SWE-2

SWE-2

Cognition
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About

Muse Spark 1.2 is Meta’s coding-focused model update designed to power Muse Code and improve software engineering workflows. The model is built for code generation, complex debugging, codebase understanding, long-horizon development tasks, and end-to-end developer workflows. Muse Spark 1.2 was co-trained with Muse Code to improve performance inside the terminal coding agent environment. It supports planning, goal conditioning, context compaction, subagent coordination, and iterative coding workflows across large repositories. The model was trained with expanded coding compute, diverse development environments, self-improvement loops, and long-running engineering tasks. Built for AI developers and software teams, Muse Spark 1.2 helps agents plan, write, validate, debug, and optimize code with greater autonomy.

About

SWE-2 is Cognition’s advanced coding model designed to improve software engineering performance while reducing the cost of agentic coding workflows. The model is post-trained from Kimi K3 and uses reinforcement learning to optimize multiple reasoning-effort levels within a single training run. SWE-2 is designed to explore codebases more selectively, begin implementation sooner, and complete tasks with fewer redundant reads and reasoning steps than earlier Cognition models. Its capabilities include code generation, debugging, test creation, verification, repository analysis, and complex terminal-based software engineering tasks. The model also emphasizes stronger engineering judgment, end-to-end test coverage, instruction following, and evidence-based verification of user assumptions. SWE-2 is available through Devin Desktop and Devin CLI, with broader rollout planned across Devin Web and Fusion.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

AI developers, software engineers, coding agent builders, research teams, platform teams, DevOps teams, ML engineers, enterprise development teams, and organizations that need code generation, debugging, codebase understanding, long-horizon coding, terminal agents, subagent coordination, repository automation, kernel optimization, and end-to-end developer workflow support

Audience

Software developers, engineering teams, AI coding agent users, DevOps professionals, and organizations that need capable agentic software engineering with lower execution cost and more efficient reasoning

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

$1.25 per 1M tokens (input)
$1.25 per million tokens in input, and $4.25 per million tokens of output
Free Version
Free Trial

Pricing

$20/month
Free Version
Free Trial

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5

Pros & Cons from Real Users

Pros

  • Muse Spark 1.2 looks like a big step up for developers because it is clearly aimed at real software engineering work, not just casual code suggestions. The fact that it powers Muse Code makes it feel more practical right away, especially for terminal-based workflows where the model can help write code, validate changes, and work through bigger tasks. I like that Meta seems to be pushing hard into agentic coding. Earlier Muse Spark versions were already positioned around multimodal reasoning, tool use, and visual coding, and 1.2 feels like the more developer-focused evolution of that direction. The cost angle is interesting too. Reports mention Muse Code having multiple pricing tiers, including a cheaper option, which could matter a lot for developers running coding agents frequently instead of only using AI once in a while.

Cons

  • It is still new and tied to a beta coding agent, so I would not trust it blindly yet. I would want to test it on real repos, messy bugs, failing tests, multi-file edits, and longer agent runs before making it part of my daily stack. Meta also still has to prove the developer experience. A strong model is one thing, but coding agents live or die on tooling, speed, reliability, permissions, logs, diffs, and how well they recover when something breaks.

Pros & Cons from Real Users

Pros

  • The biggest thing that stands out is the cost-performance balance. SWE-2 is not just trying to top one benchmark; it is trying to get very close to frontier coding performance at a much lower cost. For developers, that matters a lot. Coding agents can burn through tokens quickly when they are reading files, making edits, running tests, and iterating. A model that performs near the top while being meaningfully cheaper is much easier to use every day. I also like that SWE-2 seems built for real software engineering workflows, not just isolated code snippets. The strong DeepSWE and Terminal-Bench results make it especially interesting for repo-level tasks, debugging, tool use, and longer agent runs.

Cons

  • Benchmarks are useful, but real projects bring messy architecture, flaky tests, undocumented behavior, and weird edge cases.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Meta
Founded: 2004
United States
meta.ai

Company Information

Cognition
Founded: 2023
United States
cognition.com

Alternatives

Alternatives

GPT-5.6 Sol

GPT-5.6 Sol

OpenAI
GPT-5.6 Sol

GPT-5.6 Sol

OpenAI
SWE-1.7

SWE-1.7

Cognition
SWE-1.6

SWE-1.6

Cognition

Categories

Categories

Integrations

C#
C++
CSS
Go
JavaScript
Kotlin
Kubernetes
Lua
PHP
PowerShell
Python
R
Ruby
Rust
SQL
Scala
Swift
TypeScript
XML
YAML

Integrations

C#
C++
CSS
Go
JavaScript
Kotlin
Kubernetes
Lua
PHP
PowerShell
Python
R
Ruby
Rust
SQL
Scala
Swift
TypeScript
XML
YAML
Claim Muse Spark 1.2 and update features and information
Claim Muse Spark 1.2 and update features and information
Claim SWE-2 and update features and information
Claim SWE-2 and update features and information