Claude Opus 4.8
Explore benchmark scores, genre strengths, weaknesses, and recent examples for Claude Opus 4.8 on Orivel.
Model Overview
Released
2026-05-28
Context
1M tokens
Input
$5.00 / 1M
Output
$25.00 / 1M
Claude Opus 4.8, released May 28, 2026, was Anthropic's flagship until Claude Fable 5 took the top spot on June 9, 2026. It held Orivel's Anthropic balanced slot until Claude Opus 5 replaced it at the identical price on July 24, 2026, and is now retired from new comparisons; past results stay published.
The headline gains over Opus 4.7 are sharper judgement, more honesty about its own progress, and the ability to work independently for longer. It is around four times less likely than its predecessor to let flaws in its own code pass unremarked, and it leads on agentic software engineering, scoring 69.2% on SWE-Bench Pro ahead of GPT-5.5 and Gemini 3.1 Pro.
The model keeps the 1M-token context window and up to 128k tokens of output on the Messages API. Pricing is unchanged from Opus 4.7 ($5 input / $25 output per 1M tokens), with a January 2026 knowledge cutoff. New surfaces add an `effort` control (defaults to high) and a Dynamic Workflows research preview for large, parallelized agentic tasks.
Retirement notes
- Released May 28, 2026 as the successor to Claude Opus 4.7 (about six weeks later)
- Sharper judgement, more honesty about its own progress, and longer independent work
- ~4x less likely than Opus 4.7 to let flaws in its own code pass unremarked
- SWE-Bench Pro 69.2% — ahead of GPT-5.5 and Gemini 3.1 Pro on agentic coding
- Gains across multidisciplinary reasoning, agentic computer use, and agentic financial analysis
- 1M-token context window; up to 128k output tokens on the Messages API
- `effort` parameter (defaults to high) to tune how hard the model works per response
- Dynamic Workflows research preview for large, parallel-subagent tasks; fast mode at 2.5x speed
- Pricing unchanged from Opus 4.7: $5 input / $25 output per 1M tokens
- Adaptive thinking; available across Claude API, Amazon Bedrock, Vertex AI, and Microsoft Foundry
- Knowledge and training data cutoff: January 2026
Overall Performance
Overall Rank
-
Overall win rate
Average Score
Wins
44
Sample Count
54
Win Rate by Model
Compare by Genre
Strong Genres
Creative Writing
Average Score
Genre Average
Win Rate
Sample Count
1
Genre Rank
3 / 15
Wins
1
Analysis
Average Score
Genre Average
Win Rate
Sample Count
1
Genre Rank
1 / 15
Wins
1
Business Writing
Average Score
Genre Average
Win Rate
Sample Count
2
Genre Rank
4 / 14
Wins
2
Counseling
Average Score
Genre Average
Win Rate
Sample Count
2
Genre Rank
2 / 16
Wins
2
Roleplay
Average Score
Genre Average
Win Rate
Sample Count
1
Genre Rank
4 / 14
Wins
1
Weaker Genres
Idea Generation
Average Score
Genre Average
Win Rate
Sample Count
1
Genre Rank
12 / 14
Wins
0
Brainstorming
Average Score
Genre Average
Win Rate
Sample Count
2
Genre Rank
9 / 14
Wins
1
Planning
Average Score
Genre Average
Win Rate
Sample Count
1
Genre Rank
9 / 13
Wins
0
Strength by Evaluation Criteria
Average score by criterion (out of 10)
Instruction Following
Safety
Faithfulness
Emotional Impact
Persona Consistency
Ethics & Safety
Appropriateness
Depth
Helpfulness
Empathy
Structure
Reasoning Quality
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