Compare coding agents on a repository task that includes editing, running checks, and reviewing the resulting patch. An editor assistant and a terminal agent can both help with code, but they differ in how much context and execution control you manage.
Use the same issue, test command, and acceptance criteria for each trial. Review the diff and any executed commands, including failures. Compare the cost of a completed and reviewed task rather than treating token allowance or an attractive demo as the result.
OpenAI Codex helps developers inspect repositories, edit code and run tools through local clients and eligible cloud tasks.

Codex is OpenAI's coding agent for developers who want help writing, reviewing and maintaining software. It can work with a repository, explain code, make edits and run development tools. Local clients and eligible cloud environments provide different ways to carry out a task.
Codex works on a development task with project context rather than only returning an isolated code snippet. It can inspect files and use tools while making changes. Its suggestions and test output help a developer review a result, but generated code still needs appropriate checks.
Start in a repository and describe the behavior you want changed. Codex can examine existing implementation, edit files and run available checks. Project instructions, environment permissions and installed tools shape what it can do. Review the diff and any remaining failures before accepting changes.
The CLI and IDE extension provide local development workflows. Codex Cloud runs tasks in managed environments for eligible accounts, subject to workspace settings. Cloud work can continue while a computer is asleep, whereas local workflows depend on the device running the task.
OpenAI shows coding workflows and examples for Codex. Evaluate it with a representative task and your repository's checks. A successful demonstration does not establish correctness for a different codebase, dependency set or deployment environment.
Allowances vary by plan, task complexity, tools and model. Check account eligibility and usage before starting long-running tasks.
Looking for alternatives to other popular tools? Check out other posts in the alternatives series and flowtools.co, a directory of best AI tools with filters for tags and categories for easy browsing and discovery.
Factory Droid is an AI software engineering agent for teams that need help coding, testing, and deploying software.

Factory Droid is an AI coding agent for teams that want agents involved across the software delivery lifecycle. It helps with coding, testing, and deployment, with background agents that can run in the cloud or locally.
Factory Droid is not pitched as a single editor plugin. Factory describes it as a self-improving SDLC system where engineering signals feed back into coding, testing, deployment, and readiness workflows.
Deployment flexibility is the other clear difference. Enterprise includes on-premise deployment options, dedicated compute, and data residency. Requirements for hosting and access should be included in the enterprise agreement.
The Pro plan includes desktop, CLI, and SDK access, cloud and local background agents, billing and usage statistics, and an agent-readiness dashboard. Factory lists support for frontier and open-weight models, including GPT-5, Claude Opus and Sonnet, and Gemini.
Higher plans increase rolling rate limits and add infrastructure for remote agents. Plus adds about 5x Pro usage and Droid Computers for remote Droids. Max adds about 10x Pro usage and early feature access. Business and Enterprise add team management, security, dedicated compute, data controls, and larger deployment options.
Factory publishes customer quotes instead of a public average rating. A Nav CTO quote highlights a secure, controlled way to unify engineering context around sensitive financial data. A Tilt CTO quote frames Factory as a way to guide heavier software work.
The tradeoff is that the buying path is more enterprise-oriented than many coding tools. Business and Enterprise do not publish fixed monthly prices, and heavy users may need Plus or Max because usage is managed through rolling rate limits.
Factory Droid is priced for serious engineering usage. Pro covers the core workflow, while higher plans add usage, remote compute, security, and deployment control.
Augment Code is an AI coding platform for engineering teams running agents across triage, coding, review and verification.

