Best AI coding tools and agents, with Bug Bench data

For most developers, the best AI coding tools are Claude Code and Codex, coding agents that take a task, edit files across a repo and run commands. In the AI-written code cubic reviewed in the week of Oct 5, 2026, Claude Code wrote 78.1% and Codex 18.8%. The models with the lowest relative bug rate inside them were Claude Fable 5.1, statistically tied with Claude Sonnet 5.5, and GPT-5.6 Sol.

Those shares describe code reviewed by cubic, not the whole market. If you'd rather stay in an editor, Cursor and GitHub Copilot are the main options. OpenCode and Gemini CLI are open-source agents, and OpenCode includes free models.

Product details below come from each vendor's docs and pricing pages as of Oct 13, 2026. The bug data comes from Bug Bench, our public benchmark of the bugs we find in AI-written code.

What Bug Bench shows about AI coding agents

Bug Bench ranks AI coding models by the bugs we find in the code they write. Its coding agents page adds two things per agent: its share of the AI-written code we reviewed, and the model with the lowest bug rate inside it.

Gemini CLI and GitHub Copilot aren't on the coding agents page, so Bug Bench publishes no agent data for them.

How to read the numbers:

• Relative bug rate: counted bugs per AI-attributed line in code we reviewed, divided by the rate across all AI-attributed lines in the window. 1.00 is average, and lower is better.

• Counted bug: a finding from our review on AI-written code that a developer upvoted or an AI coding agent addressed.

• Statistically tied: the two 95% confidence intervals overlap, so neither model is clearly ahead.

• Observational, not causal: teams choose their models, so a rate reflects the code each model was used for as well as the model.

Two agents wrote almost all of it

Claude Code and Codex together wrote 96.9% of the AI-written code we reviewed in the week of Oct 5. Shares move from week to week, though. Claude Code dipped to 50.2% in the week of Aug 17, Codex peaked at 38.4% in the week of Aug 24, and Cursor peaked at 10.4% in the week of Aug 17.

The model inside the agent matters

Inside Claude Code, rates ran from 1.09 for Claude Fable 5.1 to 1.49 for Claude Opus 5.5. Inside Codex, GPT-5.6 Sol had 0.62, or 38% fewer counted bugs than the all-model average, while GPT-6 Astra had 1.13 and GPT-6.1 Sol 1.22 (two weeks of data), statistically tied with each other. Inside Cursor, both ranked models had point estimates above the average, at 1.28 and 1.52, and the two are statistically tied.

Early data on the vendors' suggested models

Claude Code defaults to Opus 5.5 on Pro, Max, Team, Enterprise and the Anthropic API, and Opus 5.5 had 1.49 inside Claude Code. OpenAI recommends GPT-6.1 Sol for complex coding and agentic workflows, and it had 1.22 inside Codex, statistically tied with GPT-6 Astra. Head to head across all agents, GPT-6.1 Sol had 18% fewer counted bugs per line than Opus 5.5 (1.23 vs 1.50).

Both rates rest on two or three weeks of code. Opus 5.5 first appeared in the data in the week of Sep 21, and GPT-6.1 Sol in the week of Sep 28.

What the data can't tell you

• Bug Bench doesn't publish one bug rate per agent. Each rate compares a model inside one agent with the all-model average, so the data doesn't say which agent writes fewer bugs.

• Teams pick models for different work, so a model that gets the hardest tasks carries that in its rate.

AI coding agents vs AI coding assistants

GitHub's Copilot docs describe two ways AI helps you code (about GitHub Copilot):

• Assistive: the tool responds while you work by suggesting, answering or explaining code, and you review and apply each suggestion.

• Agentic: you describe a goal and the tool works through multiple steps. It researches the repository, proposes a plan, edits files and runs tools, then hands the work back for your review.

