Choose Amazon Q Developer when
Choose Amazon Q Developer when developers building and operating applications on AWS.
Amazon Q Developer vs Codex
Which AI coding workflow fits you?
Reviewed Jul 12, 2026
47-field comparison matrix
| Dimension |  Amazon Q DeveloperEnterprise coding assistant integrated with AWS development and operationsView full Amazon Q Developer analysis |  CodexCross-surface coding agent and multi-agent command centerView full Codex analysis | Official evidence |
|---|---|---|---|
| Product formDetermines whether adoption replaces the primary editor or layers an agent across existing tools. | Enterprise coding assistant integrated with AWS development and operations | Cross-surface coding agent and multi-agent command center | Amazon Q Developer product overview OpenAI Codex product overview |
| Primary surfacesShows how much of the team's current development environment can remain in place. | VS Code extension · JetBrains plugin · Visual Studio integration · Eclipse preview · AWS Management Console and mobile console · GitHub.com and GitHub Enterprise Cloud preview · GitLab Duo with Amazon Q · Microsoft Teams and Slack | ChatGPT desktop app in Codex mode · Codex IDE extension · Codex CLI · Codex web · Codex cloud · GitHub | Amazon Q Developer product overview OpenAI Codex product overview |
| Execution environmentsAffects machine usage, task isolation, and the ability to continue long-running work away from a laptop. | Local IDE workspace · AWS-managed application transformation workflow · AWS Management Console · Connected GitHub or GitLab repository · Command-line workflow transitioned to Kiro CLI | Local workspace · Git worktree · OpenAI-managed cloud container | Amazon Q Developer product overview OpenAI Codex product overview |
| Model strategyInfluences model choice, vendor concentration, and how usage costs vary by task. | What Amazon Q Developer is — Model strategy: Amazon Q Developer is AWS's generative AI assistant for software development and cloud operations. It supports code generation and understanding, security review, application modernization, and AWS resource guidance.Confirmed | What Codex is — Model strategy: Codex is a coding agent connected by a ChatGPT account across the desktop app, IDE, terminal, web, and cloud. The desktop experience is designed as a command center for supervising multiple agents and long-running work.Confirmed | Amazon Q Developer product overview OpenAI Codex product overview |
| Free starting pointSets the cost of running a real proof of concept before committing a team. | $0/plan — Free entry available. Perpetual Free — 50 agentic requests and 1,000 transformation lines per month | $0/plan — Free entry available. Codex is included across ChatGPT plans, including Free and Go, with limits that vary by plan | Amazon Q Developer pricing Using Codex with your ChatGPT plan |
| Best-fit buying archetypeTurns the feature inventory into an explicit initial choice while keeping editorial judgment separate from product facts. | What Amazon Q Developer is — Best-fit buying archetype: Amazon Q Developer is AWS's generative AI assistant for software development and cloud operations. It supports code generation and understanding, security review, application modernization, and AWS resource guidance.Confirmed | What Codex is — Best-fit buying archetype: Codex is a coding agent connected by a ChatGPT account across the desktop app, IDE, terminal, web, and cloud. The desktop experience is designed as a command center for supervising multiple agents and long-running work.Confirmed | Amazon Q Developer product overview OpenAI Codex product overview |
| Native full editorDetermines migration effort and whether developers can consolidate manual coding and agent work into one editor. | Editing and coding workflow — Native full editor: In the IDE, Amazon Q combines inline completion, chat, repository-aware questions, agentic planning, file edits, diffs, shell commands, refactoring, tests, and code review.Confirmed | Coding workflow — Native full editor: Codex can inspect repositories, edit files, execute commands and tests, review diffs, and complete substantial engineering tasks. Local work is available through the app, IDE extension, and CLI, while cloud tasks can continue independently.Confirmed | Amazon Q Developer product overview OpenAI Codex product overview |
| Dedicated inline completionInline completion affects hundreds of small daily edits that do not warrant delegating a full agent task. | Editing and coding workflow — Dedicated inline completion: In the IDE, Amazon Q combines inline completion, chat, repository-aware questions, agentic planning, file edits, diffs, shell commands, refactoring, tests, and code review.Confirmed | Coding workflow — Dedicated inline completion: Codex can inspect repositories, edit files, execute commands and tests, review diffs, and complete substantial engineering tasks. Local work is available through the app, IDE extension, and CLI, while cloud tasks can continue independently.Confirmed | Amazon Q Developer product overview OpenAI Codex product overview |
