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What is SWE-2 Flash?

SWE-2 Flash is an AI coding and software engineering model developed by Cognition to deliver high-speed programming capabilities with lower inference costs than larger frontier models. The model uses a 276-billion-parameter mixture-of-experts architecture with approximately 12 billion active parameters, based on Thinking Machines' Inkling-Small foundation model. Cognition enhances the underlying model through a dedicated mid-training process followed by large-scale reinforcement learning focused on software engineering and general reasoning tasks. Its training incorporates several trillion tokens of carefully selected technical material, including source code, scientific publications, articles, and other datasets relevant to complex problem-solving. SWE-2 Flash supports automated code generation, software maintenance, code reviews, feature development, documentation updates, and other tasks performed by autonomous development agents. The model is optimized for efficient inference and generates approximately 200 tokens per second, compared with approximately 60 tokens per second for the larger SWE-2 model. Cognition reports that SWE-2 Flash operates at one-fifth the cost of SWE-2 while maintaining competitive performance across several software engineering evaluations. Its published benchmark results include 24.0% on FrontierCode 2.0, 45.5% on FrontierCode 1.1 Main, 60.1% on DeepSWE 1.1, and 89.9% on SWE-Bench Pro v2 Hard. The model also demonstrates cybersecurity-related capabilities, achieving 34.8% on ExploitBench compared with 11.3% for its original foundation model. Developers can access SWE-2 Flash through Devin Desktop and CLI for interactive programming assistance and agent-driven engineering workflows. Cognition is developing a secure program for sharing model weights with approved industry partners and research organizations, potentially enabling fine-tuning and deployment on private or on-premises infrastructure.

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.

Media

Media

Integrations Supported

.NET
C#
C++
CSS
Cerebras
Dart
Devin
Devin Desktop
HTML
Kotlin
Lua
PHP
PowerShell
Python
Ruby
Rust
Scala
Terraform
XML

Integrations Supported

Tinker

API Availability

API Availability

Has API

Pricing Information

$20/month
Free Version

Pricing Information

$0.30 per million input tokens
$0.30 per million input tokens and $1.20 per million output tokens

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Cognition

Date Founded

2023

Company Location

United States

Company Website

cognition.com

Company Facts

Organization Name

Thinking Machines Lab

Date Founded

2025

Company Location

United States

Company Website

thinkingmachines.ai/news/inkling-small/

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

AI Vision Models

Not specified

Open-Weight AI Models

Not specified

Small Language Models

Not specified

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