RotenAI
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Documents Models

Models for extracting, summarizing and reasoning over document content.

  • Document extraction
  • Report summaries
  • Contract review
  • Knowledge workflows
Performance candidate

Compare the recorded score and API price.

A

Claude Fable 5 High

Anthropic
Recorded Arena score149645 points above the cost candidateScore points do not measure real-world quality.
API price
$7.00Uncached input / 1M tokens
$35.00Output / 1M tokens
A candidate for evaluation; no absolute winner is claimed.

For native PDF input, contact Roten to confirm the request format. The examples here send document text.

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Lower-cost candidate

Consider the trade-off between cost and the recorded score.

K

Kimi K2.6

Moonshot AI
Recorded Arena score145145 Arena points lowerScore points do not measure real-world quality.
Token cost savings
−90.5%Input cost vs Claude Fable 5 High
$0.665Input / 1M tokens
−92%Output cost vs Claude Fable 5 High
$2.80Output / 1M tokens
45 Arena points lower · 90.5% lower input cost · 92% lower output cost

Document summaries and reasoning using extracted text.

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Prices apply to the stated model settings. Token input rates cover uncached input; output tokens are priced separately. Cache usage and image or video settings can change the charge.

Compare API support and prices.

Input formats, model capabilities and prices.

API capabilities and billing references for documents candidates
ReferenceClaude Fable 5 HighPerformance candidateKimi K2.6Cost candidate
Input → outputtext, image, document → texttext → text

Documents use extracted text, not native PDF uploads.

Uncached input / 1M tokens$7.00$0.665
Output / 1M tokens$35.00$2.80
Cost comparisonScoped price reference90.5% lower input cost · 92% lower output cost
Reference Arena score14961451
Billing detailsUncached input and output are priced separately per million tokens.Uncached input and output are priced separately per million tokens.

Implementation

Test your chosen model.

Copy an available model request, replace the API key with your own, and run.

API model ID: kimi-k2.6

Document summaries and reasoning using extracted text. Native PDF uploads are not supported by these examples.

Documents use extracted text, not native PDF uploads.

This example sends extracted or sample document text. Input format: text.

Copy the Python or cURL test for Kimi K2.6. Replace the API-key placeholder with your own key and run.

Document text test · The sample document is included in the request as text.

Kimi K2.6 · Python
import requests

response = requests.post(
    url="https://api.roten-ai.com/v1/chat/completions",
    headers={
        "Authorization": "Bearer YOUR_ROTEN_API_KEY",
    },
    json={
        "model": "kimi-k2.6",
        "messages": [
            {
                "role": "user",
                "content": "Summarize this sample project memo in two bullets.\n\nThe product team is evaluating an AI API for customer-support replies. The trial will compare response usefulness and request cost. Engineering will record the results before selecting a model."
            }
        ],
        "max_tokens": 256,
        "thinking": {
            "type": "disabled"
        },
        "stream": False
    },
    timeout=180,
)

print(response.json())
response.raise_for_status()

Python requires requests: install once with python3 -m pip install requests. cURL examples run directly in your terminal.

Evidence and limits

Understand the candidate selection.

Reference Arena scores, API tests and billing rates describe different aspects of each candidate.

Read the methodology

Built for production

Running AI at scale?

Talk to us about volume pricing, model selection and migration.

Talk to Sales