Claude Opus 4
Claude Opus 4 is a coding model from Anthropic with strong benchmark scores, including 72.5% on SWE-bench Verified and 43.2% on Terminal-bench, with sustained performance on multi-hour agentic tasks and hybrid extended thinking with tool use.
View API reference- Input and output price
- Input $15, Output $75, Per 1M tokens
- 24h uptime
- Loading AI Gateway uptime
import { streamText } from 'ai'
const result = streamText({ model: 'anthropic/claude-opus-4', prompt: 'Why is the sky blue?'})Copy link to headingPlayground
Try out Claude Opus 4 by Anthropic. Usage is billed to your team at API rates. Free users (those who haven't made a payment) get $5 of credits every 30 days.
Claude Opus 4
Claude Opus 4
Copy link to headingProviders
Route requests across multiple providers. Copy a provider slug to set your preference. Visit the docs for more info. Using a provider means you agree to their terms, listed under Legal.
Copy link to headingUptime24 hours
Direct request success rate on AI Gateway and per-provider. Visit the docs for more info.
Copy link to headingThroughput24 hours
P50 throughput on live AI Gateway traffic, in tokens per second (TPS). Visit the docs for more info.
Copy link to headingLatency24 hours
P50 time to first token (TTFT) on live AI Gateway traffic, in milliseconds. View the docs for more info.
Getting started
Call Claude Opus 4 through AI Gateway with the AI SDK generateText and streamText functions, or through the OpenAI Chat Completions, OpenAI Responses, and Anthropic Messages APIs by changing the base URL. AI Gateway authenticates the request and routes it to an available provider.
Install the AI SDK (pnpm add ai dotenv), create an API key from the API Keys page, and set it as AI_GATEWAY_API_KEY in your environment. Full setup is covered in the text generation quickstart.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'anthropic/claude-opus-4', prompt: 'Why is the sky blue?', });
console.log(result.text);}
main().catch(console.error);Top-level parameters
The same Claude Opus 4 request in each API format AI Gateway supports.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'anthropic/claude-opus-4', system: 'You are a concise technical assistant.', prompt: 'Summarize the tradeoffs between static generation and SSR.', maxOutputTokens: 1024, });
console.log(result.text);}
main().catch(console.error);Standard parameters like prompt, messages, temperature, and tools work as documented in the AI SDK docs. These are the parameters with model-specific behavior.
| Parameter | Type | Required | Description |
|---|---|---|---|
model | string | Yes | Model ID in the form creator/model, e.g. anthropic/claude-opus-4. AI Gateway routes the request to an available provider. |
maxOutputTokens | number | No | Hard cap on generated tokens. Claude Opus 4 supports up to 8,192 output tokens. Reasoning tokens count toward this limit. |
reasoning | 'provider-default' | 'none' | 'minimal' | 'low' | 'medium' | 'high' | 'xhigh' | No | Provider-agnostic reasoning effort, available in AI SDK 7 or later. Maps to the provider’s native reasoning configuration; reasoning settings under providerOptions take precedence when both are set. See the Reasoning section below. |
providerOptions | Record<string, JSONValue> | No | AI Gateway routing options under gateway, plus any provider-native options under the provider’s own namespace — see the table below. |
Input limits
| Input | Formats | Sources | Max count | Max size | Limits |
|---|---|---|---|---|---|
| Text | — | — | — | — | Prompt and response share the 200K-token context window |
| Image | — | URL, base64, Uint8Array | — | — | Sent as image parts in messages; counts as input tokens |
| — | URL, base64, Uint8Array | — | — | Sent as file parts in messages; counts as input tokens |
Provider options
Set AI Gateway routing options under providerOptions.gateway. For provider-specific options, pass them under the provider’s namespace as documented by the AI SDK.
Learn more in the AI SDK anthropic provider docs.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'anthropic/claude-opus-4', prompt: 'Why is the sky blue?', providerOptions: { gateway: { only: ['vertexAnthropic'], }, }, });
console.log(result.text);}
main().catch(console.error);These AI Gateway routing options apply to every model. Provider-specific options pass through under the provider’s own namespace (for example providerOptions.anthropic) exactly as documented by the AI SDK.
| Parameter | Type | Required | Description |
|---|---|---|---|
providerOptions.gateway.only | string[] | No | Restrict routing to these provider slugs. Requests fail over only within the listed providers. |
providerOptions.gateway.order | string[] | No | Preferred provider order. Listed providers are tried first; unlisted providers remain available as fallbacks. |
providerOptions.gateway.sort | 'cost' | 'ttft' | 'tps' | No | Rank candidate providers by price, time to first token, or tokens per second instead of the default routing order. |
providerOptions.gateway.zeroDataRetention | boolean | No | Route only to providers with a zero-data-retention policy for this model. |
Routing across providers
AI Gateway serves the same model through multiple providers and fails over automatically. order expresses a preference while keeping every provider eligible; only is a hard allowlist — if none of the listed providers are available the request fails instead of falling back.
