# Interleaved Thinking Supporty - Documentation

> For the complete documentation index, see [llms.txt](/llms.txt). Markdown is available with `Accept: text/markdown` and `.md` URL variants.

Source: /docs/guides/llm-interleaved-thinking

# Interleaved Thinking Supporty

Last Updated: 2025-12-03

Status: Supported (OpenAI-Compatible)

##

[​](#1-overview)

1. Overview

Interleaved Thinking is an advanced reasoning framework that enables models to perform explicit reasoning steps between tool calls.
Models with Interleaved Thinking can:

- Reflect on the current environment and tool outputs

- Decide the next action based on updated reasoning

- Maintain a continuous reasoning chain across multiple tool invocations

- Provide transparent, inspectable multi-step thinking through `reasoning_details` or `reasoning_content`

This capability transforms traditional function-calling into agent-level tool use, making complex workflows more accurate, reliable, and context-aware.
Novita fully supports Interleaved Thinking for all models that natively expose reasoning streams (e.g., MiniMax-M2 and other OpenAI-compatible reasoning models).

##

[​](#2-key-concepts)

2. Key Concepts

###

[​](#2-1-interleaving)

2.1 Interleaving

Instead of executing a single reasoning phase followed by a tool call, the model performs:

```
Reason → Tool Call → Observe → Reason → Tool Call → ...
```

This allows the model to adjust its strategy dynamically based on previous tool outputs.

###

[​](#2-2-reasoning-details-reasoning_details)

2.2 Reasoning Details (`reasoning_details`)

For some models, the content of the model’s thinking will be returned in the form of a separate structure:

```
"reasoning_details": [
{
"type": "reasoning.text",
"format": "openai-responses-v1",
"text": "Model’s step-by-step reasoning..."
}
]
```

For such models, Novita supports returning this field in both streaming and non-streaming modes.

###

[​](#2-3-conversation-memory-requirement)

2.3 Conversation Memory Requirement

To maintain reasoning continuity: You must append the model’s full response including `reasoning_details`, `tool_calls`, and `content` to subsequent `messages`.
Failing to preserve the chain may result in:

- Incorrect tool use

- Lost reasoning context

- Repeated or circular tool calls

- Reduced reliability

This requirement mirrors OpenAI’s reasoning APIs.

##

[​](#3-api-behavior)

3. API Behavior

###

[​](#3-1-request-format)

3.1 Request Format

No changes are required on the user side.
Interleaved Thinking works with the standard OpenAI-compatible Chat Completions API.

###

[​](#3-2-response-format)

3.2 Response Format

The model may return the following fields:

- `reasoning_content`: original thinking content

- `reasoning_details`: structured reasoning segments, this field is optioanl

- `tool_calls`: tool invocation plan

- `content`: natural language output

These extend the standard OpenAI format.

##

[​](#4-example-request-minimax-m2)

4. Example Request (MiniMax-M2)

```
{
"model": "minimax/minimax-m2",
"messages": [
{
"role": "user",
"content": "How's the weather in San Francisco?"
},
{
"role": "assistant",
"name": "MiniMax AI",
"content": "",
"tool_calls": [
{
"id": "call_function_asqvfevfc8af_1",
"type": "function",
"function": {
"name": "get_weather",
"arguments": "{\"location\": \"San Francisco, US\"}"
}
}
],
"reasoning_details": [
{
"type": "reasoning.text",
"id": "reasoning-text-1",
"format": "openai-responses-v1",
"index": 0,
"text": "The user is asking about the weather in San Francisco..."
}
]
},
{
"role": "tool",
"tool_call_id": "call_function_asqvfevfc8af_1",
"content": "24℃, sunny"
}
],
"stream": true,
"reasoning_split": true,
"max_tokens": 1024,
"temperature": 0.7,
"tools": [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get weather for a specific location",
"parameters": {
"type": "object",
"properties": {
"location": { "type": "string" }
},
"required": ["location"]
}
}
}
]
}
```

##

[​](#5-example-response-non-streaming)

5. Example Response (Non-Streaming)

```
{
"id": "07a4dedfdb1498b045498dfd42497639",
"object": "chat.completion",
"created": 1764303147,
"model": "MiniMax",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "",
"name": "MiniMax",
"tool_calls": [
{
"index": 0,
"id": "call_function_9w7wq1j9zmpl_1",
"type": "function",
"function": {
"name": "get_weather",
"arguments": "{\"location\": \"ShangHai\"}"
}
}
],
"reasoning_content": "The user asked for Shanghai weather...",
"reasoning_details": [
{
"type": "reasoning.text",
"text": "The user is asking about the weather in Shanghai...",
"id": "reasoning-text-1",
"format": "openai-responses-v1",
"index": 0
}
]
},
"finish_reason": "tool_calls"
}
]
}
```

##

[​](#6-streaming-response-example)

6. Streaming Response Example

```
{
"id": "664c5ad870c1888fbcbd267d9829e354",
"object": "chat.completion.chunk",
"created": 1764303504,
"model": "minimax-m2",
"choices": [
{
"index": 0,
"delta": {
"role": "assistant",
"reasoning_content": "...\n\nThe user has specifically asked...",
"reasoning_details": [
{
"type": "reasoning.text",
"text": ".\n\nThe user has specifically asked...",
"id": "reasoning-text-1",
"format": "openai-responses-v1",
"index": 0
}
]
},
"finish_reason": null
}
]
}
```

##

[​](#7-developer-notes)

7. Developer Notes

###

[​](#7-1-models-that-support-interleaved-thinking)

7.1 Models That Support Interleaved Thinking

All models exposing `reasoning_details` through OpenAI-compatible APIs, including:

- MiniMax-M2

- (Upcoming) Novita Reasoning Series

- Other reasoning-enabled partner models

###

[​](#7-2-pricing)

7.2 Pricing

Billing is based on reasoning tokens, following the model’s pricing rules.
`reasoning_details` will increase token usage.

###

[​](#7-3-error-handling)

7.3 Error Handling

You may encounter:

- Missing tool parameters

- Recursive or repeated tool calls

- Incorrect assumptions in the reasoning phase

Ensure your application validates tool arguments and handles model errors gracefully.

##

[​](#8-best-practices)

8. Best Practices

✓ Always include full model messages in the next request
Include:

- `content`

- `tool_calls`

- `reasoning_details`

✓ Enable streaming for long-chain reasoning
Streaming allows the client to:

- Monitor the reasoning process

- Detect incorrect tool plans early

- Provide faster user feedback

✓ Combine with server-side state machines for stability
For production systems, we recommend pairing Interleaved Thinking with deterministic guardrails, e.g.:

- Parameter validators

- Execution sandbox

- Maximum recursion safeguards

##

[​](#9-summary)

9. Summary

Interleaved Thinking significantly enhances multi-step reasoning and tool-use reliability:

- Transparent and inspectable step-wise reasoning

- Adaptive planning between tool invocations

- Stronger context retention across long workflows

- Fully compatible with OpenAI-style Chat Completions API

Novita will continue expanding support for advanced reasoning models, bringing agent-level intelligence to the API layer.

Last modified on December 4, 2025