> ## Documentation Index
> Fetch the complete documentation index at: https://docs.hicap.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Anthropic

> Anthropic Claude models available through the Hicap API

All Anthropic models below are accessible through the **Hicap API** using the standard [OpenAI API spec](https://platform.openai.com/docs/api-reference). Point your OpenAI SDK at `https://api.hicap.ai/v1` and use any model ID listed here. For pricing, see the [Model Catalog](https://hicap.ai/models).

## claude-opus-4.6

Claude Opus 4.6 is the latest and most capable Claude model, delivering state-of-the-art reasoning, coding, analysis, and creative output. It offers a 200K context window with efficient prompt caching for cost-effective processing of long inputs.

<div className="text-white font-bold">Best for:</div>

<div className="bg-gray-200 dark:bg-black px-3 py-1 mt-2">
  <span>
    Maximum-capability tasks: advanced agentic coding, deep research synthesis, complex multi-step reasoning, strategic analysis, and high-stakes content generation where quality and depth are paramount.
  </span>
</div>

| Input               |   | Output |
| ------------------- | - | ------ |
| `Text, Image, Code` |   | `Text` |

<Columns cols={1}>
  <div>
    <div className="text-white font-bold">This model offers</div>

    <ul className="mb-6">
      <li>\* 200,000 context window</li>
    </ul>
  </div>
</Columns>

## claude-sonnet-4.6

Claude Sonnet 4.6 is the latest mid-tier Claude model, offering strong reasoning, coding, and instruction following at an excellent cost-to-performance ratio. It balances intelligence and speed with a 200K context window.

<div className="text-white font-bold">Best for:</div>

<div className="bg-gray-200 dark:bg-black px-3 py-1 mt-2">
  <span>
    Enterprise copilots, production coding assistants, document analysis, structured reasoning, and general-purpose AI applications where strong performance at moderate cost is ideal.
  </span>
</div>

| Input               |   | Output |
| ------------------- | - | ------ |
| `Text, Image, Code` |   | `Text` |

<Columns cols={1}>
  <div>
    <div className="text-white font-bold">This model offers</div>

    <ul className="mb-6">
      <li>\* 200,000 context window</li>
    </ul>
  </div>
</Columns>

## claude-sonnet-4.5

Latest mid-to-high tier Claude model (successor to 3.5-Sonnet) that delivers near-Opus-level reasoning with much lower latency and cost. Strong in long-context comprehension (up to 200k+), precise writing, and multimodal analysis (text + image).

<div className="text-white font-bold">Best for:</div>

<div className="bg-gray-200 dark:bg-black px-3 py-1 mt-2">
  <span>
    Enterprise copilots, advanced coding and debugging, legal/financial document analysis, product and design QA, structured reasoning tasks. Ideal when you want high intelligence at practical scale.
  </span>
</div>

| Input               |   | Output |
| ------------------- | - | ------ |
| `Text, Image, Code` |   | `Text` |

<Columns cols={1}>
  <div>
    <div className="text-white font-bold">This model offers</div>

    <ul className="mb-6">
      <li>\* 200,000 context window</li>
      <li>\* 64,000 max output tokens</li>
      <li>\* January 1, 2025 knowledge cutoff</li>
    </ul>
  </div>
</Columns>

## claude-haiku-4.5

Lightweight, fastest Claude 4.5 variant, designed for real-time inference and very low compute cost. Maintains solid understanding and summarization abilities, but not deep reasoning.

<div className="text-white font-bold">Best for:</div>

<div className="bg-gray-200 dark:bg-black px-3 py-1 mt-2">
  <span>
    High-throughput chatbots, customer support automation, RAG summarizers, quick document Q\&A, or embedded assistants where speed and affordability matter most.
  </span>
</div>

| Input         |   | Output |
| ------------- | - | ------ |
| `Text, Image` |   | `Text` |

<Columns cols={1}>
  <div>
    <div className="text-white font-bold">This model offers</div>

    <ul className="mb-6">
      <li>\* 200,000 context window</li>
      <li>\* 64,000 max output tokens</li>
      <li>\* February 1, 2025 knowledge cutoff</li>
    </ul>
  </div>
</Columns>

## claude-sonnet-4

Extended version of Claude Sonnet 4V with ultra-long context support (beyond 200k tokens, up to \~1M depending on configuration). Maintains multimodal (text + images) while handling very large corpora.

<div className="text-white font-bold">Best for:</div>

<div className="bg-gray-200 dark:bg-black px-3 py-1 mt-2">
  <span>
    Deep document analysis (legal, technical, research) with embedded visuals, large-scale design system validation, long historical chat/session review, and knowledge-base copilots that need persistent memory across massive inputs.
  </span>
</div>

| Input               |   | Output |
| ------------------- | - | ------ |
| `Text, Image, Code` |   | `Text` |

<Columns cols={1}>
  <div />
</Columns>

## claude-opus-4.5

Claude Opus 4.5 is a high-end reasoning and language model designed for deep analysis, nuanced understanding, and carefully structured responses. It excels at handling complex instructions, long-form content, and sensitive or high-context tasks with a strong emphasis on clarity, safety, and interpretability.

