Claude Opus 4.7 vs GPT-4.1

Across our 12-test suite the models split results and tie frequently. Wins, ties, and their practical meaning:

• Claude Opus 4.7 wins (in our testing) creative problem solving (5 vs 3): better at producing non-obvious, specific, feasible ideas. Claude ranks tied for 1st on creative problem solving (tied with 8 others of 55).
• Claude wins safety calibration (3 vs 1): more reliable refusals/acceptances in risky prompts; Claude ranks 10th of 56 (3 models share that score).
• Claude wins agentic planning (5 vs 4): stronger goal decomposition and failure recovery; it’s tied for 1st (with 15 others of 55).
• GPT-4.1 wins constrained rewriting (5 vs 4): better at compressing content into hard limits—useful for strict character-limited outputs (GPT-4.1 is tied for 1st with 4 others of 55).
• GPT-4.1 wins classification (4 vs 3): more accurate categorization/routing; GPT-4.1 is tied for 1st on classification (with 29 others of 54).
• GPT-4.1 wins multilingual (5 vs 4): higher-quality non-English output; GPT-4.1 ranks tied for 1st (with 34 others of 56).
• Ties (both models score the same in our testing): structured output (4), strategic analysis (5), tool calling (5), faithfulness (5), long-context (5), and persona consistency (5). For example, both tie for 1st on long-context (tied with 37 others of 56), meaning both handle 30K+ retrieval similarly in our tests. External benchmarks (supplementary): GPT-4.1 scores 48.5% on SWE-bench Verified, 83% on MATH Level 5, and 38.3% on AIME 2025 (according to Epoch AI). No external SWE-bench/Math/AIME scores are provided for Claude in the payload. Practical takeaway: Claude’s wins matter when safety, multi-step planning, and creative ideation are critical; GPT-4.1’s wins matter for strict formatting, categorical tasks, and multilingual applications. Many core capabilities (tool calling, faithfulness, long-context, persona consistency, strategic analysis, structured output) are effectively tied in our testing.

Pricing: Claude Opus 4.7 charges $5 per million input tokens and $25 per million output tokens; GPT-4.1 charges $2 per million input and $8 per million output. For a common symmetric workload (1M input + 1M output tokens/month) Claude costs $30 vs GPT-4.1 $10. At 10M/10M that’s $300 vs $100; at 100M/100M it’s $3,000 vs $1,000. The payload reports an overall price ratio of 3.125, and in symmetric IO scenarios Claude runs roughly 3x the cost of GPT-4.1. Who should care: startups and high-volume API users will feel this immediately—saving $200/month at 10M tokens or $2,000/month at 100M tokens. Teams with tight budgets or large-scale serving should prefer GPT-4.1; teams that prioritize the specific wins listed for Claude should budget for the premium.

Choose Claude Opus 4.7 if: you need stronger safety calibration, best-in-class agentic planning for multi-step goal decomposition, or superior creative problem solving and you can accept roughly a 3x cost premium. Choose GPT-4.1 if: you need cost-efficient inference at scale, stronger constrained rewriting and classification, or the best multilingual output in our tests; also consider GPT-4.1 when external math/coding signals (Epoch AI SWE-bench and MATH scores) are relevant to your evaluation.