R1 vs GPT-4.1 Nano

Summary of our 12-test suite: R1 wins 4 tests, GPT‑4.1 Nano wins 3, and 5 tests tie. R1 wins: strategic_analysis (R1 5 vs Nano 2) — R1 is tied for 1st in strategic_analysis ("tied for 1st with 25 other models out of 54 tested"), meaning it handles nuanced tradeoff reasoning substantially better in our evaluations; creative_problem_solving (R1 5 vs Nano 2) — R1 ranks tied for 1st on creative problem solving, so it produces more non‑obvious, feasible ideas in our tests; persona_consistency (R1 5 vs Nano 4) — R1 is tied for 1st on persona_consistency, helpful when maintaining characters or system roles; multilingual (R1 5 vs Nano 4) — R1 ranks tied for 1st on multilingual, so non‑English parity is stronger in our testing. GPT‑4.1 Nano wins: structured_output (Nano 5 vs R1 4) — Nano is tied for 1st on structured output ("tied for 1st with 24 other models out of 54 tested"), which translates to tighter JSON/schema adherence; classification (Nano 3 vs R1 2) — Nano ranks 31 of 53 on classification vs R1 rank 51 of 53, so Nano is better at routing and labeling tasks; safety_calibration (Nano 2 vs R1 1) — Nano ranks 12 of 55 vs R1 at 32 of 55, indicating safer refusal behavior in our suite. Ties (no clear winner): constrained_rewriting (4/4), tool_calling (4/4), faithfulness (5/5), long_context (4/4), agentic_planning (4/4) — both models performed equivalently on these tasks in our benchmarks. Math benchmarks (external, Epoch AI): on MATH Level 5 (Epoch AI) R1 scores 93.1% vs GPT‑4.1 Nano 70% (R1 rank 8 of 14, Nano rank 11 of 14); on AIME 2025 (Epoch AI) R1 53.3% vs Nano 28.9% (R1 rank 17 of 23, Nano rank 20 of 23). These external math results corroborate R1's advantage on difficult quantitative reasoning in our tests. Context window & modalities: GPT‑4.1 Nano supports text+image+file->text and a huge context window (1,047,576 tokens) vs R1 text->text and 64,000 tokens; despite that, both tied at 4/5 for long_context in our task suite.

Costs per 1K tokens (mTok): R1 input $0.70 / output $2.50; GPT‑4.1 Nano input $0.10 / output $0.40. Output-only monthly examples: for 1M output tokens (1,000 mTok) R1 = $2,500 vs Nano = $400; 10M tokens: R1 = $25,000 vs Nano = $4,000; 100M tokens: R1 = $250,000 vs Nano = $40,000. If you count both input+output at equal volumes, per‑1M tokens R1 = $3,200 vs Nano = $500; at 100M that's $320,000 vs $50,000. The ~6.25x output price ratio (2.5/0.4) means startups, consumer apps, and high‑volume pipelines should prioritize GPT‑4.1 Nano to avoid huge monthly bills; teams needing R1's superior reasoning/math must justify the cost with features that monetize higher accuracy or capability.

Choose R1 if you need the strongest reasoning, creative problem solving, multilingual parity, or high‑difficulty math performance in our tests and can absorb the cost (R1 output $2.50 per 1K tokens). Choose GPT‑4.1 Nano if you need strict structured outputs, better classification and safety behavior, file/image inputs, or you have high token volumes and must limit costs (GPT‑4.1 Nano output $0.40 per 1K tokens).