| End-to-end agent changesShows whether the product can move beyond suggestions to implementation, testing, and revision. | Editing and coding workflow — End-to-end agent changes: In the IDE, Amazon Q combines inline completion, chat, repository-aware questions, agentic planning, file edits, diffs, shell commands, refactoring, tests, and code review.Confirmed | Coding workflow — End-to-end agent changes: Codex can inspect repositories, edit files, execute commands and tests, review diffs, and complete substantial engineering tasks. Local work is available through the app, IDE extension, and CLI, while cloud tasks can continue independently.Confirmed | Amazon Q Developer product overview OpenAI Codex product overview |
| Codebase context approachContext retrieval quality becomes more important as repository size and architectural complexity grow. | Editing and coding workflow — Codebase context approach: In the IDE, Amazon Q combines inline completion, chat, repository-aware questions, agentic planning, file edits, diffs, shell commands, refactoring, tests, and code review.Confirmed | Coding workflow — Codebase context approach: Codex can inspect repositories, edit files, execute commands and tests, review diffs, and complete substantial engineering tasks. Local work is available through the app, IDE extension, and CLI, while cloud tasks can continue independently.Confirmed | Amazon Q Developer product overview OpenAI Codex product overview |
| Visual and frontend workflowVisual input and browser verification reduce the gap between generated frontend code and the intended design. | Editing and coding workflow — Visual and frontend workflow: In the IDE, Amazon Q combines inline completion, chat, repository-aware questions, agentic planning, file edits, diffs, shell commands, refactoring, tests, and code review.Confirmed | Coding workflow — Visual and frontend workflow: Codex can inspect repositories, edit files, execute commands and tests, review diffs, and complete substantial engineering tasks. Local work is available through the app, IDE extension, and CLI, while cloud tasks can continue independently.Confirmed | Amazon Q Developer product overview OpenAI Codex product overview |
| Terminal, build, and test executionThe implementation loop is incomplete if the agent cannot run the repository's own verification commands. | Editing and coding workflow — Terminal, build, and test execution: In the IDE, Amazon Q combines inline completion, chat, repository-aware questions, agentic planning, file edits, diffs, shell commands, refactoring, tests, and code review.Confirmed | Coding workflow — Terminal, build, and test execution: Codex can inspect repositories, edit files, execute commands and tests, review diffs, and complete substantial engineering tasks. Local work is available through the app, IDE extension, and CLI, while cloud tasks can continue independently.Confirmed | Amazon Q Developer product overview OpenAI Codex product overview |
| Debugging workflowShows whether the product can diagnose runtime behavior rather than only rewrite code from static context. | Editing and coding workflow — Debugging workflow: In the IDE, Amazon Q combines inline completion, chat, repository-aware questions, agentic planning, file edits, diffs, shell commands, refactoring, tests, and code review.Confirmed | Coding workflow — Debugging workflow: Codex can inspect repositories, edit files, execute commands and tests, review diffs, and complete substantial engineering tasks. Local work is available through the app, IDE extension, and CLI, while cloud tasks can continue independently.Confirmed | Amazon Q Developer product overview OpenAI Codex product overview |
| Project instructions and rulesPersistent instructions reduce repeated prompting and encode architecture, testing, and review requirements. | Context and extensibility — Project instructions and rules: Amazon Q understands local workspaces, AWS resources and documentation, and connected private repositories. AWS also documents native and MCP-based tools for agentic workflows.Confirmed | Context and extensibility — Project instructions and rules: Codex uses AGENTS.md, configuration, rules, skills, plugins, MCP, hooks, and programmable interfaces to align tasks with project and team requirements.Confirmed | Amazon Q Developer product overview Introducing the Codex app |