Options under a provider's own namespace (for example providerOptions.anthropic) are forwarded to that provider with the request. Providers ignore option namespaces that don't apply to them, so it is safe to set provider options alongside gateway routing options.
Reasoning
AI Gateway bridges reasoning across every API format. The AI SDK exposes a provider-agnostic top-level reasoning level (none, minimal, low, medium, high, or xhigh); the Chat Completions and Responses formats take the same effort under reasoning.effort; and the Anthropic Messages format uses a native thinking token budget. Whichever you send, the gateway maps it to the target model’s native configuration, converting between effort levels and token budgets as needed. Reasoning-related settings under providerOptions take full precedence over the top-level reasoning value and are never merged. Reasoning tokens typically count toward your output-token usage, though how they’re reported and billed varies by provider.
Learn more in the AI Gateway reasoning guide.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'anthropic/claude-opus-4', prompt: 'Explain the Monty Hall problem step by step.', reasoning: 'high', });
console.log(result.text);}
main().catch(console.error);Image input
Send images alongside text as message parts. Images count as input tokens.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'anthropic/claude-opus-4', messages: [ { role: 'user', content: [ { type: 'text', text: 'Describe this image.' }, { type: 'image', image: 'https://example.com/photo.jpg' }, ], }, ], });
console.log(result.text);}
main().catch(console.error);PDF input
Attach PDFs as file parts. Their contents count as input tokens.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'anthropic/claude-opus-4', messages: [ { role: 'user', content: [ { type: 'text', text: 'Summarize this document.' }, { type: 'file', mediaType: 'application/pdf', data: 'https://example.com/document.pdf', }, ], }, ], });
console.log(result.text);}
main().catch(console.error);Tool calling
Expose tools the model can call. Define each tool’s inputs with a Zod schema.
import { generateText, tool } from 'ai';import { z } from 'zod';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'anthropic/claude-opus-4', prompt: 'What is the weather in San Francisco?', tools: { getWeather: tool({ description: 'Get the current weather for a location', inputSchema: z.object({ location: z.string() }), execute: async ({ location }) => ({ location, temperatureC: 18 }), }), }, });
console.log(result.text);}
main().catch(console.error);Copy link to headingMore models by Anthropic
| Model |
|---|
| 1M | 1.4 s | 83 tps | $5/M+1 more | $25/M+1 more | Read$0.50/M Write$6.25/M | $10/K | +3 |  +1 | 07/24/2026 | |||||
| 1M | 1.5 s | 116 tps | $2/M | $10/M | Read$0.20/M Write$2.50/M | $10/K | +3 | +1 | 06/29/2026 | |||||
| 1M | 1.1 s | 104 tps | $5/M+1 more | $25/M+1 more | Read$0.50/M Write$6.25/M | $10/K | +3 | +1 | 05/28/2026 | |||||
| 1M | 0.8 s | 74 tps | $3/M | $15/M | Read$0.30/M Write$3.75/M | $10/K | +3 | +1 | 02/17/2026 | |||||
| 1M | 1.2 s | 53 tps | $5/M+1 more | $25/M+1 more | Read$0.50/M Write$6.25/M | $10/K | +3 |  | 02/05/2026 | |||||
| 200K | 0.5 s | 115 tps | $1/M | $5/M | Read$0.10/M Write$1.25/M | $10/K | +3 | +1 | 10/15/2025 |
Copy link to headingAbout Claude Opus 4
Claude Opus 4 launched on May 22, 2025 alongside Claude Sonnet 4. Anthropic positioned it for demanding coding workloads. The benchmark results: 72.5% on SWE-bench Verified and 43.2% on Terminal-bench. These scores were achieved without extended thinking, showing that Claude Opus 4's baseline capability advanced beyond previous models.
