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Claude Opus 5

Up to 30%

Claude Opus 5 brings Anthropic conversational intelligence to LLM.API so teams can ship assistants and agents without juggling multiple vendor SDKs.

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What is Claude Opus 5?

Claude Opus 5 is an Anthropic chat model exposed on LLM.API under id `claude-opus-5`. Strongest Claude Opus model for coding, agents, and professional work. Teams use it when they need reliable text generation with text, image inputs and text outputs over an OpenAI-compatible API.

Providers

LLM.API routes Claude Opus 5 to the providers below, with discounted effective rates versus list price.

List price by provider ($ / 1M tokens)

InputOutput
anthropic$5 in
$25 out
aws-bedrock$5 in
$25 out
aws-mantle$5 in
$25 out

Provider list prices; the LLM.API discount applies on top.

ProviderPricingContextCapabilities
anthropic30% offin $5000; out — per 1M tokens1M tokensvision, tools, streaming, reasoning, web search, JSON, structured
aws-bedrock30% offin $5000; out — per 1M tokens1M tokensvision, tools, streaming, reasoning, web search, JSON
aws-mantle30% offin $5000; out — per 1M tokens1M tokensvision, tools, streaming, reasoning, web search, JSON

Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 21 Sept 2026.

Try this model

Test Claude Opus 5 right here — free to start.

Claude Opus 5
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call Claude Opus 5 through the OpenAI-compatible API — POST /v1/chat/completions.

python
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_LLMAP_KEY",
    base_url="https://api.llmapi.ai/v1",
)

resp = client.chat.completions.create(
    model="claude-opus-5",
    messages=[
        {"role": "system", "content": "You are a precise product assistant."},
        {"role": "user", "content": "Give me three crisp launch checklist items."},
    ],
)
print(resp.choices[0].message.content)
{
  "model": "claude-opus-5",
  "messages": [
    {"role": "system", "content": "You are a precise product assistant."},
    {"role": "user", "content": "Give me three crisp launch checklist items."}
  ]
}

5 Core Capabilities

  • Long-context synthesis

    Summarizes and cross-references information across large prompts when context allows. Relevant for `claude-opus-5` workloads on LLM.API.

  • Structured outputs

    Can produce JSON-friendly or schema-oriented responses when prompted carefully. Reflects Anthropic positioning for this endpoint.

  • Instruction following

    Follows detailed system and user instructions with strong adherence to format and tone. Tuned to how teams typically call Claude Opus 5.

  • Code assistance

    Helps write, explain, refactor, and debug application code across common languages. Tuned to how teams typically call Claude Opus 5.

  • Tool-ready dialogue

    Works well in agent loops that call functions, browsers, or retrieval APIs. Reflects Anthropic positioning for this endpoint.

6 Most Valuable Use Cases

  • Customer support copilots that draft accurate, on-brand replies with Claude Opus 5
  • Product analytics narration and anomaly explanations
  • Policy Q&A bots with careful refusal behavior with Claude Opus 5
  • Data extraction into JSON for downstream systems
  • Multilingual localization drafts for UX copy with Claude Opus 5
  • Coding agents for refactors, tests, and PR explanations

Why Build on LLM.API?

One unified API. Every major model. Built-in reliability, cost control, and observability.

  • Intelligent AI Routing

    Automatically route each request to the best model across providers based on latency, cost, and quality—without changing your integration or redeploying code.

    One endpoint, every model.

  • Cost-Aware Execution

    Control spend with per-request cost estimation, smart model selection, and centralized quotas so teams can experiment fast without runaway bills or manual tracking.

    More performance, less spend.

  • Resilient Fallback Flows

    Define automatic, provider-agnostic fallbacks to keep your app up during outages, rate limits, or timeouts—no brittle failover logic scattered through your codebase.

    Never go dark on users.

  • Deep LLM Observability

    Trace every call across providers with logs, metrics, and request replay so you can debug, tune prompts, and optimize model choices from one unified dashboard.

    See every token, everywhere.

  • Task-Level Orchestration

    Describe tasks, not models. LLM.API maps them to the right tools, models, and prompts so you ship complex AI workflows with minimal glue code.

    Think tasks, not models.

  • High-Throughput Batch APIs

    Process millions of inferences efficiently with optimized batch pipelines, concurrency controls, and retry logic—all behind the same simple interface you use for single calls.

    Scale from 1 to millions.

Why run Claude Opus 5 on LLM.API?

