Scene illustration, not an output of this model
Model:
Price: 5 credits per 1K input tokens · ≈ $0.0025 · 24 credits per 1K output tokens · ≈ $0.012High stability with detailed usage records on the APIAny platform.
Prompt preset — no generated result yet
Sampling temperature.
Maximum output tokens.
Optional reasoning effort. Leave unset to use the model default. Higher effort can use more tokens and time.
USD estimate ≈ $0.0495: $999 tier: $1 = 2,000 credits.
History
Saved locally in this browser
0 running · 0 completed
Input
≈ $0.0025
Output
≈ $0.012
Cache
≈ $0.0003
Context
Max output
Authentication
Every request needs a Bearer token in the Authorization header. Create an API key in the console.
Authorization: Bearer YOUR_API_KEYhttps://apiany.ai/v1/chat/completionsRequest parameters
| Parameter | Type | Required | Notes |
|---|---|---|---|
model | string | Required | Model identifier to invoke. Use this model's ID. |
messages | array | Required | Conversation history in OpenAI chat format (role + content). |
stream | boolean | Optional | When true, the response streams back as server-sent events. |
Request example
curl "https://apiany.ai/v1/chat/completions" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "claude-opus-4-8",
"messages": [
{
"role": "user",
"content": "Review this fictional API design for ambiguity: POST /reports accepts {date,format}; response is {success:true,id}; GET /reports/:id returns either a file or {status:'working'}; time zone, valid formats, authorization, error codes and retention are unspecified. Prioritize clarifications and suggest a minimal consistent contract. Keep proposed choices distinct from supplied facts."
}
],
"temperature": 0.7,
"max_tokens": 4096,
"reasoning_effort": "high"
}'Response example
{
"id": "chatcmpl-abc123",
"object": "chat.completion",
"model": "claude-opus-4-8",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Hello! How can I help?"
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 12,
"completion_tokens": 18,
"total_tokens": 30
}
}Model overview
Anthropic Claude Opus 4.8 is a frontier model for demanding reasoning, large codebases, long-form analysis, and complex agent workflows.
Evaluate the model against reasoning depth, workflow fit, and production constraints before standardizing a route.
Claude Opus 4.8 is available on APIAny as one documented API surface with live pricing, model status, request examples, and an on-page playground. Teams can evaluate the model here, then keep authentication, usage records, and production routing in the same platform.
Try Claude Opus 4.8 in the playground
Sources
The quotations below are from official API documentation that APIAny implements against.
Send a structured list of input messages with text and/or image content, and the model will generate the next message in the conversation.
The Chat Completions API endpoint will generate a model response from a list of messages comprising a conversation.
Use cases
The Claude Opus 4.8 API is used for product workflows that need this model's output. Test the same inputs in the playground, compare related models, and choose the route that meets your quality, latency, and budget requirements.
01
Use Claude Opus 4.8 for repository analysis, implementation planning, code generation, review, and tool-assisted development. Provide clear constraints and validate generated changes with the same tests used by your engineering team.
Try Claude Opus 4.8 in the playground
02
Apply Claude Opus 4.8 to contracts, reports, research collections, and large technical documents. Structured prompts can extract evidence, compare sections, and produce summaries that retain links to the original context.
Try Claude Opus 4.8 in the playgroundAPIAny advantages
Claude Opus 4.8 on APIAny is a production route with one key, live prices, status, and usage records, so you do not maintain a separate provider integration.
Call Claude Opus 4.8 with an APIAny key and a documented request format. Keep your application integration stable while model versions and upstream routes evolve behind the gateway.
Review the live Claude Opus 4.8 pricing rules before a request, estimate credits in the playground, and inspect request-level usage records after the call completes.
Core capabilities
Claude Opus 4.8 API features are the input, output, and workflow traits that matter when you evaluate this model. Available request parameters remain visible in the live API reference on this page.
/01
Use Claude Opus 4.8 to break down multi-step problems, compare alternatives, and produce structured conclusions that can be reviewed.
/02
Apply Claude Opus 4.8 to implementation, debugging, refactoring, repository navigation, and technical explanation with test-based verification.
/03
Use a large context window for codebases, documents, conversation history, and multi-step instructions while monitoring token cost.
/04
Let Claude Opus 4.8 prepare or select tool calls while your application enforces permissions, validates arguments, and records actions.
Integration
Integrating the Claude Opus 4.8 API is a three-step path from playground test to authenticated production request. The page keeps the model identifier, request schema, pricing, and response examples together. Move from a representative prompt to monitored production traffic with explicit quality and fallback checks.
Sign in to APIAny, create a project API key, and assign only the model scope and budget controls your application needs.
Copy the request example from this page, set the model field to the selected Claude Opus 4.8 version, and send it to the documented APIAny endpoint.
Track status, latency, credits, and returned usage. Compare versions or related models with the same workload before shifting production traffic.
FAQ
Direct answers about capabilities, use cases, integration, and choosing the right Claude Opus 4.8 route.
Anthropic Claude Opus 4.8 is a frontier model for demanding reasoning, large codebases, long-form analysis, and complex agent workflows. APIAny makes this model callable through an authenticated API with live pricing, status information, request examples, and a browser playground on the same page.
Common Claude Opus 4.8 workflows include Coding agents and software delivery, Long-document analysis, Research and complex reasoning. The best fit depends on the input format, output quality, latency, and cost your product requires.
Create an APIAny key, use the endpoint documented on this page, and set the request model field to the selected Claude Opus 4.8 version. The playground can generate a working payload before you integrate it into application code.
03
Use Claude Opus 4.8 to decompose difficult questions, compare evidence, and produce decision-ready analysis. Ask the model to distinguish sourced facts, assumptions, and recommendations so reviewers can verify the result.
Try Claude Opus 4.8 in the playground
Use model status, channel health, retry policy, and usage logs to operate Claude Opus 4.8 as part of a production workflow instead of treating it as an isolated demo.
/05
Render supported Claude Opus 4.8 text output incrementally for interactive assistants and long-running generation tasks.
Compare the versions shown on this page by price, supported parameters, and capabilities such as Complex reasoning, Code generation and analysis, Long-context processing. Test a representative production input before choosing the default route.