An AI coding assistant works at your cursor. A coding agent works on a whole task. Most tools now do both, but each leans one way. Claude Code, Codex, OpenCode and Gemini CLI are built around the agent. Cursor and Copilot put an agent inside the editor, next to autocomplete.

The best AI coding tools at a glance

The six tools, one by one

Claude Code

Anthropic describes Claude Code as "an agentic coding tool that reads your codebase, edits files, runs commands, and integrates with your development tools" (overview).

• Where it runs: the claude CLI on macOS, Linux, WSL and Windows, a VS Code extension that also installs in Cursor, a JetBrains plugin, the Claude desktop app, the web at claude.ai/code, and the Claude apps for iOS and Android (platforms).

• Models: Claude only. On the Anthropic API, the opus, sonnet and fable aliases point to Opus 5.5, Sonnet 5.5 and Fable 5.1, and Opus 5.5 is the default on paid plans (model configuration). It also runs through Amazon Bedrock, Google Cloud's Agent Platform and Microsoft Foundry.

• Pricing: included in all paid Claude plans, sharing one usage pool with the rest of the plan. For heavy use, Anthropic points to pay-as-you-go API credits through a Console account (Claude pricing).

• Bug Bench: 78.1% of the AI-written code we reviewed in the week of Oct 5. Fable 5.1 had the lowest rate inside it, 1.09, statistically tied with Sonnet 5.5 at 1.24.

• Suits: developers who hand off whole tasks and review the result, and teams that already pay for Claude.

Our guide to using Claude Code covers setup and team habits.

Codex

Codex is OpenAI's coding agent, documented at learn.chatgpt.com.

• Where it runs: the Codex CLI on macOS, Linux and Windows; an IDE extension for VS Code, Cursor and Windsurf, with JetBrains IDEs and Xcode on their own integrations; the ChatGPT desktop app; and Codex Cloud, which runs tasks in cloud environments you follow from the web, mobile or desktop app.

• Models: OpenAI's GPT models. OpenAI recommends GPT-6.1 Sol for complex coding and agentic workflows, GPT-6 Astra for the hardest end-to-end work and GPT-6 Luna for focused, repeatable tasks.

• Sandbox and source: local commands run in a sandbox by default (sandbox), and the CLI is open source at openai/codex (open source).

• Pricing: included in ChatGPT plans. Free and Go get GPT-6 Luna in the desktop app, subject to rollout, and Plus adds Codex on the web, in the CLI, in the IDE extension and on iOS. An API key covers the CLI, SDK and IDE extension at API rates (Codex pricing).

• Bug Bench: 18.8% of the AI-written code we reviewed in the week of Oct 5, down from 21.4% in the week of Jun 22. GPT-5.6 Sol had 0.62 inside Codex with no tie, and it ranks first of seven models across all agents, at 0.65.

• Suits: ChatGPT subscribers, teams that prefer GPT models, and anyone who wants a sandbox on by default or a CLI they can read and fork.

Cursor

Cursor's docs call it "a coding agent for building ambitious software." It's a desktop code editor with an agent, tab completions and models from several labs. Cursor is now part of SpaceX, which acquired it.

• Where it runs: the Cursor desktop app; the Cursor CLI on macOS, Linux, WSL and Windows; cloud agents in isolated VMs, started from the desktop app, cursor.com/agents, the iOS app, Slack, GitHub, Linear or an API; and JetBrains IDEs through the Agent Client Protocol, on a paid plan.

• Models: "frontier models from OpenAI, Anthropic, Google, SpaceXAI, and more," including Claude Fable 5.1, Opus 5.5 and Sonnet 5.5, GPT-5.6 Sol, Gemini 3.1 Pro, Grok 4.7 and Composer 2.5 (models and pricing).

• Pricing: Cursor sells individual and team plans, and Cursor pricing lists what each one includes.

