Claude Sonnet 4.6 vs Grok 4.20
For most professional and safety-sensitive workflows, Claude Sonnet 4.6 is the better pick: it wins 3 of 12 benchmarks in our tests (notably safety_calibration, creative_problem_solving, agentic_planning). Grok 4.20 is the cost-efficient choice and wins structured_output and constrained_rewriting; choose Grok where strict format compliance or lower per‑token cost matters.
anthropic
Claude Sonnet 4.6
Benchmark Scores
External Benchmarks
Pricing
Input
$3.00/MTok
Output
$15.00/MTok
modelpicker.net
xai
Grok 4.20
Benchmark Scores
External Benchmarks
Pricing
Input
$2.00/MTok
Output
$6.00/MTok
modelpicker.net
Benchmark Analysis
We compared Claude Sonnet 4.6 and Grok 4.20 across our 12-test suite and report our internal 1–5 scores and ranking context. Key wins and ties (all statements are from our testing):
- Claude Sonnet 4.6 wins: creative_problem_solving 5 vs 4 (Sonnet tied for 1st of 54, tied with 7 others), safety_calibration 5 vs 1 (Sonnet tied for 1st of 55, tied with 4 others), agentic_planning 5 vs 4 (Sonnet tied for 1st of 54, tied with 14 others). These scores indicate Sonnet is more reliable on refusal/permission decisions, idea generation for non-obvious solutions, and multi-step goal decomposition in our tests.
- Grok 4.20 wins: structured_output 5 vs 4 (Grok tied for 1st of 54, Sonnet rank 26 of 54) and constrained_rewriting 4 vs 3 (Grok rank 6 of 53 vs Sonnet rank 31). That translates into Grok producing more accurate JSON/schema compliance and better compression into hard char limits in our tasks.
- Ties: strategic_analysis (5/5), tool_calling (5/5), faithfulness (5/5), classification (4/4), long_context (5/5), persona_consistency (5/5), multilingual (5/5). In particular, both models tie for 1st on tool_calling and faithfulness (each tied with many other leading models), so for function selection and sticking to source material our tests show comparable performance.
- External supplements (Epoch AI): Claude Sonnet 4.6 scores 75.2% on SWE-bench Verified (Epoch AI), ranking 4 of 12 on that external coding benchmark, and 85.8% on AIME 2025 (Epoch AI), ranking 10 of 23. Grok 4.20 has no SWE-bench or AIME entry in the payload. These external numbers support Sonnet’s coding/math strengths in our comparative view but should be read as supplementary to our 1–5 tests. Overall interpretation: Sonnet’s clear advantage is safety and agentic reasoning plus strong creative outputs; Grok’s clear advantage is structured-output fidelity and constrained rewriting plus a much lower output cost.
Pricing Analysis
Pricing in the payload is per million tokens: Sonnet 4.6 input $3/M, output $15/M; Grok 4.20 input $2/M, output $6/M. Examples at common monthly volumes (input-only / output-only / 50/50 split):
- 1M tokens: Sonnet = $3 / $15 / $9 (50/50); Grok = $2 / $6 / $4 (50/50).
- 10M tokens: Sonnet = $30 / $150 / $90; Grok = $20 / $60 / $40.
- 100M tokens: Sonnet = $300 / $1,500 / $900; Grok = $200 / $600 / $400. Impact: generation-heavy workloads (high output token counts) pay the largest premium for Sonnet: at 100M output tokens Sonnet costs $1,500 vs Grok $600 (a $900 gap). Teams with heavy schema/JSON outputs or tight budgets should prioritize Grok; teams that need stronger safety calibration, complex agentic planning, or higher creative/problem-solving fidelity should budget for Sonnet’s higher per-output cost.
Real-World Cost Comparison
Bottom Line
Choose Claude Sonnet 4.6 if you need: strong safety calibration and refusal behavior, high-quality creative problem solving, robust agentic planning/goal decomposition, or stronger external coding/math signals (Sonnet scores 75.2% on SWE-bench Verified and 85.8% on AIME 2025 per Epoch AI). Choose Grok 4.20 if you need: strict structured-output / JSON schema compliance, reliable constrained rewriting (tight character budgets), or want the lower per‑token price for high-volume generation workloads (input/output $2/$6 vs Sonnet $3/$15 per M).
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.