| Reusable skillsSkills turn specialized repeatable work into a maintained capability instead of a copied prompt. | Context and extensibility — Reusable skills: Amazon Q understands local workspaces, AWS resources and documentation, and connected private repositories. AWS also documents native and MCP-based tools for agentic workflows.Confirmed | Context and extensibility — Reusable skills: Codex uses AGENTS.md, configuration, rules, skills, plugins, MCP, hooks, and programmable interfaces to align tasks with project and team requirements.Confirmed | Amazon Q Developer product overview Introducing the Codex app |
| MCP supportMCP enables reusable connections to external tools, services, and private operational context. | Context and extensibility — MCP support: Amazon Q understands local workspaces, AWS resources and documentation, and connected private repositories. AWS also documents native and MCP-based tools for agentic workflows.Confirmed | Context and extensibility — MCP support: Codex uses AGENTS.md, configuration, rules, skills, plugins, MCP, hooks, and programmable interfaces to align tasks with project and team requirements.Confirmed | Amazon Q Developer product overview Introducing the Codex app |
| Plugins and marketplaceA managed extension ecosystem affects discovery, reuse, permissions, and supply-chain governance. | Context and extensibility — Plugins and marketplace: Amazon Q understands local workspaces, AWS resources and documentation, and connected private repositories. AWS also documents native and MCP-based tools for agentic workflows.Confirmed | Context and extensibility — Plugins and marketplace: Codex uses AGENTS.md, configuration, rules, skills, plugins, MCP, hooks, and programmable interfaces to align tasks with project and team requirements.Confirmed | Amazon Q Developer product overview Introducing the Codex app |
| HooksHooks allow deterministic checks and integrations around otherwise probabilistic agent behavior. | Context and extensibility — Hooks: Amazon Q understands local workspaces, AWS resources and documentation, and connected private repositories. AWS also documents native and MCP-based tools for agentic workflows.Confirmed | Context and extensibility — Hooks: Codex uses AGENTS.md, configuration, rules, skills, plugins, MCP, hooks, and programmable interfaces to align tasks with project and team requirements.Confirmed | Amazon Q Developer product overview Introducing the Codex app |
| SDK and non-interactive executionProgrammable entry points determine whether the agent can be embedded in CI, scripts, and internal tooling. | Context and extensibility — SDK and non-interactive execution: Amazon Q understands local workspaces, AWS resources and documentation, and connected private repositories. AWS also documents native and MCP-based tools for agentic workflows.Confirmed | Context and extensibility — SDK and non-interactive execution: Codex uses AGENTS.md, configuration, rules, skills, plugins, MCP, hooks, and programmable interfaces to align tasks with project and team requirements.Confirmed | Amazon Q Developer product overview Introducing the Codex app |
| Team capability distributionCentral distribution prevents every developer from maintaining incompatible private agent setups. | Context and extensibility — Team capability distribution: Amazon Q understands local workspaces, AWS resources and documentation, and connected private repositories. AWS also documents native and MCP-based tools for agentic workflows.Confirmed | Context and extensibility — Team capability distribution: Codex uses AGENTS.md, configuration, rules, skills, plugins, MCP, hooks, and programmable interfaces to align tasks with project and team requirements.Confirmed | Amazon Q Developer product overview Introducing the Codex app |
| Parallel agentsParallelism is the main throughput advantage of moving from pair programming to agent orchestration. | Agents and transformation workflows — Parallel agents: Amazon Q provides task-oriented coding agents and specialized transformation agents rather than a general multi-agent worktree manager. Transformation workflows target Java upgrades and .NET modernization.Confirmed | Agents and orchestration — Parallel agents: Codex supports multiple agents running in parallel across projects. Built-in worktrees isolate local tasks, cloud environments isolate delegated work, and scheduled Automations handle recurring jobs.Confirmed | Amazon Q Developer product overview OpenAI Codex product overview |
| Git worktree isolationWorktrees let multiple agents change one repository without colliding in the same checkout. | Agents and transformation workflows — Git worktree isolation: Amazon Q provides task-oriented coding agents and specialized transformation agents rather than a general multi-agent worktree manager. Transformation workflows target Java upgrades and .NET modernization.Confirmed | Agents and orchestration — Git worktree isolation: Codex supports multiple agents running in parallel across projects. Built-in worktrees isolate local tasks, cloud environments isolate delegated work, and scheduled Automations handle recurring jobs.Confirmed | Amazon Q Developer product overview OpenAI Codex product overview |