• Bug Bench: 1.6% of the AI-written code we reviewed in the week of Oct 5, down from 9.4% in the week of Jun 22. Two models were ranked inside it: Claude Opus 5 at 1.28 and GPT-5.6 Sol at 1.52, statistically tied, with both point estimates above the all-model average. GPT-5.6 Sol is on Cursor's current model list.

• Suits: developers who spend the day in an editor and want autocomplete plus an agent, and teams that want Claude, GPT, Gemini and Grok in one tool.

OpenCode

OpenCode is "an open source AI coding agent" that runs as a terminal interface, a desktop app or an IDE extension (OpenCode docs).

• Where it runs: the terminal on macOS, Linux and Windows (WSL recommended), a desktop app and an IDE extension. Running /init writes an AGENTS.md file for your project.

• Models: bring your own. OpenCode connects to 75+ providers through Models.dev, including local models, and you can sign in with a GitHub Copilot or ChatGPT Plus or Pro account to use that subscription (opencode.ai).

• Pricing: free models are included, or you pay your model provider. Two optional paid services sit on top: Zen, a curated set of tested models charged per request, and Go, monthly plans for open models.

• Bug Bench: 0.7% of the AI-written code we reviewed in the week of Oct 5, down from 3.0% in the week of Jun 22. No model inside it is ranked yet.

• Suits: developers who want an open-source agent, want to switch providers or run local models, or want a different interface for a Copilot or ChatGPT subscription they already have.

Gemini CLI

Gemini CLI is Google's "open-source AI agent that brings the power of Gemini directly into your terminal," licensed under Apache 2.0 (gemini-cli on GitHub).

• Where it runs: the terminal. Install it with npm, Homebrew or MacPorts, and use gemini -p for non-interactive runs in scripts.

• Models: Gemini. The README lists Gemini 3 models with a 1M token context window, and built-in tools for Google Search grounding, file operations, shell commands and web fetching. It supports MCP servers and GEMINI.md context files.

• Access and pricing: since June 18, 2026, Gemini CLI no longer serves Google AI Pro and Ultra subscribers or people using it free through Gemini Code Assist for individuals. Google moved them to Antigravity CLI. Organizations on a Gemini Code Assist Standard or Enterprise license keep access, and it still works with paid Gemini or Gemini Enterprise Agent Platform API keys (Google's announcement).

• Bug Bench: not on our coding agents page, so we have no data on its code.

• Suits: organizations on a Gemini Code Assist Standard or Enterprise license, and teams that already pay for Gemini API access.

GitHub Copilot

GitHub describes Copilot as "an AI assistant that helps you write, understand, and ship software" (about GitHub Copilot). In the editor, it gives inline suggestions and next edit suggestions as you type, answers questions about nearby code and has an agent that can edit files for you.

• Where it runs: VS Code, Visual Studio, JetBrains IDEs, Eclipse and Xcode, plus the GitHub website, GitHub Mobile, the Copilot CLI and the Copilot app (where to use Copilot).

• Models: the paid individual plans list models from several labs, including Claude Sonnet 5.5, Claude Opus 5.5, GPT-5.6 Sol, GPT-6.1 Sol, Gemini 3.8 Flash and Grok 4.7. Copilot Free and Copilot Student use auto model selection only.

• Pricing: Copilot Free (up to 2,000 completions a month), Copilot Student, paid individual plans (Pro, Pro+ and Max), and Business and Enterprise for organizations. Each plan comes with an allowance of GitHub AI Credits (Copilot plans).

• Bug Bench: not on our coding agents page either. Its paid plans do list GPT-5.6 Sol, first of seven models in the overall Bug Bench ranking.

• Suits: developers who want help as they type in the IDE they already use, including Visual Studio, Eclipse or Xcode, and organizations that buy through GitHub and want central policy control.

Compare the tools head to head

Each of these posts goes deeper on one pair or one tool:

• Codex vs Claude Code: OpenAI's and Anthropic's agents compared on models, sandboxing, instruction files and price, with Bug Bench data.

