Claude Opus 4.8 — API Pricing & Benchmarks

Claude Opus 4.8 is Anthropic's previous-generation reasoning model, released in 2026-05. The API costs $5.00 per 1M input tokens and $25.0 per 1M output tokens ($10.0 blended at a 3:1 ratio), with cached input at $0.50. It supports a 1M-token context window. On the independently measured Artificial Analysis Intelligence Index it scores 57.3, ranking #13 of 68 models tracked on this site, with a median output speed of 63 tokens/sec.

Explore provider routes and additional benchmark sources for Claude Opus 4.8

ProviderAnthropic
Input price / 1M tokens$5.00
Output price / 1M tokens$25.0
Cached input / 1M tokens$0.50
Blended price (3:1)$10.0
Context window1M
Max output tokens128K
Knowledge cutoff2026-01
Licenseproprietary
Input modalitiesT+I
Output speed (tok/s)63
Released2026-05
Artificial Analysis Intelligence Index57.3
LMArena Elo1461
GPQA Diamond92%
AIME98.3%*
SWE-bench Verified88.6%*
Humanity's Last Exam48.7%

Where Claude Opus 4.8 fits

On a blended 3:1 basis Claude Opus 4.8 costs $10.0 per 1M tokens, cheaper than 8% of the 80 priced models in this index. It is a previous-generation model: usually only worth choosing if you have an existing integration, negotiated pricing, or need its specific behavior, since newer siblings offer better price-performance. Measured output speed of 63 tokens/sec is below the index median of 104 — typical of reasoning-heavy models, and worth checking against interactive latency budgets. Cached input is priced at $0.50 (90% below standard input), which rewards prompt structures with long stable prefixes — see our caching guide.

Price history

PeriodInput $/1MOutput $/1MCached $/1M
2026-07-18 → current$5.00$25.0$0.50

No list-price changes recorded since tracking began. Full dataset: price-history.json (CC BY 4.0).

Alternatives at a similar price

About Anthropic

Anthropic builds the Claude family, organized into Opus (flagship), Sonnet (mid-tier) and Haiku (small) tiers alongside the Fable line. Claude models currently lead the Artificial Analysis Intelligence Index and are particularly strong on agentic-coding benchmarks such as SWE-bench Verified.

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