anthropic/claude-opus-4.7
1,000,000 context · $5.00/M input$4.50/M input · $25.00/M output$22.50/M output10% off
Opus 4.7 is Anthropic's latest and most capable Opus model, designed for autonomous agents that operate across long-running, multi-step workflows. It builds on Opus 4.6 with significant gains in agentic coding — scoring 64.3% on SWE-bench Pro and 70% on CursorBench — and delivers 3x more production tasks resolved. The model excels at large codebase navigation, complex refactors, multi-stage debugging, and end-to-end project execution over extended sessions.Beyond engineering, Opus 4.7 shows strong knowledge work performance — document drafting, presentation building, and data analysis — with near-production-ready output in a single pass. It maintains coherence across very long outputs and supports high-resolution vision up to 3.75 megapixels with 98.5% visual acuity.
按用量付費
無需預付費用,僅按實際使用量付費
使用以下程式碼範例整合我們的 API:
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="anthropic/claude-opus-4.7",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)Opus 4.7 is Anthropic's most capable generally available model, released on April 16, 2026. It delivers a 13% lift on coding benchmarks, 3x more production tasks resolved, and near-perfect vision accuracy at 98.5% — all at the same pricing as Opus 4.6. The model is purpose-built for long-horizon agentic work, complex software engineering, and sustained knowledge tasks that require deep reasoning and self-verification.
Beyond coding, Opus 4.7 introduces high-resolution vision support up to 3.75 megapixels (3x the previous limit), a new xhigh effort level for finer quality-cost control, and stricter instruction following that makes it more predictable in production. It scores 64.3% on SWE-bench Pro (up from 53.4%), 70% on CursorBench (up from 58%), and leads on agentic benchmarks ahead of GPT-5.4 and Gemini 3.1 Pro.
| Benchmark | Opus 4.6 | Opus 4.7 | GPT-5.4 | Gemini 3.1 Pro |
|---|---|---|---|---|
| SWE-bench Pro | 53.4% | 64.3% | 57.7% | 54.2% |
| SWE-bench Verified | 80.8% | 87.6% | — | 80.6% |
| CursorBench | 58% | 70% | — | — |
| 93-task Coding Benchmark | Baseline | +13% | — | — |
| Production Tasks (Rakuten-SWE-Bench) | Baseline | 3x | — | — |
| Visual Acuity (Computer Use) | 54.5% | 98.5% | — | — |
| OfficeQA Pro (Document Reasoning) | Baseline | 21% fewer errors | — | — |
| Multi-step Workflows | Baseline | +14%, 1/3 fewer tool errors | — | — |
| Specification | Value |
|---|---|
| Provider | Anthropic |
| Model Type | Large Language Model (LLM) |
| Architecture | Transformer (Adaptive Thinking) |
| Context Window | 1000000 tokens |
| Max Output | 128000 tokens |
| Input | Text, Image |
| Output | Text |
| Vision | Supported (up to 3.75MP) |
| Function Calling | Supported |
| Effort Levels | low, medium, high, xhigh, max |
| Release Date | April 16, 2026 |
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $5.0 |
| Output | $25.0 |
Note: Opus 4.7 ships with an updated tokenizer that may produce 1.0–1.35x more tokens depending on content type. The per-token price is unchanged, but effective cost may increase up to 35% for certain content (structured data, code). Benchmark your actual workloads before migrating at scale.
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: anthropic/claude-opus-4.7
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="anthropic/claude-opus-4.7",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)
curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "anthropic/claude-opus-4.7",
"messages": [{"role": "user", "content": "Hello!"}]
}'
| Aspect | Opus 4.6 | Opus 4.7 |
|---|---|---|
| Coding (93-task) | Baseline | +13% |
| Production Tasks | Baseline | 3x more resolved |
| Visual Acuity | 54.5% | 98.5% |
| Max Image Resolution | ~1.25MP | 3.75MP (3x) |
| Effort Levels | low/medium/high/max | + xhigh (new) |
| Task Budgets | — | Public Beta |
| Instruction Following | Standard | Stricter, more literal |
| Tokenizer | v1 | Updated (1.0–1.35x more tokens) |
| Pricing | $5/$25 | $5/$25 (unchanged) |
Sources: Anthropic official release, felloai.com, nxcode.io, thenextweb.com. Content was rephrased for compliance with licensing restrictions.
anthropic/claude-opus-4.7
Opus 4.7 is Anthropic's latest and most capable Opus model, designed for autonomous agents that operate across long-running, multi-step workflows. It builds on Opus 4.6 with significant gains in agentic coding — scoring 64.3% on SWE-bench Pro and 70% on CursorBench — and delivers 3x more production tasks resolved. The model excels at large codebase navigation, complex refactors, multi-stage debugging, and end-to-end project execution over extended sessions.Beyond engineering, Opus 4.7 shows strong knowledge work performance — document drafting, presentation building, and data analysis — with near-production-ready output in a single pass. It maintains coherence across very long outputs and supports high-resolution vision up to 3.75 megapixels with 98.5% visual acuity.
輸入
$5$4.50 /M
輸出
$25$22.50 /M
折扣
10% 折扣
上下文
1000K
最大輸出
128K
Vision
支援
工具調用
支援
WaveSpeedAI 定價:輸入每百萬 token $4.50,輸出每百萬 token $22.50。Prompt 快取與批次處理分別計費,可顯著降低長上下文、高重複任務的實際成本。
Claude Opus 4.7 每次請求最多支援 1000K 上下文 token,輸出最多 128K token。
是的。WaveSpeedAI 透過 https://llm.wavespeed.ai/v1 的 OpenAI 相容端點提供 Claude Opus 4.7。將官方 OpenAI SDK 的 base URL 指向該位址,使用 WaveSpeedAI 的 API Key 即可,無需其他程式碼變更。
登入 WaveSpeedAI,在 Access Keys 建立 API Key,使用上方顯示的 model id 向 https://llm.wavespeed.ai/v1/chat/completions 發送請求。新帳號將獲得免費額度,用於試用 Claude Opus 4.7。