AI Tool

Cognition's SWE-2 Review

SWE-2 is an advanced coding model from Cognition that leverages a multi-trillion parameter infrastructure to enhance performance while reducing costs.

shipped Sep 13, 2026codepaid

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codeproductivity

Why it matters

1Post-trained from Moonshot AI's Kimi K3, a 2.8-trillion-parameter model.

2Achieves 50.0% on FrontierCode 1.1 Main and 73.0% on DeepSWE 1.1.

3Claims to be 64% cheaper than Fable 5.1 on FrontierCode 1.1 Main.

4Utilizes a novel RL algorithm that trains across different reasoning effort levels in a single run.

About Cognition's SWE-2

Usage Pricing

$3.28/task per task

Platforms

Web, Desktop

Pricing Plans

Standard

$3.28/task

• 50.9% pass rate on FrontierCode 1.1 Main
• 63% cost reduction compared to previous models

Cost Examples

• Use SWE-2 for 100 tasks: ~$328

Specs

API Available

Yes, public API

overview

What is Cognition's SWE-2?

Cognition's SWE-2 is an agentic coding model tool developed by Cognition that enables software engineers and developers to automate software engineering tasks. It is post-trained from a 2.8-trillion-parameter base model using reinforcement learning, designed for agentic coding tasks that require strong performance at lower computational and monetary cost.

features

Key Features of Cognition's SWE-2

Cognition's SWE-2 incorporates several technical advancements and capabilities designed to optimize autonomous software engineering workflows.

50.0% on FrontierCode 1.1 Main benchmark.
Lower inference–training mismatch compared to SWE-1.7.
Improved resource allocation through a novel RL algorithm.
Enhanced coding competency across various task complexity levels.
Robustness against reward hacking achieved through comprehensive verifier hardening.
Post-trained from Moonshot AI's Kimi K3, a 2.8-trillion-parameter model.
Single-run RL algorithm optimizing the entire cost-performance frontier.
Infrastructure enhancements including prefill delayer for GPU scheduling (10-20% increase in tokens per GPU).
Speculative decoding and NVFP4/FP8 quantization-aware kernels for efficiency.

use cases

Who Should Use Cognition's SWE-2?

Cognition's SWE-2 is primarily designed for software engineers and developers seeking to automate and optimize various stages of the software development lifecycle, particularly those involving complex coding tasks and autonomous agentic workflows.

Software Engineers: For autonomous software engineering tasks, including interpreting high-level goals and generating code.
Developers using AI coding agents: For focused codebase exploration, generating and modifying code, and running/verifying tests.
Teams requiring efficient problem-solving: When standard solutions are blocked, SWE-2 demonstrates resourcefulness in finding alternative paths.
Organizations focused on cost-performance optimization: Leveraging its superior cost-performance results for agentic coding tasks.

how to use

How to Use Cognition's SWE-2

Cognition's SWE-2 is integrated into Cognition's Devin products, including Devin Desktop and CLI, with planned rollout for Devin Web and Fusion. Users access its capabilities through these platforms.

1Subscribe to Devin Pro: Access SWE-2 by subscribing to Devin Pro for $20 per month.
2Install Devin Desktop or CLI: Download and install the Devin Desktop application or the Devin Command Line Interface.
3Define a high-level goal: Provide SWE-2 with a clear, high-level software engineering objective.
4Monitor task execution: Observe SWE-2 as it devises a plan, conducts research, writes code, and verifies tests.
5Review and integrate code: Evaluate the generated code and integrate it into your project as needed.

pricing

Cognition's SWE-2 Pricing & Plans

Cognition's SWE-2 is not offered as a standalone API with per-token pricing. Instead, its capabilities are integrated into Cognition's Devin products. The primary access point is through a subscription to Devin Pro, which includes SWE-2's functionalities. Additionally, a per-task pricing model is available for specific usage scenarios.

Devin Pro: $20 per month (includes SWE-2 integration).
Standard: $3.28 per task (usage-based pricing for specific tasks).
Cost Example: Using SWE-2 for 100 tasks would cost approximately $328 under the Standard pricing model.

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Pros

+Achieves competitive performance on several coding benchmarks, including 50.0% on FrontierCode 1.1 Main and 73.0% on DeepSWE 1.1.
+Offers superior cost-performance results, claiming to be 64% cheaper than Fable 5.1 on FrontierCode 1.1 Main.
+Utilizes a novel RL algorithm that optimally trains across different levels of reasoning effort in a single run.
+Post-trained from Moonshot AI's Kimi K3, a 2.8-trillion-parameter model, enhancing its base capabilities.
+Demonstrates resourcefulness in problem-solving, finding alternative solutions when initial paths are blocked.
+Integrated into Devin Desktop and CLI, providing direct access for developers.

Cons

−Scores significantly lower on more challenging agentic benchmarks like Terminal-Bench 4 (27.3%) compared to competitors like Fable 5.1 (55.8%) and GPT-6 Astra (57.9%).
−Some users report that SWE-2 tends to ask too many clarifying questions before proceeding with a task, potentially adding friction.
−Not offered as a standalone API with per-token pricing, requiring integration through Devin products.
−Concerns exist regarding potential 'cherry-picked benchmarks' in initial announcements, specifically omitting weaker scores on certain tests.

Similar Tools

Cognition's SWE-2 vs Competitors

Cognition's SWE-2 is positioned to push the Pareto frontier of capability and cost in agentic coding, competing with several established and emerging AI coding tools.

FauxPilot↗

It allows users to run a local, self-hosted code completion server using open-source models, providing a privacy-focused alternative to cloud-based AI assistants.

While SWE-2 offers a highly optimized, cloud-based service, FauxPilot requires users to manage their own local server and model, which can be more resource-intensive and less performant out-of-the-box but offers complete data privacy and no recurring costs.

TabnineOn Stork

Tabnine provides AI code completion and generation that learns from your code and adapts to your coding style, offering both cloud-based and local models.

Tabnine offers a more traditional IDE-integrated code completion experience compared to SWE-2's potentially more agent-like or reasoning-focused approach, with a focus on developer productivity through intelligent suggestions rather than complex problem-solving.

CursorOn Stork

Cursor is an AI-native code editor built from the ground up to integrate large language models for coding tasks like generation, editing, and debugging directly within the IDE.

Unlike SWE-2 which is a backend model, Cursor is a full-fledged IDE with AI deeply integrated, requiring users to adopt a new editor but offering a seamless AI-powered workflow for code creation and modification.

See every Cognition's SWE-2 alternative, compared→