Claude Sonnet 4.6 vs o3

Head-to-head summary from our 12-test suite (scores and ranks come from the payload):

• Wins for Claude Sonnet 4.6: creative_problem_solving 5 vs o3 4 (Sonnet tied for 1st of 54), classification 4 vs 3 (Sonnet rank 1 of 53 tied), long_context 5 vs 4 (Sonnet tied for 1st of 55; o3 rank 38 of 55) and safety_calibration 5 vs 1 (Sonnet tied for 1st of 55; o3 rank 32 of 55). For real tasks this means Sonnet better handles non-obvious idea generation, resists harmful prompts while permitting legit ones, and retrieves/ reasons over 30K+ tokens more reliably.
• Wins for o3: structured_output 5 vs Sonnet 4 (o3 tied for 1st of 54) and constrained_rewriting 4 vs Sonnet 3 (o3 rank 6 of 53). Practically, o3 is superior at strict JSON/schema adherence and squeezing content into hard character limits.
• Ties (equal scores): strategic_analysis (5), tool_calling (5), faithfulness (5), persona_consistency (5), agentic_planning (5), multilingual (5). Both models are top-tier on reasoning, tool selection/sequencing, staying faithful to sources, maintaining persona, agentic planning, and multilingual output. External benchmarks (attributed): on SWE-bench Verified (Epoch AI) Sonnet 4.6 scores 75.2% (rank 4 of 12) vs o3's 62.3% (rank 9 of 12), supporting Sonnet's coding/code-reasoning edge. On MATH Level 5 (Epoch AI) o3 scores 97.8% (rank 2 of 14), a clear signal that o3 is extreme strong for competition-grade math. On AIME 2025 (Epoch AI) Sonnet 85.8% vs o3 83.9% (Sonnet rank 10, o3 rank 12 of 23). These external results corroborate our internal wins: Sonnet is stronger for coding and long-context safety-sensitive workflows, while o3 is best for formal constrained formats and high-end math.

Per-token prices from the payload: Claude Sonnet 4.6 input $3 / mTok and output $15 / mTok; o3 input $2 / mTok and output $8 / mTok. Translate to common monthly volumes (mTok = 1,000 tokens):

• 1M tokens (50/50 input/output): Sonnet = $9,000 (500mTok input =$1,500; 500mTok output =$7,500). o3 = $5,000 (500mTok input =$1,000; 500mTok output =$4,000). Delta = $4,000/month.
• 10M tokens (50/50): Sonnet = $90,000; o3 = $50,000. Delta = $40,000/month.
• 100M tokens (50/50): Sonnet = $900,000; o3 = $500,000. Delta = $400,000/month. If usage is output-heavy (e.g., 80% output), the gap widens: 1M tokens -> Sonnet $12,600 vs o3 $6,400. If input-only, Sonnet $3,000 vs o3 $2,000 per 1M. Who should care: startups, high-volume APIs, and cost-conscious products should prefer o3 to reduce spend. Teams for whom safety, very long context (1,000,000 token window), or top creative/code performance drive business value should evaluate Sonnet despite the higher per-token bill.

Choose Claude Sonnet 4.6 if you need strict safety calibration, very long-context reasoning (100k+ to 1M windows), superior creative problem solving, or the best coding/coding-navigation signals (SWE-bench 75.2% and internal 5/5 scores). Expect to pay roughly 1.875x more per token. Choose o3 if you need the best structured-output and constrained-rewriting reliability, top-tier competition math (MATH Level 5 97.8% per Epoch AI), or a materially lower bill — it’s the better cost/value choice for high-volume production.