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Documentation Index

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IO Intelligence supports models that can “think” before answering — exposing their step-by-step reasoning alongside the final response. You control this behavior with a single, OpenAI-compatible reasoning field on every chat completion request.

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Enable or disable reasoning

Add a reasoning object to your /v1/chat/completions payload: 
{
  "model": "moonshotai/Kimi-K2.6",
  "messages": [{ "role": "user", "content": "..." }],
  "reasoning": { "effort": "medium" }
}
effort valueBehavior
"none"Disable reasoning
"low"Enable reasoning, lighter thinking
"medium"Enable reasoning, balanced thinking
"high"Enable reasoning, deeper thinking
(field omitted)Use the model’s default behavior
The same field works for every model that supports reasoning — no per-model configuration required.

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Quickstart

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Enable reasoning (curl)

curl https://api.intelligence.io.solutions/api/v1/chat/completions \
  -H "Authorization: Bearer $IO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-ai/DeepSeek-V4-Pro",
    "messages": [
      { "role": "user", "content": "A farmer has 30 heads and 74 legs across his chickens and cows. How many of each?" }
    ],
    "reasoning": { "effort": "medium" }
  }'

​
Disable reasoning (curl)

curl https://api.intelligence.io.solutions/api/v1/chat/completions \
  -H "Authorization: Bearer $IO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "moonshotai/Kimi-K2.6",
    "messages": [
      { "role": "user", "content": "Just give me the number: what is 7 + 9?" }
    ],
    "reasoning": { "effort": "none" }
  }'

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Python (OpenAI SDK)

from openai import OpenAI
client = OpenAI(
    base_url="https://api.intelligence.io.solutions/api/v1",
    api_key="YOUR_IO_API_KEY",
)
# Enable reasoning
response = client.chat.completions.create(
    model="moonshotai/Kimi-K2.6",
    messages=[{"role": "user", "content": "Plan a 3-day Lisbon itinerary."}],
    extra_body={"reasoning": {"effort": "medium"}},
)
# Disable reasoning
response = client.chat.completions.create(
    model="moonshotai/Kimi-K2.6",
    messages=[{"role": "user", "content": "What is 7 + 9? Just the number."}],
    extra_body={"reasoning": {"effort": "none"}},
)

​
Node.js (OpenAI SDK)

import OpenAI from "openai";
const client = new OpenAI({
  baseURL: "https://api.intelligence.io.solutions/api/v1",
  apiKey: process.env.IO_API_KEY,
});
const response = await client.chat.completions.create({
  model: "moonshotai/Kimi-K2.6",
  messages: [{ role: "user", content: "Plan a 3-day Lisbon itinerary." }],
  // @ts-expect-error — reasoning is an IO Intelligence extension
  reasoning: { effort: "medium" },
});

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Reading the response

When reasoning is enabled, the model’s chain of thought is returned in choices[0].message.reasoning_content, and reasoning tokens are reported in usage.completion_tokens_details.reasoning_tokens: 
{
  "choices": [
    {
      "message": {
        "role": "assistant",
        "reasoning_content": "Let me set up two equations: c + w = 30 and 2c + 4w = 74...",
        "content": "23 chickens and 7 cows."
      }
    }
  ],
  "usage": {
    "completion_tokens": 65,
    "completion_tokens_details": { "reasoning_tokens": 48 }
  }
}
When reasoning is disabled ("effort": "none"):
  • reasoning_content is null or omitted
  • reasoning_tokens is 0 (or near-zero for models that always think internally)
  • The visible answer is in content only

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Streaming

Reasoning works with "stream": true as well. While the model is thinking, you’ll receive delta events with a reasoning_content field; once thinking finishes, regular content deltas follow. 
{ "choices": [{ "delta": { "reasoning_content": "Let me set up..." } }] }
{ "choices": [{ "delta": { "reasoning_content": " two equations..." } }] }
{ "choices": [{ "delta": { "content": "23 chickens" } }] }
{ "choices": [{ "delta": { "content": " and 7 cows." } }] }

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Backwards compatibility

  • Requests without the reasoning field continue to behave exactly as before.
  • The legacy reasoning_effort: "low" | "medium" | "high" top-level string is still accepted.
    You can safely roll out the new field at your own pace.

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Errors

StatusMeaning
400A small number of always-reasoning models reject effort: "none". Use a different effort or omit the field.
402The selected model requires a higher IO Intelligence tier.
429You’ve been rate-limited. Back off and retry.

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Models Enabled

The capability of reason enabling/disabling has been enabled for the following models:
ModelEnableDisableNotes
moonshotai/Kimi-K2.6✓✓Clean toggle
openai/gpt-oss-120b✓✓Always reasons internally; effort:"none" suppresses reasoning_content only
deepseek-ai/DeepSeek-V4-Pro✓✓Clean toggle
deepseek-ai/DeepSeek-V4-Flash✓✓
deepseek-ai/DeepSeek-V3.2✓✓Doesn’t always engage reasoning for trivial prompts
MiniMaxAI/MiniMax-M2.7✓N/AAlways-on reasoning by design, effort:"none" is a no-op for this model
google/gemma-4-26b-a4b-it——Reasoning routing in progress; check release notes before relying on it

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FAQs

No. Use reasoning.effort everywhere, IO Intelligence handles the rest.
Reasoning tokens are billed as completion tokens. none skips them entirely; low/medium/high each produce progressively more reasoning tokens. Exact budgets vary by model.
Yes, just don’t render reasoning_content in your UI. It’s returned as a separate field so you can choose whether to show it.
Yes. Reasoning happens before tool selection; the chain of thought explains why the model chose a particular tool call.