| Cloud agentsCloud execution keeps long tasks running without tying them to developer hardware. | Agents and transformation workflows — Cloud agents: Amazon Q provides task-oriented coding agents and specialized transformation agents rather than a general multi-agent worktree manager. Transformation workflows target Java upgrades and .NET modernization.Confirmed | Agents and orchestration — Cloud agents: Codex supports multiple agents running in parallel across projects. Built-in worktrees isolate local tasks, cloud environments isolate delegated work, and scheduled Automations handle recurring jobs.Confirmed | Amazon Q Developer product overview OpenAI Codex product overview |
| SubagentsSubagents allow a primary task to delegate exploration and implementation without blocking the parent workflow. | Agents and transformation workflows — Subagents: Amazon Q provides task-oriented coding agents and specialized transformation agents rather than a general multi-agent worktree manager. Transformation workflows target Java upgrades and .NET modernization.Confirmed | Agents and orchestration — Subagents: Codex supports multiple agents running in parallel across projects. Built-in worktrees isolate local tasks, cloud environments isolate delegated work, and scheduled Automations handle recurring jobs.Confirmed | Amazon Q Developer product overview OpenAI Codex product overview |
| Local and cloud continuityContinuity determines whether developers can delegate, resume, and locally verify work without recreating context. | Agents and transformation workflows — Local and cloud continuity: Amazon Q provides task-oriented coding agents and specialized transformation agents rather than a general multi-agent worktree manager. Transformation workflows target Java upgrades and .NET modernization.Confirmed | Agents and orchestration — Local and cloud continuity: Codex supports multiple agents running in parallel across projects. Built-in worktrees isolate local tasks, cloud environments isolate delegated work, and scheduled Automations handle recurring jobs.Confirmed | Amazon Q Developer product overview OpenAI Codex product overview |
| Scheduled automationsScheduled background work is essential for recurring triage, monitoring, and maintenance rather than one-off coding. | Agents and transformation workflows — Scheduled automations: Amazon Q provides task-oriented coding agents and specialized transformation agents rather than a general multi-agent worktree manager. Transformation workflows target Java upgrades and .NET modernization.Confirmed | Agents and orchestration — Scheduled automations: Codex supports multiple agents running in parallel across projects. Built-in worktrees isolate local tasks, cloud environments isolate delegated work, and scheduled Automations handle recurring jobs.Confirmed | Amazon Q Developer product overview OpenAI Codex product overview |
| Mobile and remote supervisionRemote supervision matters when agents run longer than a normal editor session or need approval away from a desk. | Agents and transformation workflows — Mobile and remote supervision: Amazon Q provides task-oriented coding agents and specialized transformation agents rather than a general multi-agent worktree manager. Transformation workflows target Java upgrades and .NET modernization.Confirmed | Agents and orchestration — Mobile and remote supervision: Codex supports multiple agents running in parallel across projects. Built-in worktrees isolate local tasks, cloud environments isolate delegated work, and scheduled Automations handle recurring jobs.Confirmed | Amazon Q Developer product overview OpenAI Codex product overview |
| Diff review and feedbackA strong review surface keeps humans in control without forcing them to inspect an agent's entire execution log. | Code review and delivery — Diff review and feedback: Amazon Q connects implementation with security scans, code-quality review, generated diffs, tests, application upgrades, and repository workflows. It does not provide a general standalone deployment platform.Confirmed | Delivery and code review — Diff review and feedback: Codex connects implementation with diff review, testing, GitHub, pull requests, and dedicated code review. Local and cloud output remains reviewable before it is merged.Confirmed | Amazon Q Developer code reviews OpenAI Codex product overview |
| Git isolation and rollbackRollback and isolation reduce the cost of trying alternative implementations or recovering from a poor edit. | Code review and delivery — Git isolation and rollback: Amazon Q connects implementation with security scans, code-quality review, generated diffs, tests, application upgrades, and repository workflows. It does not provide a general standalone deployment platform.Confirmed | Delivery and code review — Git isolation and rollback: Codex connects implementation with diff review, testing, GitHub, pull requests, and dedicated code review. Local and cloud output remains reviewable before it is merged.Confirmed | Amazon Q Developer code reviews OpenAI Codex product overview |
