Anthropic

Claude 4 Opus

Type
language model
Context
200K tokens
Max output
32K
Released
14 May 2025
Knowledge cutoff
March 2025
API string
claude-opus-4-20250514

Prices by provider

Provider Input, $ per 1M Output, $ per 1M In our data since
Jiekou.AI $13.5 $67.5 31 Jul 2026
NanoGPT $14.994 $75.004 31 Jul 2026
302.AI $15 $75 31 Jul 2026
Abacus.AI $15 $75 31 Jul 2026
Amazon Bedrock $15 $75 2 Aug 2026
Anthropic $15 $75 1 Aug 2026
Merge Gateway $15 $75 31 Jul 2026

Only the base tier and only per-token prices are shown. Batch, discounted and cached rates, as well as prices per image or per second of video, do not go into this table: they cannot stand in the same column as a price per million tokens.

The date in the last column is the day this price first entered our collection. The price may well be older: before that day we simply were not recording it. It has not changed since — otherwise a new row with a new date would stand in its place.

Measurement results

Task set Result Run conditions Measured by
Arena Score, programming 1,401.8 1,395–1,409 — —
Arena Score, long queries 1,401.79 1,395–1,409 — —
Arena Score, multi-turn dialogue 1,385.96 1,378–1,393 — —
Arena Score in Russian 1,380.6 1,369–1,392 — —
Arena Score in English 1,376.69 1,371–1,382 — —
Arena Score, hard prompts 1,375.85 1,370–1,381 — —
Arena Score, creative writing 1,374.61 1,366–1,383 — —
Arena Score, mathematics 1,373.35 1,362–1,384 — —
Arena Score, instruction following 1,372.89 1,366–1,379 — —
Arena Score, expert questions 1,371.29 1,359–1,384 — —
Arena Score, overall 1,364.57 1,360–1,369 — —
Arena Score in French 1,364.46 1,339–1,390 — —
Arena Score in Spanish 1,350.89 1,330–1,372 — —
Arena Score, text recognition in images 1,179.05 1,163–1,195 — —
Arena Score, working with images 1,175.62 1,163–1,189 — —
Arena Score, understanding diagrams 1,175.37 1,150–1,201 — —
MATH, difficulty level five 85.05 % · with a tuned harness Epoch evaluations
Creative writing (Lech Mazur’s evaluation) 83.6 % thinking budget: 16K lechmazur/writing Github repository
Aider Polyglot — code edits in six languages 72 % · with a tuned harness Aider LLM Leaderboards
SWE-bench Verified — fixing bugs in repositories 70.66 % · with a tuned harness Epoch evaluations
GPQA Diamond — graduate-level questions 68.35 % thinking budget: 16K · with a tuned harness Epoch evaluations
Mock AIME 2024–2025 — olympiad problems 64.41 % thinking budget: 27K · with a tuned harness Epoch evaluations
Fiction.LiveBench — holding a long context 61.1 % — Fiction.live leaderboard
SimpleBench — trick questions 50.56 % thinking budget: 12K SimpleBench Leaderboard
DeepResearch Bench — deep research 49 % thinking budget: 2K DeepResearchBench Leaderboard
GeoBench — locating a place from a photograph 49 % thinking budget: 32K GeoBench leaderboard
WeirdML — unusual machine learning tasks 43.4 % thinking budget: 16K WeirdML Leaderboard
Cybench — cybersecurity tasks 38 % · with a tuned harness Cybench leaderboard
ARC-AGI — generalising to unseen patterns 35.7 % thinking budget: 16K · with a tuned harness ARC Prize Leaderboard
ARC-AGI-2 8.61 % thinking budget: 16K —
GSO-Bench — code optimisation 6.9 % — GSO Leaderboard
Humanity’s Last Exam — expert-level questions 6.22 % — —
CritPt — physics problems 0.3 % — —