Claude Opus 5.5 vs Grok 4.7

Where it leads

• Higher Arena Text score, 1509 Elo vs 1441 Elo
• Higher Arena WebDev score, 1810 Elo vs 1637 Elo
• Higher FrontierMath Tiers 1-3 (v2) score, 91.2% vs 53%
• Higher SimpleQA Verified score, 72.2% vs 56%
• Larger context window 1,000,000 vs 500,000 tokens
• Accepts image input
• Cheaper cached input, $0.20 vs $0.50 per 1M tokens
• Batch pricing, $2 input and $10 output per 1M tokens

Best for

• Long-running agentic coding and knowledge work as the general-purpose default
• Cache-heavy agent loops where the 0.05x read multiplier compounds

Watch out for

• The API effort default is medium here, not high as on Claude Fable 5.1 and Claude Sonnet 5.5, so a like-for-like comparison has to set effort explicitly
• The 4.7-generation tokenizer produces roughly 30% more tokens for the same text than Claude Sonnet 4.6 and earlier, so per-token rates do not compare directly across generations

Where it leads

• Lower input and output prices, $2 and $6 vs $4 and $20 per 1M tokens
• Higher GPQA Diamond score, 92.7% vs 90.6%

Best for

• Output-heavy generation under the 200,000-token prompt line
• A cheaper alternative to the frontier tiers where 500k of context is enough

Watch out for

• The long-prompt threshold is 200,000 tokens, the lowest of any model here, and reaching it doubles input and output for the entire request
• xAI's model page does not state a maximum output for Grok 4.7, so it is recorded as unknown rather than inferred
• That page does not explicitly list image input for this model either, so it is catalogued as text-only