<div className="text-white font-bold">Best for:</div>

<div className="bg-gray-200 dark:bg-black px-3 py-1 mt-2">
  <span>
    Deep reasoning, complex analysis, long-form writing, policy-heavy workflows, and high-stakes tasks where precision, context awareness, and thoughtful responses are essential.
  </span>
</div>

| Input         |   | Output |
| ------------- | - | ------ |
| `Text, Image` |   | `Text` |

<Columns cols={1}>
  <div>
    <div className="text-white font-bold">This model offers</div>

    <ul className="mb-6">
      <li>\* 200,000 context window</li>
      <li>\* 64,000 max output tokens</li>
      <li>\* May 2025 knowledge cutoff</li>
    </ul>
  </div>
</Columns>

## claude-opus-4.1

Claude Opus 4.1 is a drop-in replacement for Opus 4 that delivers superior performance and precision for real-world coding and agentic tasks. It handles complex, multi-step problems with more rigor and attention to detail.

<div className="text-white font-bold">Best for:</div>

<div className="bg-gray-200 dark:bg-black px-3 py-1 mt-2">
  <span>
    Strategic decision-making, in-depth research, advanced coding and debugging, legal/financial/technical analysis, high-stakes content generation (contracts, reports, product strategy docs). Best when quality > cost/latency.
  </span>
</div>

| Input               |   | Output |
| ------------------- | - | ------ |
| `Text, Image, Code` |   | `Text` |

<Columns cols={1}>
  <div>
    <div className="text-white font-bold">This model offers</div>

    <ul className="mb-6">
      <li>\* 200,000 context window</li>
      <li>\* 32,000 max output tokens</li>
      <li>\* March 1, 2025 knowledge cutoff</li>
    </ul>
  </div>
</Columns>

## claude-opus-4

Excels in deep reasoning, logical coherence, and creative writing. Handles complex instructions, long documents, and multimodal text+image analysis with high factual reliability. Slightly slower and more expensive than Sonnet models but provides top-tier accuracy.

<div className="text-white font-bold">Best for:</div>

<div className="bg-gray-200 dark:bg-black px-3 py-1 mt-2">
  <span>
    Strategic and analytical tasks where precision, reasoning depth, and interpretability matter most — e.g., legal or financial analysis, multi-step research, technical documentation, and advanced coding/debugging workflows.
  </span>
</div>

| Input               |   | Output |
| ------------------- | - | ------ |
| `Text, Image, Code` |   | `Text` |

<Columns cols={1}>
  <div>
    <div className="text-white font-bold">This model offers</div>

    <ul className="mb-6">
      <li>\* 200,000 context window</li>
      <li>\* 32,000 max output tokens</li>
      <li>\* March 1, 2025 knowledge cutoff</li>
    </ul>
  </div>
</Columns>

## claude-3.7-sonnet

Claude 3.7 Sonnet shows particularly strong improvements in coding and front-end web development. Along with the model, we’re also introducing a command line tool for agentic coding, Claude Code. Claude Code is available as a limited research preview, and enables developers to delegate substantial engineering tasks to Claude directly from their terminal.

<div className="text-white font-bold">Best for:</div>

<div className="bg-gray-200 dark:bg-black px-3 py-1 mt-2">
  <span>
    Agents with tools and deep reasoning with “extended thinking” and efficient tool use in tokens.
  </span>
</div>

| Input               |   | Output |
| ------------------- | - | ------ |
| `Text, Image, Code` |   | `Text` |

<Columns cols={1}>
  <div>
    <div className="text-white font-bold">This model offers</div>

    <ul className="mb-6">
      <li>\* 200,000 context window</li>
      <li>\* 64,000 max output tokens</li>
      <li>\* October 1, 2024 knowledge cutoff</li>
    </ul>
  </div>
</Columns>

## claude-3.5-sonnet

Mid-tier Claude 3.5 model offering strong reasoning, coding, and writing quality at a good cost-to-performance ratio. Supports image input (vision) and long context (200k tokens).

<div className="text-white font-bold">Best for:</div>

<div className="bg-gray-200 dark:bg-black px-3 py-1 mt-2">
  <span>
    General enterprise copilots, technical writing, product documentation, Figma/UI reviews, code explanation and debugging. Ideal when you need smart but affordable reasoning.
  </span>
</div>

| Input               |   | Output |
| ------------------- | - | ------ |
| `Text, Image, Code` |   | `Text` |

<Columns cols={1}>
  <div>
    <div className="text-white font-bold">This model offers</div>

    <ul className="mb-6">
      <li>\* 200,000 context window</li>
      <li>\* 8,192 max output tokens</li>
      <li>\* April 1, 2024 knowledge cutoff</li>
    </ul>
  </div>
</Columns>

## claude-3.5-haiku

Lightweight, fastest and cheapest Claude 3.5 variant. Lower reasoning depth but very low latency. Still capable of handling moderate context sizes and structured reasoning.

<div className="text-white font-bold">Best for:</div>

<div className="bg-gray-200 dark:bg-black px-3 py-1 mt-2">
  <span>
    Real-time assistants, chatbots, RAG queries, customer support, lightweight summarization, or any latency-sensitive app.
  </span>
</div>

| Input         |   | Output |
| ------------- | - | ------ |
| `Text, Image` |   | `Text` |

<Columns cols={1}>
  <div>
    <div className="text-white font-bold">This model offers</div>

    <ul className="mb-6">
      <li>\* 200,000 context window</li>
      <li>\* 8,192 max output tokens</li>
      <li>\* July 1, 2024 knowledge cutoff</li>
    </ul>
  </div>
</Columns>