Claude Opus 4.6 vs GPT-4.1
In our benchmarks Claude Opus 4.6 is the better pick for agentic, safety-sensitive, and long-running coding workflows; it wins more tests (3 vs GPT‑4.1's 2). GPT‑4.1 wins constrained rewriting and classification while offering a much lower price per token, so pick GPT‑4.1 when cost and tight-format tasks matter.
anthropic
Claude Opus 4.6
Benchmark Scores
External Benchmarks
Pricing
Input
$5.00/MTok
Output
$25.00/MTok
modelpicker.net
openai
GPT-4.1
Benchmark Scores
External Benchmarks
Pricing
Input
$2.00/MTok
Output
$8.00/MTok
modelpicker.net
Benchmark Analysis
Head-to-head (our 12-test suite and Epoch AI external scores): Wins — Claude Opus 4.6 wins creative_problem_solving (5 vs 3), safety_calibration (5 vs 1), and agentic_planning (5 vs 4). GPT‑4.1 wins constrained_rewriting (5 vs 3) and classification (4 vs 3). Ties (identical scores): structured_output (4), strategic_analysis (5), tool_calling (5), faithfulness (5), long_context (5), persona_consistency (5), and multilingual (5). External benchmarks (Epoch AI): on SWE-bench Verified Claude scores 78.7% vs GPT‑4.1 48.5% (Claude ranks 1 of 12, sole holder; GPT ranks 11 of 12). On AIME 2025 Claude scores 94.4% vs GPT‑4.1 38.3% (Claude ranks 4 of 23; GPT ranks 19 of 23). GPT‑4.1 posts 83% on MATH Level 5 (rank 10 of 14). What this means in practice: Claude’s 5/5 safety_calibration (tied for 1st in our set) signals stronger refusal/permission behavior useful for moderation and compliance workflows; its agentic_planning 5/5 (tied for 1st) and top SWE-bench Verified score (78.7%) indicate better performance for multi-step coding and agent workflows. GPT‑4.1’s 5/5 constrained_rewriting and 4/5 classification make it a better, cheaper choice for strict-format transformations and routing/classification tasks. Where both tie (tool_calling, long_context, faithfulness) you can expect comparable behavior for long-context retrieval, function selection, and sticking to source material.
Pricing Analysis
Pricing (payload rates): Claude Opus 4.6 — $5 input / $25 output per million tokens; GPT‑4.1 — $2 input / $8 output per million tokens. Using a simple 50/50 input/output assumption: per 1M total tokens Claude ≈ $15, GPT‑4.1 ≈ $5. At 10M tokens/month Claude ≈ $150 vs GPT‑4.1 ≈ $50. At 100M tokens/month Claude ≈ $1,500 vs GPT‑4.1 ≈ $500. The output-cost ratio (25/8 = 3.125) in the payload shows Claude’s per-output-token cost is ~3.125× higher. Who should care: startups and high-volume API users will see immediate savings with GPT‑4.1; teams building agentic pipelines, safety-critical systems, or heavy long-context coding workflows should evaluate whether Claude’s higher cost is justified by its wins on safety and agentic planning.
Real-World Cost Comparison
Bottom Line
Choose Claude Opus 4.6 if you need: - Agentic planning and multi-step workflow reliability (agentic_planning 5 vs 4). - Strong safety calibration and compliance (safety_calibration 5 vs 1). - Best-in-class coding/long-workflow support (SWE-bench Verified 78.7%, rank 1). Choose GPT‑4.1 if you need: - Lower cost at scale—about $5 per 1M tokens vs Claude’s ~$15 under a 50/50 I/O split. - Strict constrained rewriting and format adherence (constrained_rewriting 5 vs 3). - Better classification/routing for tasks (classification 4 vs 3). If you operate at high volume or have tight per-token budgets, prioritize GPT‑4.1; if safety, agentic correctness, and top external coding benchmarks matter more than cost, prioritize Claude Opus 4.6.
How We Test
We test every model against our 12-benchmark suite covering tool calling, agentic planning, creative problem solving, safety calibration, and more. Each test is scored 1–5 by an LLM judge. Read our full methodology.