| Pull-request workflowPull-request integration determines how easily delegated work enters a normal engineering review process. | Code review and delivery — Pull-request workflow: Amazon Q connects implementation with security scans, code-quality review, generated diffs, tests, application upgrades, and repository workflows. It does not provide a general standalone deployment platform.Confirmed | Delivery and code review — Pull-request workflow: Codex connects implementation with diff review, testing, GitHub, pull requests, and dedicated code review. Local and cloud output remains reviewable before it is merged.Confirmed | Amazon Q Developer code reviews OpenAI Codex product overview |
| Dedicated code reviewDedicated review can find defects independently of the agent that authored the change, but packaging and cost differ. | Code review and delivery — Dedicated code review: Amazon Q connects implementation with security scans, code-quality review, generated diffs, tests, application upgrades, and repository workflows. It does not provide a general standalone deployment platform.Confirmed | Delivery and code review — Dedicated code review: Codex connects implementation with diff review, testing, GitHub, pull requests, and dedicated code review. Local and cloud output remains reviewable before it is merged.Confirmed | Amazon Q Developer code reviews OpenAI Codex product overview |
| CI and PR follow-throughFollow-through reduces the manual loop of watching checks, reading failures, patching, and waiting again. | Code review and delivery — CI and PR follow-through: Amazon Q connects implementation with security scans, code-quality review, generated diffs, tests, application upgrades, and repository workflows. It does not provide a general standalone deployment platform.Confirmed | Delivery and code review — CI and PR follow-through: Codex connects implementation with diff review, testing, GitHub, pull requests, and dedicated code review. Local and cloud output remains reviewable before it is merged.Confirmed | Amazon Q Developer code reviews OpenAI Codex product overview |
| Verification artifactsArtifacts make it possible to judge whether an agent actually tested and inspected its work. | Code review and delivery — Verification artifacts: Amazon Q connects implementation with security scans, code-quality review, generated diffs, tests, application upgrades, and repository workflows. It does not provide a general standalone deployment platform.Confirmed | Delivery and code review — Verification artifacts: Codex connects implementation with diff review, testing, GitHub, pull requests, and dedicated code review. Local and cloud output remains reviewable before it is merged.Confirmed | Amazon Q Developer code reviews OpenAI Codex product overview |
| Free planA free plan supports a real repository trial before procurement or team rollout. | $0/plan — Free entry available. Perpetual Free — 50 agentic requests and 1,000 transformation lines per month | $0/plan — Free entry available. Codex is included across ChatGPT plans, including Free and Go, with limits that vary by plan | Amazon Q Developer pricing Using Codex with your ChatGPT plan |
| Personal paid entryShows the recurring commitment required for sustained personal use without conflating a client subscription with a platform bundle. | $19/user/month — Amazon Q Developer Pro. Amazon Q Developer Pro. Free includes monthly request and transformation limits. Pro is $19 per user per month with higher agentic limits, 4,000 transformation lines per user pooled by payer account, and $0.003 per additional submitted transformation line. | $null/plan-dependent — See official pricing. No standalone individual price is listed in the reviewed pricing material. Codex usage draws from the plan's agentic usage and credit pool. The current rate card primarily maps model input, cached-input, and output tokens to credits. | Amazon Q Developer pricing Using Codex with your ChatGPT plan |
| Primary usage unitThe billing unit determines whether cost forecasting follows requests, model list prices, tokens, or credits. | Pricing and usage — Primary usage unit: Amazon Q Developer has a perpetual Free tier and a $19-per-user monthly Pro tier. Free has fixed monthly agentic and transformation limits; Pro adds higher limits, administration, privacy defaults, and IP indemnity.Confirmed | Pricing and usage — Primary usage unit: Codex is included through ChatGPT plans rather than sold only as one standalone client subscription. Limits vary by plan, and additional use is managed through a credits system whose cost depends on model and token mix.Confirmed | Amazon Q Developer pricing Using Codex with your ChatGPT plan |
