied for 1st) vs GPT’s 4 (rank 16), indicating R1’s stronger goal decomposition and recovery in our tests. 4) Structured output — GPT-5.4 Mini scores 5 (tied for 1st) vs R1’s 4 (rank 26), so GPT is the safer pick when strict JSON/schema compliance matters. 5) Strategic analysis — GPT scores 5 (tied for 1st) vs R1’s 4 (rank 27), meaning GPT produced higher-scoring nuanced numeric tradeoffs in our scenarios. Ties — constrained_rewriting (4/4), creative_problem_solving (4/4), faithfulness (5/5), classification (4/4), long_context (5/5), persona_consistency (5/5), and multilingual (5/5) — both models performed equally well on these tasks in our testing. Additional context: R1’s context window is 163,840 tokens; GPT-5.4 Mini’s is 400,000 tokens and supports text+image+file→text, but both earned top scores (5) on our long_context test. Note R1 has model quirks: it uses explicit reasoning tokens and can return empty responses on structured_output, constrained_rewriting, and agentic_planning unless configured with high max completion tokens — this impacts short structured tasks and must be engineered around.

R1 0528 is materially cheaper: input $0.50/mTok and output $2.15/mTok vs GPT-5.4 Mini at $0.75/mTok and $4.50/mTok. At 1M tokens (1,000 mTok) a 50/50 input/output split costs ~$1,325 on R1 and ~$2,625 on GPT-5.4 Mini (saving $1,300/month). At 10M tokens a 50/50 split costs ~$13,250 (R1) vs $26,250 (GPT) — a $13,000 monthly gap. At 100M tokens the 50/50 totals are ~$132,500 (R1) vs $262,500 (GPT) — a $130,000 monthly difference. Teams with high throughput or tight margins should prefer R1 0528 for cost efficiency; teams that require best-in-class structured-output compliance or multimodal inputs may accept GPT-5.4 Mini’s higher cost.

Choose R1 0528 if you need lower-cost production throughput, strong tool calling and agentic planning, better safety calibration, and top-tier long-context and multilingual performance (in our testing). Choose GPT-5.4 Mini if you require the strictest structured-output/JSON compliance or the strongest strategic numeric reasoning and multimodal inputs (text+image+file) and can absorb roughly double the per-token output cost.