Anthropic

Claude 4.1 Opus

Type
language model
Context
200K tokens
Max output
32K
Released
5 August 2025
Knowledge cutoff
March 2025
API string
claude-opus-4-1-20250805

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 31 Jul 2026
Helicone $15 $75 31 Jul 2026
LLM Gateway $15 $75 31 Jul 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 1,473.09 1,468–1,478
Arena Score, long queries 1,445.19 1,440–1,450
Arena Score in Spanish 1,444.59 1,430–1,459
Arena Score, multi-turn dialogue 1,441.82 1,436–1,448
Arena Score, hard prompts 1,441.49 1,438–1,445
Arena Score, instruction following 1,433.82 1,429–1,439
Arena Score in English 1,428.72 1,425–1,433
Arena Score in French 1,427.47 1,410–1,445
Arena Score, expert questions 1,425.18 1,415–1,435
Arena Score in Russian 1,422.37 1,414–1,430
Arena Score, mathematics 1,421.84 1,413–1,430
Arena Score, overall 1,417.42 1,414–1,420
Arena Score, creative writing 1,410.22 1,404–1,416
Arena Score, web development 1,388.74 1,378–1,400
Creative writing (Lech Mazur’s evaluation) 84.7 % lechmazur/writing Github repository
SWE-bench Verified — fixing bugs in repositories 73.35 % · with a tuned harness Epoch evaluations
GPQA Diamond — graduate-level questions 69.7 % thinking budget: 27K · with a tuned harness Epoch evaluations
Mock AIME 2024–2025 — olympiad problems 68.86 % thinking budget: 27K · with a tuned harness Epoch evaluations
SimpleBench — trick questions 52 % SimpleBench Leaderboard
DeepResearch Bench — deep research 49.7 % DeepResearchBench Leaderboard
GDPval — tasks from real occupations 43.6 %
WeirdML — unusual machine learning tasks 42.76 % thinking budget: 16K WeirdML Leaderboard
Cybench — cybersecurity tasks 42 % · with a tuned harness Cybench leaderboard
Terminal-Bench — working in the command line 38 % · with a tuned harness Terminal-Bench v2 Leaderboard
SimpleQA Verified — factual accuracy 34.8 % thinking budget: 27K Epoch evaluations
FrontierMath, levels 1–3 12.63 % thinking budget: 32K Epoch evaluations
Humanity’s Last Exam — expert-level questions 7.06 %
FrontierMath, level 4 — research-grade problems 2.44 % thinking budget: 32K Epoch evaluations
Chess puzzles 2.15 % Epoch evaluations