  • Unified AI Routing

    Reach Claude Opus 5 and sibling models through one OpenAI-compatible endpoint.

  • Cost Control

    Production: Compare provider price points and keep spend visible as you scale Claude Opus 5.

  • Reliability Layer

    Retry and route across configured providers when a single upstream blips.

  • Observability

    Trace prompts, tokens, and errors for Claude Opus 5 alongside the rest of your stack.

  • Drop-in SDKs

    Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.

  • Model Breadth

    Swap Claude Opus 5 for chat, media, or embedding alternatives without rewriting auth.

When to Use — When NOT to Use

Use it if...

  • Your prompts benefit from the model's family strengths (reasoning, speed, or cost) (Claude Opus 5)
  • You want OpenAI-compatible chat completions through a single LLM.API key (Claude Opus 5)
  • You need provider failover options exposed for this model id (Claude Opus 5)
  • You need a general-purpose text model for assistants, agents, or content workflows (Claude Opus 5)

Avoid if...

  • Your use case depends on unpublished proprietary benchmarks not listed here
  • You require on-prem only deployment with no cloud inference
  • You need guaranteed real-time hard latency SLAs without benchmarking the provider
  • You need pure embedding, OCR, or media generation instead of chat

BENCHMARKS

Claude Opus 5 benchmark scores

Intelligence index

This model51.
Tracked median24.

Scale: 0-100 index points

Output speed

This model52 t/s

Scale: 0-400 tokens per second

Reference price per 1M tokens

Input$5.00
Output$25.00

Bars compare input and output list prices for this model.

Artificial Analysis Intelligence Index51
Median index across all tracked models24
Output speed52 tokens/s
Reference input price$5.00 / 1M tokens
Reference output price$25.00 / 1M tokens

Independent scores published by Artificial Analysis (source). Reference prices are provider list prices, not LLM.API pricing.

RELIABILITY

Claude Opus 5 uptime, last 30 days

30-Day Uptime
97.55%
Past Incidents (30d)
13
Error rate (24h)
8.20%

Last 30 days

19/30 days operational | 97.55% uptime

Availability tracked for this model. Full history on the LLM Uptime Status page or the status hub. LLM.API routes around provider outages automatically.

COMMUNITY

What developers say about Claude models

Summarised from publicly published developer and community reviews of this model family. Opinions are the sources’, not LLM.API’s, and may not be specific to Claude Opus 5.

  • Reviewers consistently rank the Opus tier at or near the frontier for coding and agentic work, and several note the price/performance gap to rivals has narrowed.
  • A recurring complaint in community round-ups is verbosity — strong reasoning, but long answers and heavy token use unless you constrain output.
  • Teams report the Sonnet/Haiku tiers as the practical default for volume, keeping Opus for planning and hard debugging.

SOURCES

Frequently Asked Questions

  • How is Claude Opus 5 priced on LLM.API?

    Listed pricing metadata shows: In $5.00 / 1M tokens · Out $25.00 / 1M tokens. LLM.API may offer discounted effective rates (illustrative ~30% callout vs list when available).. Confirm live rates in the LLM.API dashboard or docs before production budgeting.

  • What is Claude Opus 5?

    Strongest Claude Opus model for coding, agents, and professional work. On LLM.API it is addressed as `claude-opus-5`.

  • What are limitations of Claude Opus 5?

    Like other API models, Claude Opus 5 can be wrong, incomplete, or uneven on edge cases. Validate outputs for high-stakes use. Media/OCR/STT models additionally depend on input quality.

  • Where is the canonical page for Claude Opus 5?

    https://llmapi.ai/models/anthropic-claude-opus-5/

  • Does Claude Opus 5 support streaming?

    Yes—at least one listed provider advertises streaming.

  • Which providers serve Claude Opus 5?

    LLM.API currently lists: anthropic, aws-bedrock, aws-mantle. Availability can vary by region and account.

  • Is Claude Opus 5 a chat model?

    Yes—Claude Opus 5 is exposed as a chat/completions-style endpoint on LLM.API.

  • When should I choose Claude Opus 5?

    You need provider failover options exposed for this model id — especially when you specifically need Claude Opus 5.

  • What is the context length for Claude Opus 5?

    Reported context for Claude Opus 5 is 1M tokens. Always verify the active provider row if multiple providers are listed.

  • Can I use tools or structured outputs with Claude Opus 5?

    Tool and/or structured-output flags appear on one or more providers for this model—confirm in the providers table.

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