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What is Inkling-Small?

Inkling-Small is an efficient multimodal AI model built to deliver strong reasoning and coding performance at a fraction of Inkling’s size. It is a Mixture-of-Experts transformer with 276 billion total parameters and 12 billion active parameters. The model was trained on NVIDIA GB300 NVL72 systems and is designed to combine high capability with more efficient inference. Inkling-Small supports native reasoning across text, images, and audio, allowing it to work across multimodal tasks without relying on separate encoders. Its context window supports up to one million tokens, making it useful for long-form reasoning, large-scale code understanding, document analysis, and agentic workflows. Users can adjust reasoning effort from minimal to extra high depending on whether they need faster responses or deeper computation. The model’s training process includes improved pre-training data, post-training with on-policy distillation from Inkling, and extended agentic coding reinforcement learning. These techniques helped Inkling-Small outperform its larger counterpart on reasoning and coding benchmarks. The model performs well in coding and tool-use harnesses and exceeds 80% on SWE-bench Verified. Its encoder-free architecture processes audio as dMel spectrograms and images as 40-by-40-pixel patches alongside text tokens. By combining efficient MoE design, one-million-token context, adjustable reasoning effort, multimodal processing, coding strength, and tool-use performance, Inkling-Small is designed for developers and teams that need capable AI with lower active compute requirements.

What is GPT-Realtime-2.1?

GPT-Realtime-2.1 is an OpenAI realtime reasoning model for developers building voice agents, conversational AI assistants, and speech-to-speech applications. The model is designed to support fast interactive experiences where users can speak naturally and receive audio or text responses. GPT-Realtime-2.1 updates GPT-Realtime-2 with improved handling of alphanumeric recognition, silence, background noise, and interruptions. It supports text, audio, and image input, with text and audio output, while video is not supported. The model includes configurable reasoning effort so developers can balance reasoning depth, latency, and token usage for different voice-agent workflows. GPT-Realtime-2.1 also supports instruction following, function calling, tool use, and reasoning tokens for more complex applications. Its 128,000-token context window and 32,000-token maximum output allow it to manage longer conversations and richer task context. OpenAI lists support across endpoints such as Chat Completions, Responses, Realtime, realtime translations, realtime transcription sessions, Assistants, Batch, and related API services. The model’s documented pricing includes $4 per 1 million text input tokens, $0.40 per 1 million cached text input tokens, and $24 per 1 million text output tokens, with separate audio and image token pricing. GPT-Realtime-2.1 is not documented as supporting streaming, structured outputs, fine-tuning, or predicted outputs. By combining realtime speech, multimodal input, reasoning, function calling, and tool use, GPT-Realtime-2.1 gives developers a foundation for building sophisticated AI voice agents and interactive customer-facing applications.

Media

Media

Integrations Supported

Model Context Protocol (MCP)
OpenAI
Tinker
gpt-realtime

Integrations Supported

Model Context Protocol (MCP)
OpenAI
Tinker
gpt-realtime

API Availability

Has API

API Availability

Has API

Pricing Information

$0.30 per million input tokens
$0.30 per million input tokens and $1.20 per million output tokens
Free Version
Free Trial Offered?

Pricing Information

$0.40 per cached input
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Thinking Machines Lab

Date Founded

2025

Company Location

United States

Company Website

thinkingmachines.ai/news/inkling-small/

Company Facts

Organization Name

OpenAI

Date Founded

2015

Company Location

United States

Company Website

developers.openai.com/api/docs/models/gpt-realtime-2.1

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