| Overage behaviorOverage rules determine whether work stops at a limit or continues with a variable bill. | Pricing and usage — Overage behavior: Amazon Q Developer has a perpetual Free tier and a $19-per-user monthly Pro tier. Free has fixed monthly agentic and transformation limits; Pro adds higher limits, administration, privacy defaults, and IP indemnity.Confirmed | Pricing and usage — Overage behavior: Codex is included through ChatGPT plans rather than sold only as one standalone client subscription. Limits vary by plan, and additional use is managed through a credits system whose cost depends on model and token mix.Confirmed | Amazon Q Developer pricing Using Codex with your ChatGPT plan |
| Team entry planTeam pricing determines the baseline before variable model use, review, and enterprise controls. | $19/user/month — Amazon Q Developer Pro with Identity Center. Amazon Q Developer Pro with Identity Center. Free includes monthly request and transformation limits. Pro is $19 per user per month with higher agentic limits, 4,000 transformation lines per user pooled by payer account, and $0.003 per additional submitted transformation line. | $null/plan-dependent — See official pricing. No standalone team price is listed in the reviewed pricing material. Codex usage draws from the plan's agentic usage and credit pool. The current rate card primarily maps model input, cached-input, and output tokens to credits. | Amazon Q Developer pricing Using Codex with your ChatGPT plan |
| Code-review billingReview volume can become a material cost separate from interactive coding. | Pricing and usage — Code-review billing: Amazon Q Developer has a perpetual Free tier and a $19-per-user monthly Pro tier. Free has fixed monthly agentic and transformation limits; Pro adds higher limits, administration, privacy defaults, and IP indemnity.Confirmed | Pricing and usage — Code-review billing: Codex is included through ChatGPT plans rather than sold only as one standalone client subscription. Limits vary by plan, and additional use is managed through a credits system whose cost depends on model and token mix.Confirmed | Amazon Q Developer pricing Using Codex with your ChatGPT plan |
| Enterprise billing and usage administrationLarge teams need spend visibility, procurement support, allocation controls, and auditability in addition to feature access. | Pricing and usage — Enterprise billing and usage administration: Amazon Q Developer has a perpetual Free tier and a $19-per-user monthly Pro tier. Free has fixed monthly agentic and transformation limits; Pro adds higher limits, administration, privacy defaults, and IP indemnity.Confirmed | Pricing and usage — Enterprise billing and usage administration: Codex is included through ChatGPT plans rather than sold only as one standalone client subscription. Limits vary by plan, and additional use is managed through a credits system whose cost depends on model and token mix.Confirmed | Amazon Q Developer pricing Using Codex with your ChatGPT plan |
| Training-data policySource code and prompts may contain proprietary logic, credentials, or regulated data. | Security, privacy, and governance — Training-data policy: Amazon Q Developer uses AWS identity and security controls, code-reference tracking, public-code suppression, telemetry settings, and different content-sharing defaults by tier. Pro proprietary content is not used for service improvement.Confirmed | Security and governance — Training-data policy: Codex combines OS-enforced local sandboxing, configurable approvals, default network restrictions, isolated cloud containers, and ChatGPT workspace controls. Data-training defaults depend on whether the user is on a consumer or business plan.Confirmed | Amazon Q Developer data-sharing controls Codex agent approvals and security |
| Local sandboxLocal sandboxing limits the damage of a mistaken or manipulated command on a developer machine. | Security, privacy, and governance — Local sandbox: Amazon Q Developer uses AWS identity and security controls, code-reference tracking, public-code suppression, telemetry settings, and different content-sharing defaults by tier. Pro proprietary content is not used for service improvement.Confirmed | Security and governance — Local sandbox: Codex combines OS-enforced local sandboxing, configurable approvals, default network restrictions, isolated cloud containers, and ChatGPT workspace controls. Data-training defaults depend on whether the user is on a consumer or business plan.Confirmed | Amazon Q Developer data-sharing controls Codex agent approvals and security |