Augment Code is an AI coding platform for professional engineering teams that want agents to work across the software delivery loop, not just autocomplete code. Cosmos coordinates agents for triage, authoring, review and verification, with shared organization knowledge and controls for larger codebases.
Augment Code is positioned less like a single coding assistant and more like an organization-level agent system. The homepage describes specialized experts for each stage: Work Dispatcher, PR Author, Pair Review, Deep Code Review, PR Risk Analysis and Tester.
Its main technical differentiator is the Context Engine. Augment says it maps codebase structure and pulls only the slice relevant to the task, instead of sending broad keyword matches to a model. That matters for teams worried about token cost, context quality and large-repo changes.
Teams can use shipped experts, fork them or build their own templates with separate environments, capabilities and memory. Cosmos adds an expert registry, human-in-the-loop escalation, organization knowledge, scheduling, sandboxes, shared file systems and lifecycle triggers.
The enterprise feature set includes zero data retention, CMEK encryption, VPC deployment, single-tenant instances, BYOK for models, data residency controls, replayable runs, on-prem deployment, HIPAA BAA availability and dedicated account support.
Augment's homepage includes vendor-reported customer outcomes. Those figures are examples of particular deployments, not guaranteed results for every team.
The product suits teams that need shared agent workflows, policy controls and codebase context. Standard and Business support is community-based with tickets through the support portal, while Enterprise adds dedicated support.
Standard and Business usage is pooled across the team. Extra usage is handled with pay-as-you-go top-ups, and the pricing FAQ lists a 40% service fee on LLM usage, with compute billed separately and no service fee on compute.
Amp is a coding agent for developers who want CLI, editor, and web control over model-powered coding work.

Amp is a coding agent and development environment for web, terminal, and native app workflows. It can inspect projects, edit code, and use tools. Its current experience includes orbs: machines created for agent threads with the project's code and tools ready to use.
Amp combines the coding agent with a development environment. An orb supplies a machine for a thread, so a remote task can continue after you close your laptop. Local CLI workflows and your own runners provide other ways to work.
Create a project from a Git repository, then give the agent a task. The web experience starts threads in orbs, while the CLI can work on your machine or from scripts. Native apps add notifications and ways to follow up on agent work.
Threads and workspace features support collaboration. Plugins and skills customize the workflow, and model routing can use supported external accounts. A consumer subscription must be connected and eligible; it does not automatically cover every model or infrastructure charge.
Amp publishes product examples and vendor-selected feedback rather than a universal independent rating. Review generated code and test changes in your project. Orb resource needs, provider access, and the selected workflow affect cost.
Hobby is free, with pay-as-you-go orbs or your own runners. Paid individual tiers start at $20/month. Teams have no additional team charge, and members can use different tiers. Enterprise pricing is custom. Amp lists no token fee for supported external subscriptions or BYOK; provider charges and orb usage still depend on the selected setup.
Use an open-source coding agent for editors and the terminal, with supported model providers and reviewable changes.

Cline is an open-source AI coding agent that runs inside VS Code, your terminal, CI pipelines, or your own product through its SDK. It is built for developers who want an autonomous agent that edits across a whole project, runs commands, and works with supported model providers while you keep control of cost.
Cline is open source (Apache 2.0) and model-agnostic, with several model-access options, including usage billing, BYOK, and optional ClinePass. Its Plan-and-Act split is the core mechanism: Plan mode lists which files it will touch and the steps it will take, then Act mode carries them out one approval at a time, keeping the agent transparent and reviewable rather than a black box.
You point Cline at a task and it reads the codebase, proposes a plan, then makes coordinated changes across many files while keeping imports, types, and behavior consistent. It runs tests, starts dev servers, and reacts to terminal output live. A .clinerules file teaches it your standards, architecture, and deployment conventions.
Beyond the editor, the CLI runs in scripts, cron jobs, and CI pipelines. You can register custom tools and MCP servers and set up multi-agent teams where a coordinator delegates to specialists. Cline reports contributions from more than 250 contributors.
Evaluate the Plan and Act workflow with representative changes, and inspect commands before approving them. Large tasks can consume substantial model usage. Cline reports more than 11 million installs across supported platforms; an install count is not a count of unique developers.
The extension and model access have separate economics. Compare provider usage charges and optional ClinePass with the tasks you expect to run.