Claude Opus 5 vs GPT-6 Astra

Where it leads

• Lower input and output prices, $5 and $25 vs $10 and $50 per 1M tokens
• Higher Arena Text score, 1492 Elo vs 1476 Elo
• Cheaper cached input, $0.50 vs $1 per 1M tokens
• Batch pricing, $2.50 input and $12.50 output per 1M tokens

Best for

• Complex agentic coding and enterprise work as the general-purpose default before reaching for Fable 5.1
• Latency-sensitive work that can justify Fast mode pricing

Watch out for

• Fast mode pricing applies to the whole request, including above 200K input tokens, so it doubles the effective rate rather than adding a surcharge
• Cache reads are $0.50 per million (the standard 0.1x), five times Fable 5.1’s $0.25, even though Opus 5 is the cheaper model on base tokens. A cache-heavy agent loop can invert the expected cost ordering between the two.

Where it leads

• Higher Arena WebDev score, 1773 Elo vs 1691 Elo
• Higher FrontierMath Tiers 1-3 (v2) score, 93.7% vs 85.6%
• Higher GPQA Diamond score, 95.8% vs 93.9%
• Higher SimpleQA Verified score, 75.6% vs 59.9%
• Larger context window 1,050,000 vs 1,000,000 tokens

Best for

• Frontier reasoning and agentic evaluations where deep-context retrieval accuracy is the binding constraint
• Workloads that can be kept under the long-context threshold, where the effective rate stays at $10 / $50

Watch out for

• Long-context billing is a cliff, not a taper: a request over the long-context threshold is rebilled in full at $20 per million input and $75 per million output, so a prompt that crosses it costs roughly double
• GPT-6 Astra is the first publicly released model OpenAI classifies as crossing the Critical cybersecurity threshold under its own Preparedness Framework, which carries additional deployment safeguards
• Vendor-reported benchmark figures come from OpenAI’s own launch material and its own harness; they are not independently reproduced here