Claude Opus 4.6 vs GPT-4.1 Nano

Summary of our 12-test suite results (scores are from our tests). Claude Opus 4.6 wins 8 categories: strategic_analysis 5 vs 2 (Opus tied for 1st of 54), creative_problem_solving 5 vs 2 (Opus tied for 1st), agentic_planning 5 vs 4 (Opus tied for 1st), tool_calling 5 vs 4 (Opus tied for 1st; GPT-4.1 Nano rank 18 of 54), long_context 5 vs 4 (Opus tied for 1st; Nano ranks 38 of 55), safety_calibration 5 vs 2 (Opus tied for 1st), persona_consistency 5 vs 4 (Opus tied for 1st), and multilingual 5 vs 4 (Opus tied for 1st). GPT-4.1 Nano wins two categories: structured_output 5 vs 4 (Nano tied for 1st of 54) and constrained_rewriting 4 vs 3 (Nano rank 6 of 53). Faithfulness and classification tie (both models score 5 and 3 respectively). What this means in practice: Opus’s 5/5 in tool_calling and agentic_planning translates to stronger function selection, sequencing, and multi-step agent workflows; its 5/5 long_context means better retrieval and accuracy across 30K+ token contexts. Nano’s 5/5 structured_output shows it reliably adheres to strict JSON/schema formats and performs better when exact output formatting is the dominant requirement. External benchmarks (Epoch AI) supplement these findings: Claude Opus 4.6 scores 78.7% on SWE-bench Verified (Epoch AI) and 94.4% on AIME 2025 (Epoch AI), ranking 1st on SWE-bench Verified and 4th on AIME in our referenced set. GPT-4.1 Nano scores 70% on MATH Level 5 and 28.9% on AIME 2025 (Epoch AI), placing lower on those math benchmarks. In short: Opus gives measurable advantages for complex reasoning, large-context workflows and safety-sensitive tasks; Nano is highly capable at structured outputs and is far more cost-efficient.

Costs are per 1k-token (mTok) units from the payload. Claude Opus 4.6 charges $5 input + $25 output = $30 per 1k tokens. GPT-4.1 Nano charges $0.10 input + $0.40 output = $0.50 per 1k tokens. At realistic volumes that scales quickly: for 1M tokens/month (1,000 mTok) Opus ≈ $30,000 vs Nano ≈ $500. At 10M tokens/month Opus ≈ $300,000 vs Nano ≈ $5,000. At 100M tokens/month Opus ≈ $3,000,000 vs Nano ≈ $50,000. The cost gap matters most for high-volume products (SaaS, mobile apps, search, telemetry pipelines). For small-scale research or developer experimentation the quality gap may justify Opus; for production at scale, Nano’s cost savings are decisive.

Choose Claude Opus 4.6 if you need best-in-class long-context handling, multi-step agentic planning, tool calling, coding support, or safety-calibrated responses—especially for workflows where correctness and reliability outweigh cost. Choose GPT-4.1 Nano if your priority is low latency and low cost at scale (Nano costs ~$0.50 per 1k tokens total vs Opus ~$30 per 1k), or if your workload demands strict schema/JSON outputs or tight token-budget constraints.