Claude Opus 4.8 vs Claude Sonnet 5: which do you actually need?
Claude Opus 4.8 costs 2.5x Claude Sonnet 5 on both input and output pricing — $5.00 vs $2.00 per million input tokens, $25.00 vs $10.00 per million output tokens. Same provider, same 1M context window, same tokenizer. At 100M input/30M output tokens a month, that's $1,250 for Opus versus $500 for Sonnet 5. The gap is purely about task complexity, not features.
Verified · pricing checked against Anthropic's own API documentation| Model | Input /1M | Output /1M | Context |
|---|---|---|---|
| Claude Opus 4.8 | $5.00 | $25.00 | 1M tokens |
| Claude Sonnet 5 | $2.00* | $10.00* | 1M tokens |
* Sonnet 5 introductory rate through 31 Aug 2026. Standard rate from 1 Sep 2026: $3.00/$15.00 per 1M.
The output price gap
Output tokens are where the real cost divergence happens: Opus 4.8 charges 2.5x Sonnet 5's rate on output specifically, which matters most for workloads that generate long responses — reports, drafted content, extensive code. For input-heavy tasks like document analysis or classification, the gap is proportionally the same but the absolute dollar difference is smaller.
Worked example
At 100M input tokens and 30M output tokens a month — a realistic mid-size production workload — Opus 4.8 costs $1,250/month. Sonnet 5 costs $500/month at the current introductory rate (rising to $750/month after 1 September). That's a $750/month gap today, narrowing to $500/month once Sonnet 5's standard rate kicks in.
How we'd actually decide
Default to Sonnet 5. Reach for Opus 4.8 specifically when a task involves multi-step agentic reasoning, complex code review where mistakes are expensive to catch downstream, or genuinely difficult analysis where the extra capability measurably changes the output quality — not as a blanket "use the best model" policy. Most production workloads, including most coding assistance and content generation, don't need the premium.
Pricing verified 15 July 2026, non-cached list pricing. Use the calculator with your own volume for an exact estimate.