| Cloud execution isolationCloud isolation determines whether agent tasks can access host systems or unrelated organizational data. | Security, privacy, and governance — Cloud execution isolation: Amazon Q Developer uses AWS identity and security controls, code-reference tracking, public-code suppression, telemetry settings, and different content-sharing defaults by tier. Pro proprietary content is not used for service improvement.Confirmed | Security and governance — Cloud execution isolation: Codex combines OS-enforced local sandboxing, configurable approvals, default network restrictions, isolated cloud containers, and ChatGPT workspace controls. Data-training defaults depend on whether the user is on a consumer or business plan.Confirmed | Amazon Q Developer data-sharing controls Codex agent approvals and security |
| Cloud-agent network defaultNetwork access enables dependency installation and research but increases prompt-injection and data-exfiltration risk. | Security, privacy, and governance — Cloud-agent network default: Amazon Q Developer uses AWS identity and security controls, code-reference tracking, public-code suppression, telemetry settings, and different content-sharing defaults by tier. Pro proprietary content is not used for service improvement.Confirmed | Security and governance — Cloud-agent network default: Codex combines OS-enforced local sandboxing, configurable approvals, default network restrictions, isolated cloud containers, and ChatGPT workspace controls. Data-training defaults depend on whether the user is on a consumer or business plan.Confirmed | Amazon Q Developer data-sharing controls Codex agent approvals and security |
| Command approvalsApproval policy controls how often an agent can act autonomously versus requiring a human checkpoint. | Security, privacy, and governance — Command approvals: Amazon Q Developer uses AWS identity and security controls, code-reference tracking, public-code suppression, telemetry settings, and different content-sharing defaults by tier. Pro proprietary content is not used for service improvement.Confirmed | Security and governance — Command approvals: Codex combines OS-enforced local sandboxing, configurable approvals, default network restrictions, isolated cloud containers, and ChatGPT workspace controls. Data-training defaults depend on whether the user is on a consumer or business plan.Confirmed | Amazon Q Developer data-sharing controls Codex agent approvals and security |
| SSO and SCIMIdentity federation and automated provisioning are required for reliable access removal and enterprise onboarding. | Security, privacy, and governance — SSO and SCIM: Amazon Q Developer uses AWS identity and security controls, code-reference tracking, public-code suppression, telemetry settings, and different content-sharing defaults by tier. Pro proprietary content is not used for service improvement.Confirmed | Security and governance — SSO and SCIM: Codex combines OS-enforced local sandboxing, configurable approvals, default network restrictions, isolated cloud containers, and ChatGPT workspace controls. Data-training defaults depend on whether the user is on a consumer or business plan.Confirmed | Amazon Q Developer data-sharing controls Codex agent approvals and security |
| Audit and policy controlsPolicy controls let security teams constrain repositories, models, tools, networks, and access while preserving an audit trail. | Security, privacy, and governance — Audit and policy controls: Amazon Q Developer uses AWS identity and security controls, code-reference tracking, public-code suppression, telemetry settings, and different content-sharing defaults by tier. Pro proprietary content is not used for service improvement.Confirmed | Security and governance — Audit and policy controls: Codex combines OS-enforced local sandboxing, configurable approvals, default network restrictions, isolated cloud containers, and ChatGPT workspace controls. Data-training defaults depend on whether the user is on a consumer or business plan.Confirmed | Amazon Q Developer data-sharing controls Codex agent approvals and security |
“Not publicly confirmed” means the reviewed first-party sources did not establish the capability. It does not mean “unsupported.” No star ratings, review counts, or paid rankings are used.
Editorial bottom line
Choose the workflow that fits the team
Both products can be relevant to AI-assisted software work. Compare the product form, available execution surfaces, documented workflow, pricing model, and governance requirements against the same repository task.
Choose Codex when
Choose Codex when developers who want the same coding agent in ChatGPT, an IDE, and the terminal.
Evaluate both when
Run the same representative repository task and compare output quality, review effort, execution surface, and governance requirements.
Cost scenarios
Compare pricing by workload, not sticker price
Free evaluation
Start with the documented free entry points before comparing paid usage.
