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Description

NVIDIA's Nemotron 3.5 Lightning is a state-of-the-art mixture-of-experts model boasting 30 billion parameters, of which 3 billion are actively utilized, specifically engineered for efficient, high-throughput performance in long-duration and continuously operating AI agents. This model is tailored for the execution components of agentic systems, adeptly managing frequent operations like tool invocations, output verification, routine commands, and delegating tasks to subagents, while larger reasoning models concentrate on strategic planning and orchestration. By employing a mixture-of-experts architecture, it activates only a select subset of parameters for each input token, marrying the expansive capacity of a larger model with significantly reduced computational demands. The training of this model is optimized for widely used agent harnesses and enhances inference speed through techniques such as speculative decoding, multi-token prediction, DFlash, and DSpark, making it versatile across various operational scenarios. Additionally, it is compatible with BF16 and NVFP4 checkpoints, providing flexibility in deployment from local systems like DGX Spark and GeForce RTX hardware to extensive data center infrastructures. In summary, its innovative design and scalability make it a powerful tool for advancing AI capabilities.

Description

SWE-2 is a software engineering model from Cognition built for agentic coding tasks that require strong performance at lower computational and monetary cost. It is post-trained from the Kimi K3 base model and extends Cognition’s earlier SWE-1.7 training approach with a new reinforcement learning method for jointly optimizing multiple reasoning-effort settings. Medium, high, and maximum effort modes provide different tradeoffs between speed, cost, exploration, and verification depending on task complexity. The model is trained to inspect only the parts of a codebase that are likely to matter, helping it reach implementation faster and reduce unnecessary exploration. SWE-2 can generate and modify code, run tests, analyze repositories, work through terminal tasks, and verify whether implementations satisfy user requirements. Cognition also reports improvements in end-to-end test creation, regression detection, instruction following, and re-deriving conclusions when challenged. Its training process incorporates cost-aware rewards, length-weighted reward baselines, expanded reinforcement learning environments, and hardened verifiers intended to improve both efficiency and reliability. SWE-2 is positioned as a cost-efficient alternative to larger frontier coding models while remaining competitive on software engineering benchmarks such as FrontierCode, DeepSWE, and Terminal-Bench. The model is available in Devin Desktop and Devin CLI and is being introduced to additional Cognition products including Devin Web and Fusion.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

.NET
C++
Devin Desktop
Go
Hermes Agent
JSON
Kotlin
Kubernetes
Lua
Objective-C
OpenClaw
PHP
Portable Computer by Perplexity
Python
R
Ruby
SQL
Scala
TypeScript
XML

Integrations

.NET
C++
Devin Desktop
Go
Hermes Agent
JSON
Kotlin
Kubernetes
Lua
Objective-C
OpenClaw
PHP
Portable Computer by Perplexity
Python
R
Ruby
SQL
Scala
TypeScript
XML

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

$20/month
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

nvidia.com

Vendor Details

Company Name

Cognition

Founded

2023

Country

United States

Website

cognition.com

Product Features

Product Features

Alternatives

Alternatives

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