Claude 4.1 Opus (Non-reasoning)
Claude 4.1 Opus (Non-reasoning) is an API model from Anthropic. It’s positioned for general text tasks—work that benefits from iteration, not just one-shot answers.
Intelligence
Good
Speed
Slow
38 tok/s output
Cost
High
$18.75 in / $75.00 out
Context
200K
Up to 200,000 tokens
How are Intelligence, Speed & Cost bucketed?
Intelligence and Speed buckets are percentile ranks on
Artificial Analysis. Cost buckets are fixed dollar
thresholds keyed off output-token price ($/M out).
Intelligence
- Top 1%≤ 1%
- Top 5%≤ 5%
- Top 10%≤ 10%
- Good≤ 25%
- Medium≤ 50%
- Below avg> 50%
Speed
- Top 1%≥ 345 tok/s
- Top 5%≥ 237 tok/s
- Top 10%≥ 196 tok/s
- Good≥ 146 tok/s
- Medium≥ 90 tok/s
- Slow< 90 tok/s
Cost
- Freeopen weights · self-host
- Low< $1 / M out
- Moderate$1–5 / M out
- High≥ $5 / M out
Core Capabilities
Long Documents
Handles entire codebases, books, and multi-doc RAG.
Context Window
200k tokens
≈ 154+ pages
4k Chat 聊天
32k Long docs 长文档
128k Books 整本书
400k Multi-doc 多文档
1M Codebase 整个代码库
10M
200k
Availability
API
Available
Product / App
Not available
Open Source
Not released
Enterprise
Contact sales
Pricing Model
Pay per token
Input and output billed separately.
Pay-per-token Capability / Performance
Where this model sits relative to the middle 60% of models in the tree. All scores are 0–10 (higher is better).
Lower 20% Upper 80% This model
Context / memory
Context window size · log-scaled
6.0
9.0
6.7
Lower 20% 20th percentile — 20% of models score below this This model Where the current model lands Upper 80% 80th percentile — only 20% of models score above this
Percentile boundaries are computed across every model in the tree that reports the underlying benchmark for each capability.
What it feels like
- Mid-cycle refresh of Claude 4 — modest reasoning bumps.
- Sustains hours-long agent loops without losing the thread — testers ran Opus 4 on 7+ hour autonomous coding sessions
- Best-in-class for real-world software engineering at release; SWE-bench Verified gains over Claude 3.7 Sonnet
- Native MCP support makes tool-using agents noticeably more reliable in production
Best use cases
- AI-software-engineer products (Devin, Cursor, Cline) that need long-horizon autonomy
- Agentic workflows with tool use, file editing, and computer use
- Complex bug fixes that span multiple files / systems
Tools to try
Not ideal for
- High-volume chat or simple Q&A (use Sonnet or Haiku)
- Strictly latency-sensitive applications — Opus is slower
Model Evolution
Claude is Anthropic's language model family.