Sustained performance differentiated Claude Opus 4 most distinctly from its predecessors. Rakuten validated the model with a demanding open-source refactor that ran independently for seven hours with sustained performance, maintaining focus and coherence over hundreds of individual steps. Cursor called it strong for coding and a leap forward in complex codebase understanding. Block reported it was the first model to improve code quality during editing and debugging in their agent (codename goose) while maintaining full reliability. Cognition noted Claude Opus 4 handled critical actions that previous models had missed on complex challenges.
The Claude 4 launch introduced extended thinking with tool use in beta. Both Claude Opus 4 and Sonnet 4 can alternate between reasoning and tool use like web search during a single extended thinking session. This enables research patterns where the model searches, reasons about results, searches again based on that reasoning, and synthesizes across the full chain. Memory capabilities also improved substantially: when given local file access, Claude Opus 4 creates and maintains memory files to store key information, enabling better long-term coherence on extended tasks.
The Claude 4 generation reduced shortcut-taking behavior by 65% compared to Sonnet 3.7 on agentic tasks particularly susceptible to that failure mode. This is an important reliability property for production agent deployments where gaming a metric rather than solving the underlying problem is a real risk.
Copy link to headingWhat To Consider When Choosing a Provider
- Configuration: Claude Opus 4's higher per-token cost and long-running session profile make AI Gateway cost tracking useful. Observability from the first request helps prevent budget surprises on multi-hour jobs.
- Zero Data Retention: Zero Data Retention is available for this model. It is offered on a per-provider and model basis. See the documentation for details.
- Authentication: AI Gateway authenticates requests using an API key or OIDC token. You do not need to manage provider credentials directly.
Copy link to headingWhen to Use Claude Opus 4
Best for
- Long-horizon agentic tasks: Sustained focus across thousands of steps and multiple hours, validated with a seven-hour independent refactor run
- Complex codebase understanding: Multi-file modification with SWE-bench 72.5% and Terminal-bench 43.2%
- Research and analysis workflows: Extended thinking with tool use, reasoning interleaved with web search or other external tools
- Scientific discovery and R&D: Analytical depth and domain knowledge are the binding constraints
- Production agent deployments: The 65% reduction in shortcut-taking behavior improves reliability
Consider alternatives when
- Per-token cost constraint: Sonnet 4 delivers strong performance at lower cost and matched or exceeded Claude Opus 4 on SWE-bench
- Critical response latency: Sonnet variants are faster for interactive use
- Shorter bounded tasks: The capability differential over Sonnet shrinks when multi-hour sustained attention isn't needed
- 1M context window: Came to Sonnet 4 later and to Opus models with version 4.6
Copy link to headingConclusion
Claude Opus 4 demonstrated sustained agentic performance at the Claude 4 generation's launch. It solves hard problems and maintains coherence over hours. Teams building long-horizon coding agents, research pipelines, or autonomous engineering workflows have concrete reference points in the benchmark data and early customer validation.
Copy link to headingFrequently Asked Questions
What SWE-bench and Terminal-bench scores did Claude Opus 4 achieve?
Opus 4 scored 72.5% on SWE-bench Verified and 43.2% on Terminal-bench, both without extended thinking.
How long can Claude Opus 4 run an agentic task without losing coherence?
Rakuten validated a seven-hour independent run on a demanding open-source refactoring task with sustained performance. Anthropic described the model as capable of working continuously for several hours.
What is extended thinking with tool use in Claude Opus 4?
A beta capability introduced with the Claude 4 launch. The model alternates between extended reasoning and tool calls within a single session. For example, it can think about a problem, run a web search, reason about the results, search again, and synthesize across the chain.
How did Claude Opus 4 improve memory capabilities?
When you provide local file access, Opus 4 creates and maintains memory files to store key facts and context. This enables better long-term coherence on extended tasks. Anthropic illustrated this with the model creating a navigation guide during autonomous Pokémon gameplay.
What was the shortcut-taking behavior reduction?
Claude 4 models (Opus 4 and Sonnet 4) are 65% less likely to use shortcuts or loopholes to complete agentic tasks compared to Sonnet 3.7. This is a reliability improvement for production deployments where you need the model to solve the actual problem rather than gaming the metric.
How does Opus 4 pricing compare to Sonnet 4?
Check the pricing panel on this page for today's numbers. AI Gateway tracks rates across every provider that serves Claude Opus 4.
Does Claude Opus 4 support thinking summaries?
Yes. A smaller model condenses lengthy thought processes into summaries. Anthropic noted this is only needed about 5% of the time, when thoughts are too long to display in full.
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