• Cursor vs Claude Code: an AI code editor against Anthropic's agent on models, context, rules, MCP and price, and how to run the two together.

• OpenCode vs Claude Code: an open-source agent that works with almost any model provider against Anthropic's own agent, including rules, permissions and price.

• Gemini CLI vs Claude Code: who can still use Google's open-source terminal agent after the move to Antigravity CLI, and how it compares with Claude Code.

• Cursor vs Codex: an editor with models from several labs against OpenAI's agent, including cloud agents and pricing.

• Codex CLI guide: how to install, sign in to, configure and script OpenAI's open-source terminal agent.

For the model side, see the best LLM for coding, ranked on Bug Bench.

How to choose an AI coding tool

There's no single best AI coding agent for every team. These steps narrow it down.

1. Start with what you already pay for. Claude Code comes with paid Claude plans and Codex with ChatGPT plans. OpenCode can sign in with a Copilot or ChatGPT Plus or Pro account.

2. Decide how much to hand off. For suggestions as you type, use Copilot or Cursor. To hand off a task and review the result, use Claude Code, Codex, OpenCode, Gemini CLI or the agents inside Cursor and Copilot.

3. Choose the model on purpose. Rates inside one agent vary: inside Claude Code they ran from 1.09 to 1.49. The vendors' current default and recommendation, Opus 5.5 and GPT-6.1 Sol, have only two or three weeks of data so far. Read the overall ranking and bug rate against list price next to your vendor's own model guidance before you set a team default.

4. Match where your team works. JetBrains users can run Claude Code, Codex, Cursor's agent or Copilot. Visual Studio and Eclipse users have Copilot, and Xcode users have Copilot and Codex. Terminal-first developers can pick any of the agents.

5. Check openness. The Codex CLI, OpenCode and Gemini CLI are open source, and OpenCode says it doesn't store your code or context data.

6. Write your rules down once. Agents follow the conventions they can read. Our guide to configuring coding agents that follow your team's standards shows how.

7. Measure your own repos. Track review findings by tool and by model for a few weeks before you standardize.

AI-written code still needs review

Every ranked model on Bug Bench has counted bugs, including the best one. GPT-5.6 Sol's overall rate of 0.65 means 35% fewer counted bugs than average, not zero. Each of those is a review finding that a developer upvoted or an agent addressed, so the count leaves out comments nobody acted on.

Whichever tool you pick, review its pull requests before they merge. Our AI code review guide covers what to check and how to roll a reviewer out. On GitHub, cubic installs as an app, reviews every pull request in minutes and comments on bugs, security issues and breaks from your team's rules. For the process around it, see how successful teams ship AI-generated code to production.

FAQ

Which AI tool is best for coding?

For handing off whole tasks, Claude Code and Codex lead. They wrote 78.1% and 18.8% of the AI-written code we reviewed in the week of Oct 5, 2026. For help as you type, Cursor and GitHub Copilot work inside the editor. Whichever you choose, pick the model with care: GPT-5.6 Sol ranks first of seven models on Bug Bench.

What is the difference between an AI coding assistant and an AI coding agent?

An assistant works alongside you. It suggests, answers or explains code, and you apply each suggestion. An agent takes a goal and works through the steps itself, reading the repo, planning, editing files and running commands, then hands the result back for review.

What is the best free AI coding tool?

GitHub Copilot Free includes up to 2,000 completions a month, and ChatGPT Free includes Codex with GPT-6 Luna in the desktop app, subject to rollout. OpenCode is open source and includes free models. Gemini CLI stopped serving its free individual tier on June 18, 2026, when Google moved those users to Antigravity CLI.

Can ChatGPT write code?

Yes. Codex, OpenAI's coding agent, is included in ChatGPT plans and runs in the ChatGPT desktop app, a CLI, an IDE extension and the cloud. In our data, GPT-5.6 Sol had the lowest relative bug rate inside Codex, at 0.62.