Claude Sonnet 4.6 vs GPT-4.1 Mini

Overview: In our 12-test suite Claude Sonnet 4.6 wins 7 categories, GPT-4.1 Mini wins 1, and 4 are ties. Below are test-by-test specifics with ranks and practical meaning.

• Tool calling: Sonnet 4.6 scores 5 vs GPT-4.1 Mini 4. Sonnet is tied for 1st of 54 models (tied with 16) — meaning in our tests it selects and sequences functions more accurately for multi-step agent workflows.
• Faithfulness: Sonnet 4.6 scores 5 vs GPT-4.1 Mini 4. Sonnet is tied for 1st of 55 (tied with 32) — it sticks to source content more reliably in our evaluations, reducing hallucination risk in factual tasks.
• Safety calibration: Sonnet 4.6 scores 5 vs GPT-4.1 Mini 2. Sonnet is tied for 1st of 55 (tied with 4); GPT-4.1 Mini ranks 12/55. That means Sonnet refused harmful prompts and allowed legitimate ones in our safety tests far more consistently.
• Agentic planning: Sonnet 4.6 scores 5 vs GPT-4.1 Mini 4. Sonnet is tied for 1st of 54 — it better decomposes goals and plans failure recovery in our planning scenarios.
• Strategic analysis: Sonnet 4.6 scores 5 vs GPT-4.1 Mini 4. Sonnet is tied for 1st of 54 — better at nuanced tradeoff reasoning in our numeric reasoning tests.
• Classification: Sonnet 4.6 scores 4 vs GPT-4.1 Mini 3. Sonnet ranks tied for 1st of 53 (tied with 29) — more accurate routing and categorization in our label tests.
• Creative problem solving: Sonnet 4.6 scores 5 vs GPT-4.1 Mini 3. Sonnet is tied for 1st of 54 — produces more specific, feasible creative ideas in our prompts.
• Constrained rewriting: GPT-4.1 Mini wins (4) vs Sonnet (3). GPT ranks 6/53 (tied with 24) while Sonnet ranks 31/53 — GPT-4.1 Mini handles tight character/format compression better in our constrained rewrite tasks.
• Structured output: tie (both score 4). Both rank 26/54 — equal performance on JSON/schema adherence in our tests.
• Long context: tie (both score 5). Both tied for 1st of 55 — both handle 30K+ retrieval scenarios in our long-context tests.
• Persona consistency: tie (both score 5). Both tied for 1st of 53 — both maintain persona and resist injection in our dialogue tests.
• Multilingual: tie (both score 5). Both tied for 1st of 55 — equal quality across non-English languages in our prompts.

External benchmarks (Epoch AI): On SWE-bench Verified (Epoch AI), Claude Sonnet 4.6 scores 75.2% (rank 4 of 12), indicating strong code-understanding in third-party GitHub issue resolution. GPT-4.1 Mini scores 87.3% on MATH Level 5 (Epoch AI; rank 9 of 14), showing strong performance on competition math problems. On AIME 2025 (Epoch AI), Sonnet 4.6 scores 85.8% vs GPT-4.1 Mini 44.7% — Sonnet substantially outperformed GPT-4.1 Mini on this math-olympiad benchmark in those external tests. Note: external benchmarks are attributed to Epoch AI, as provided.

Raw rate comparison (per 1,000 tokens): Claude Sonnet 4.6 input $3 / output $15; GPT-4.1 Mini input $0.40 / output $1.60. Using a 50/50 split of input vs output tokens as a simple real-world example, Sonnet 4.6 costs about $9,000 per 1M tokens, $90,000 per 10M, and $900,000 per 100M. GPT-4.1 Mini costs about $1,000 per 1M, $10,000 per 10M, and $100,000 per 100M. The payload's priceRatio is 9.375, which aligns with Sonnet being roughly nine times more expensive in typical token-split scenarios. Teams doing high-volume inference (APIs, analytics pipelines, large-scale assistants) should care most about the gap; small teams or experiments may accept Sonnet's premium for higher capability, while high-throughput services should prefer GPT-4.1 Mini for cost efficiency.

Choose Claude Sonnet 4.6 if you need best-in-class tool-calling, faithfulness, safety, agentic planning, creative problem solving or long-context work for product-grade assistants and developer-facing agents, and you can absorb a roughly 9× price premium. Choose GPT-4.1 Mini if you need a cost-efficient, high-throughput model that still handles long context and persona work, is significantly cheaper for large-volume deployments, and outperforms Sonnet on constrained rewriting and MATH Level 5 (Epoch AI).