Claude Sonnet 4.6 vs Grok 4

Across our 12-test suite, Claude Sonnet 4.6 wins four tests, Grok 4 wins one, and seven tests tie. Detailed walk-through:

• Creative problem solving: Sonnet 4.6 scores 5 vs Grok 4's 3 in our testing; Sonnet ranks tied for 1st of 54 (tied with 7 others) — expect stronger non-obvious, feasible idea generation from Sonnet.
• Tool calling: Sonnet 4.6 scores 5 vs Grok 4's 4; Sonnet is tied for 1st of 54 (tied with 16 others) while Grok ranks 18 of 54 — Sonnet is superior at selecting, sequencing and argument accuracy for function calls in our tests.
• Safety calibration: Sonnet 4.6 scores 5 vs Grok 4's 2; Sonnet ranks tied for 1st of 55 (tied with 4 others) while Grok ranks 12 of 55 — Sonnet is far more conservative at refusing harmful requests and permitting legitimate ones in our scenarios.
• Agentic planning: Sonnet 4.6 scores 5 vs Grok 4's 3; Sonnet is tied for 1st of 54 (tied with 14 others) and shows stronger goal decomposition and failure recovery in our tests.
• Constrained rewriting: Grok 4 wins 4 vs Sonnet 3; Grok ranks 6 of 53 (25 models share this score) while Sonnet ranks 31 of 53 — Grok is better at tight compression and strict character-limit rewrites in our tests.
• Ties (both models equal in our testing): structured_output (4), strategic_analysis (5), faithfulness (5), classification (4), long_context (5), persona_consistency (5), multilingual (5). Note both models rank highly on long_context and multilingual (Sonnet long_context rank tied for 1st of 55; Grok long_context also tied for 1st of 55).
• External benchmarks: Beyond our internal scores, Claude Sonnet 4.6 scores 75.2% on SWE-bench Verified and 85.8% on AIME 2025 according to Epoch AI (these place Sonnet 4.6 at rank 4 of 12 on SWE-bench Verified and rank 10 of 23 on AIME 2025 in our data). Grok 4 has no external scores in the payload.
• Context & feature implications: Sonnet 4.6 has a 1,000,000-token context window and excels at tool calling, safety, agentic planning and creative tasks; Grok 4 offers a 256,000-token window, file input support and parallel tool calling (payload notes 'uses_reasoning_tokens' as a quirk). In short: Sonnet dominates agentic/tool/safety axes in our suite; Grok is the narrower winner for constrained compression tasks.

Both models charge the same rates in the payload: $3 per mTok input and $15 per mTok output. That parity means cost is not a differentiator. Example costs (assuming a 50/50 split of input vs output tokens):

• 1M tokens/month → 500 mtok input ($1,500) + 500 mtok output ($7,500) = $9,000/mo
• 10M tokens/month → 5,000 mtok input ($15,000) + 5,000 mtok output ($75,000) = $90,000/mo
• 100M tokens/month → 50,000 mtok input ($150,000) + 50,000 mtok output ($750,000) = $900,000/mo If all tokens were output (worst-case cost): 1M=$15,000; 10M=$150,000; 100M=$1,500,000. Who should care: teams with high-throughput production workloads (10M+ tokens) must model real input/output splits — both models scale to the same dollar rates, so pick based on capabilities, not price.

Choose Claude Sonnet 4.6 if you need best-in-class tool calling, agentic planning, safety calibration, creative problem solving, and the largest context window (1,000,000 tokens). It also has strong external coding/math signals (75.2% SWE-bench Verified, 85.8% AIME 2025 per Epoch AI). Choose Grok 4 if your primary need is constrained rewriting (it scores 4 vs Sonnet's 3 and ranks 6 of 53), or you require Grok's file-input modality, parallel tool calling support and a 256k context window, while accepting lower safety and agentic scores. Cost is identical for both ($3 input / $15 output per mTok), so pick on capability and constraints.