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About

Lyzo AI is an AI-native Integrated Development Environment (IDE) built to transform the way modern software is developed. Instead of being limited to code generation, Lyzo AI is designed to understand the entire project, retain context, assist across the development lifecycle, and automate repetitive engineering workflows from a single workspace. With capabilities such as Unlimited AI Access, Unlimited Memory, Persistent Project Context, Full Codebase Indexing, Pre-installed Engineering Skills, Visual Code Mapping, AI Code Review, Intelligent Refactoring, Automated Unit Testing, Git Workflow Automation, and a Built-in DevOps Engineer, Lyzo AI brings coding, project intelligence, testing, and engineering operations together. Lyzo AI helps developers and teams understand complex codebases, build software faster, review and optimize code, automate engineering tasks, and move from development toward production with greater efficiency. Our vision is to

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.

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

Software developers, software engineering teams, startups, technology companies, enterprises, and development agencies looking to accelerate coding, codebase understanding, testing, code review, and DevOps workflows with AI.

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

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

No images available

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

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

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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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.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Lyzo AI
Founded: 2025
India
lyzo.ai/

Company Information

Meta
Founded: 2004
United States
meta.ai

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Categories

Categories

Integrations

Bash
C#
CSS
Claude Agent SDK
Go
Gray Swan
HTML
Instagram
Kotlin
LlamaIndex
Lua
Muse Code
Odysseus
OpenAI Agents SDK
PowerShell
Ruby
Rust
SQL
Solidity
Swift

Integrations

Bash
C#
CSS
Claude Agent SDK
Go
Gray Swan
HTML
Instagram
Kotlin
LlamaIndex
Lua
Muse Code
Odysseus
OpenAI Agents SDK
PowerShell
Ruby
Rust
SQL
Solidity
Swift
Claim Lyzo AI and update features and information
Claim Lyzo AI and update features and information
Claim Muse Spark 1.2 and update features and information
Claim Muse Spark 1.2 and update features and information