Claude Sonnet 4.6 vs Grok 4 for Math

What Math demands: precise step-by-step reasoning, faithful numeric arithmetic, schema-compliant structured outputs (for graders/checkers), reliable tool calling (calculator/symbolic engines), and the ability to reason creatively on nonstandard olympiad problems. When an authoritative external benchmark exists (MATH Level 5, Epoch AI) we treat it as primary; in this payload neither model has a MATH Level 5 score, so we cannot use it to decide. Instead we rely on available third-party measures and our internal proxies. Claude Sonnet 4.6 provides supplementary external evidence in our data: SWE-bench Verified 75.2% and AIME 2025 85.8% (Epoch AI). Internally, both models score identically on the two Math task tests we ran (strategic_analysis = 5, structured_output = 4), so the tie is broken by supporting metrics: Sonnet's higher creative_problem_solving and tool_calling indicate stronger performance on novel problem approaches and on tool-driven numeric workflows; Sonnet's higher safety_calibration and agentic_planning scores also reduce unsafe or incorrect shortcuts and improve multi-step decomposition. Grok 4's strengths (constrained_rewriting 4, large multimodal/file inputs, 256k context) make it competitive for compressed outputs and certain input types but do not outweigh Sonnet's advantages for open-ended math reasoning in our testing.

Examples grounded in scores and features:

• Research-style or olympiad problem solving: Choose Claude Sonnet 4.6. It scores 5 vs 3 on creative_problem_solving and has an AIME 2025 score of 85.8% (Epoch AI) and SWE-bench 75.2% (Epoch AI) in our payload, showing aptitude for difficult, nonstandard solutions.
• Calculator / tool-assisted workflows (symbolic math, code execution, multi-step numeric pipelines): Choose Claude Sonnet 4.6. Tool_calling is 5 vs Grok 4, meaning more accurate function selection and argument sequencing in our tests.
• Strict format or grader-ready JSON outputs: Both models tie on structured_output (4 vs 4); either is fine for schema-compliant answers in our suite.
• Short, character-limited summaries or compression of full solutions (submit-as-140-chars style): Choose Grok 4. It wins constrained_rewriting (4 vs 3) in our tests, so it better preserves fidelity under tight limits.
• Working from a mix of images and uploaded files (scanned problems / PDFs): Choose Grok 4 for file->text modality (payload shows Grok supports text+image+file->text); Sonnet supports text+image->text but the payload lists Grok as handling files which may simplify file-based ingestion.
• Very long derivations / huge context notebooks: Both models score 5 on long_context, but Sonnet has a larger declared context_window (1,000,000 vs 256,000), which favors Sonnet when you must keep extremely large notebooks or datasets in context.

For Math, choose Claude Sonnet 4.6 if you need stronger creative problem solving, more reliable tool-calling integrations, and better third-party external results (SWE-bench 75.2% and AIME 2025 85.8% in our payload). Choose Grok 4 if you need better constrained_rewriting (compression into tight character limits), built-in file ingestion (text+image+file->text), or you prioritize file-based multimodal input workflows where Grok's modality list may help.