anthropic/claude-opus-4.7
1,000,000 context · $5.00/M input tokens · $25.00/M output tokens
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.
Pagamento por uso
Sem custo inicial, pague apenas pelo que usar
Use os exemplos de código abaixo para integrar com nossa 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.
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.
Input
$5 /M
Output
$25 /M
Context
1000K
Max Output
128K
Vision
Supported
Tool Use
Supported
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