Claude Opus 5
Explore benchmark scores, genre strengths, weaknesses, and recent examples for Claude Opus 5 on Orivel.
Model Overview
Released
2026-07-24
Input
$5.00 / 1M
Output
$25.00 / 1M
Claude Opus 5, released July 24, 2026, is Anthropic's model for complex agentic coding and enterprise work. On Orivel it takes the Anthropic balanced slot from Opus 4.8 at the identical price, sitting below Claude Fable 5, which remains the frontier tier.
Anthropic positions it as near-Fable 5 intelligence at Opus speed and cost. It scores 96.0% on SWE-bench Verified (averaged over five trials), 79.2% on SWE-bench Pro, and 89.5% on SWE-bench Multilingual. On Frontier-Bench v0.1 it more than doubles Opus 4.8's result, and on ARC-AGI 3 it scores about three times the next-best competitor. It exceeds Fable 5's best OSWorld 2.0 result at one third of the cost.
The model has a 1M-token context window and up to 128k tokens of output, with a May 2026 knowledge cutoff — the most recent of any current Claude model. Pricing is unchanged from Opus 4.8 at $5 input / $25 output per 1M tokens. Adaptive thinking is on by default (a change from Opus 4.8), and sampling parameters such as temperature are no longer accepted.
What changed
- Released July 24, 2026 for complex agentic coding and enterprise work
- SWE-bench Verified 96.0% (5-trial average); SWE-bench Pro 79.2%; SWE-bench Multilingual 89.5%
- Frontier-Bench v0.1: more than double Opus 4.8's score; ARC-AGI 3: ~3x the next-best competitor
- Beats Fable 5's best OSWorld 2.0 result at one third of the cost
- Gains on scientific research: +10.2 points on organic chemistry, +7.7 points on protein prediction vs Opus 4.8
- 1M-token context window; up to 128k output tokens
- Adaptive thinking ON by default (Opus 4.8 required opting in); temperature / top_p / top_k no longer accepted
- Full effort range including `max`; fast mode available at 2.5x speed
- Pricing unchanged from Opus 4.8: $5 input / $25 output per 1M tokens
- Knowledge cutoff: May 2026
Overall Performance
Overall Rank
#1
Overall win rate
Average Score
Wins
16
Sample Count
17
Win Rate by Model
Compare by Genre
Strong Genres
System Design
Average Score
Genre Average
Win Rate
Sample Count
1
Genre Rank
1 / 15
Wins
1
Idea Generation
Average Score
Genre Average
Win Rate
Sample Count
1
Genre Rank
2 / 15
Wins
1
Humor
Average Score
Genre Average
Win Rate
Sample Count
1
Genre Rank
1 / 14
Wins
1
Discussion
Average Score
Genre Average
Win Rate
Sample Count
10
Genre Rank
1 / 16
Wins
10
Creative Writing
Average Score
Genre Average
Win Rate
Sample Count
1
Genre Rank
5 / 16
Wins
1
Strength by Evaluation Criteria
Average score by criterion (out of 10)
Completeness
Instruction Following
Trade-off Reasoning
Scalability & Reliability
Helpfulness
Specificity
Architecture Quality
Empathy
Audience Fit
Style Quality
Usefulness
Persuasiveness
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