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Claude Opus 4.7 (Adaptive Reasoning, Max Effort)

AnthropicClaudeProprietary

描述

Claude Opus 4.7 is Anthropic's latest Opus-class model, a direct upgrade to Opus 4.6 with notable improvements in advanced software engineering, particularly on the most difficult tasks. It handles complex, long-running agentic workflows with rigor and consistency, follows instructions more literally and precisely, and verifies its own outputs before reporting back. Substantially improved vision supports high-resolution images up to 2,576 pixels on the long edge (~3.75 megapixels, over 3x prior Claude models), unlocking dense screenshot reading, complex diagram extraction, and pixel-perfect references. Better file system-based memory enables coherent multi-session work. Introduces a new 'xhigh' effort level between 'high' and 'max' for finer control over the reasoning/latency tradeoff, and ships with task budgets (public beta) on the Claude Platform. Uses an updated tokenizer (inputs may map to ~1.0-1.35x more tokens than Opus 4.6). Released with automated safeguards that detect and block prohibited or high-risk cybersecurity uses. Available across Claude products, the Claude API, Amazon Bedrock, Google Cloud Vertex AI, and Microsoft Foundry. Pricing: $5/$25 per million tokens (input/output), unchanged from Opus 4.6.

發布日期
2026-04-16
參數規模
上下文長度
1.0M
支援模態
image, pdf, text

能力雷達圖

52
general
71
coding
91
reasoning
69
science
70
agents
80
multimodal

排行榜排名

領域#排名分數來源
智慧體能力模型榜12
64.0
LS
程式碼能力榜29
89.0
AA
通用能力榜35
82.0
AA
多模態榜10
64.0
LS
科學能力22
88.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Agents

BrowseCompOpenAI (2025)79.3%自報
OSWorld-Verified78.0%自報
MCP Atlas77.3%自報
CyberGym73.1%自報
Terminal-Bench 2.0Stanford × Laude Institute (2026)69.4%自報
Finance Agent64.4%自報
SWE-Bench ProPrinceton NLP (2024)64.3%自報
FrontierSWE63.0%
Finance Agent v251.5%
FrontierCode 1.138.5%
Legal Agent Benchmark7.1%

Biology

GPQANYU + Cohere + Anthropic (2023)94.2%自報

Code

SWE-Bench Verified87.6%自報

General

MMMLU91.5%自報
LiveBench76.9%

Math

Humanity's Last Exam54.7%自報

Multimodal

CharXiv-R91.0%自報

AA 評測指數

(Artificial Analysis)
Coding Index(Artificial Analysis)
73.6
Intelligence Index(Artificial Analysis)
55.0
Gpqa(NYU + Cohere + Anthropic (2023))
0.9
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.9
Terminalbench V2 1
0.8
Lcr(Artificial Analysis)
0.8
Ifbench(Google Research (2023))
0.6
Scicode(UIUC + Argonne National Lab (2024))
0.5
Terminalbench Hard(Stanford × Laude Institute (2026))
0.5
Hle(Center for AI Safety + Scale AI (2025))
0.4
Tau Banking
0.3

LLM Stats 分類評分

(LLM Stats (zeroeval))
Language
90
Physics
90
Frontend Development
90
Biology
90
Chemistry
90
Multimodal
80
Search
80
Long Context
70
Math
70
Reasoning
70
Safety
70
General
70
Code
70
Tool Calling
70
Vision
70
Finance
60
Agents
60
Healthcare
30
Legal
10

定價

輸入價格$5 / 1M tokens
輸出價格$25 / 1M tokens
混合價格(3:1)$10 / 1M tokens
快取讀取價格$0.5 / 1M tokens
快取寫入價格$6.25 / 1M tokens

速度

Tokens/秒0.0
首Token延遲0.00s
首回答延遲0.00s

供應商價格排行

供應商價格排行

1 個供應商

供應商輸入輸出
1Anthropic
$0.00001
$0.00003

比較該模型在不同 API 供應商之間的定價。

外部連結