Amazon Q Developer: Perpetual Free — 50 agentic requests and 1,000 transformation lines per month
Codex: Codex is included across ChatGPT plans, including Free and Go, with limits that vary by plan
Run the same scoped task in both products and compare review effort, output quality, and limits before standardizing.Daily individual use
Compare the published individual entry and the documented usage model.
Amazon Q Developer: $19/user/month — Amazon Q Developer Pro. Free includes monthly request and transformation limits. Pro is $19 per user per month with higher agentic limits, 4,000 transformation lines per user pooled by payer account, and $0.003 per additional submitted transformation line.
Codex: See official pricing. Codex usage draws from the plan's agentic usage and credit pool. The current rate card primarily maps model input, cached-input, and output tokens to credits.
Use actual workload data rather than treating plans with different usage units as directly equivalent.Governed engineering team
Evaluate governance, billing, identity, and deployment requirements alongside the seat or usage model.
Amazon Q Developer: $19/user/month — Amazon Q Developer Pro with Identity Center. Free includes monthly request and transformation limits. Pro is $19 per user per month with higher agentic limits, 4,000 transformation lines per user pooled by payer account, and $0.003 per additional submitted transformation line.
Codex: See official pricing. Codex usage draws from the plan's agentic usage and credit pool. The current rate card primarily maps model input, cached-input, and output tokens to credits.
Validate the exact plan and execution surface with both vendors before making a governance decision.Workflow fit
Recommendations by team scenario
Choose Amazon Q Developer for its documented primary workflow
Amazon Q Developer is positioned as Enterprise coding assistant integrated with AWS development and operations. Its source-reviewed guide is the right place to validate its detailed workflow, tradeoffs, and operating model.
Choose Codex for its documented primary workflow
Codex is positioned as Cross-surface coding agent and multi-agent command center. Its source-reviewed guide is the right place to validate its detailed workflow, tradeoffs, and operating model.
Run a governed pilot before standardizing
Product form alone is not enough for a governance decision. Review the official security, privacy, pricing, and execution documentation for the exact plan and deployment model.
FAQ
Questions about Amazon Q Developer and Codex
What is the main difference between Amazon Q Developer and Codex?
Amazon Q Developer is positioned as Enterprise coding assistant integrated with AWS development and operations. Codex is positioned as Cross-surface coding agent and multi-agent command center. The aligned matrix shows how those product forms map to surfaces, workflow, pricing, and governance evidence.
Does Amazon Q Developer or Codex have a free entry point?
Amazon Q Developer: Perpetual Free — 50 agentic requests and 1,000 transformation lines per month Codex: Codex is included across ChatGPT plans, including Free and Go, with limits that vary by plan
How should a team evaluate Amazon Q Developer versus Codex?
Run the same representative repository task in both products, then compare the documented execution surface, review effort, output quality, usage limits, and required governance controls.
Which product is safer for private company code?
There is no universal answer. Review the official security, privacy, network, approval, identity, and audit documentation for the exact plan and execution surface your team will use.
Methodology and sources
Primary evidence behind the matrix
Each field is grounded in current first-party product, documentation, pricing, security, privacy, changelog, or help material.
- Amazon Q Developer product overview · verified 2026-07-12
- What is Amazon Q Developer · verified 2026-07-12
- OpenAI Codex product overview · verified 2026-07-12
- Introducing the Codex app · verified 2026-07-12
- Using Codex with your ChatGPT plan · verified 2026-07-12
- Amazon Q Developer pricing · verified 2026-07-12
- Codex rate card · verified 2026-07-12
- Amazon Q Developer code reviews · verified 2026-07-12
- Amazon Q Developer FAQ · verified 2026-07-12
- Introducing upgrades to Codex · verified 2026-07-12
- Amazon Q Developer agentic coding · verified 2026-07-12
- Codex documentation · verified 2026-07-12
- Amazon Q Developer Transform · verified 2026-07-12
- Amazon Q Developer data-sharing controls · verified 2026-07-12
- Amazon Q Developer data protection · verified 2026-07-12
- Codex agent approvals and security · verified 2026-07-12
- OpenAI business data privacy · verified 2026-07-12
- SSO for ChatGPT Business · verified 2026-07-12
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