development

Best AI for Coding

The best AI coding tools and models compared: Claude Code, OpenAI Codex, GitHub Copilot, Cursor, Devin, Google Antigravity, Amazon Kiro and Cline, ranked on how often their work ships, how many developers use them, independent benchmarks and price, with the models that power them.

Updated October 2026

Quick answer: The best AI for coding for most developers is Claude Code running Claude Opus 5.5, because it is the most-used coding agent in both the Stack Overflow and JetBrains developer surveys, its pull requests had the highest merge rate in Amplifying’s study (91.5%), and Opus 5.5 has the highest score Artificial Analysis has measured on its Intelligence Index (58). For handing off tasks that come back as pull requests, OpenAI Codex, because 87.5% of the roughly 7.8 million public pull requests it has opened were merged, the highest share PR Arena tracks. For teams that review every change inside GitHub, GitHub Copilot, because 80.5% of its agent’s merged pull requests had a human reviewer. For an AI-first editor, Cursor. For the lowest cost, the open-source Cline with a cheap model such as Claude Haiku 5.5 or DeepSeek V4.1-Flash. The caveat: a merged pull request is not proof of correct code, and 56% of the merged agent pull requests Amplifying sampled had no human reviewer.

This page ranks the tools developers code with and the models inside them. Three neighbouring pages go deeper on their own subjects: best AI agents for general-purpose agents, best AI code review for the tools that check a pull request, and best AI app builders for building an app from a prompt. The full model ranking is on best AI models.

The current state of AI coding

Four facts describe where AI coding stands.

1. The unit of work is now a task, not a keystroke. In JetBrains’ survey of more than 15,000 professional developers, 90% used an AI coding agent at work at least weekly and 68% daily. Every leading tool now plans a change, edits files across a repository, runs the tests and hands back a result.
2. Claude Code overtook GitHub Copilot. In the same survey, 39% used Claude Code at work, up from 18% in January, against 21% for GitHub Copilot (down from 29%), 16% for OpenAI Codex (up from 3%) and 12% for Cursor (down from 18%).
3. There is now real-world evidence of what ships. PR Arena and Amplifying count the pull requests agents open on public GitHub repositories and how many are merged, which measures accepted work rather than a benchmark score.
4. Who owns a tool now decides which models it can run. SpaceX’s $60 billion acquisition of Cursor’s maker, Anysphere, closed on 14 August 2026, and OpenAI said on 30 August that it will stop supplying its models to Cursor on 12 November 2026.

Top AI models for coding

The model inside the tool matters as much as the tool. This table covers generally available models, with independent figures from Artificial Analysis and each model’s own page on this site.

Three things stand out.

• Claude Opus 5.5 is the highest-scoring model anyone can use. It leads the Intelligence Index at 58. Claude Sonnet 5.5 beats it on Terminal-Bench 4.0 on both Anthropic’s harness and Artificial Analysis’s, at half the token price, but cost more per completed index task because it used more output tokens.
• GPT-6.1 Sol is the value pick. It scores 52 on the index, one point below GPT-6 Astra, at a fifth of Astra’s token price and $0.72 per completed task.
• The cheap tier is now usable for routine work. Claude Haiku 5.5 scores 43 at $0.10/$0.50 for prompts up to 100,000 tokens, and DeepSeek V4.1-Flash scores 39 with MIT-licensed weights.

Anthropic’s Mythos-class Claude Fable 5.1 scores 53 on the index at $10/$50, level with GPT-6 Astra, and its sibling Claude Mythos 5.1 is restricted to vetted organisations.

Real-world capability — SWE-bench Verified (top 10)

SWE-bench Verified is older and Python-only, and none of the current flagships has published a score on it: Anthropic gave no SWE-bench figure for Claude Opus 5.5, Sonnet 5.5, Haiku 5.5 or Fable 5.1, and OpenAI stopped quoting it in February 2026. The table lists the highest published scores, per the llm-stats tracker and Anthropic’s launch figure for Opus 5.

Every model in this table has since been succeeded. Read it as the record of what was published, not as a ranking of what to use today; the table above covers the current models.

Standardized harness — SWE-bench Pro (Scale SEAL public set)

Run every model through identical scaffolding and the order changes. Scale’s SEAL board covers 1,865 tasks across 41 professional repositories:

Scale has not scored Claude Opus 5.5, Claude Sonnet 5.5, GPT-6 Astra, GPT-6.1 Sol, Grok 4.7 or Gemini 3.8 Flash. On their makers’ own harnesses, GPT-5.6 Sol reported 64.6%, Grok 4.5 64.7% and Claude Opus 5 79.2%.

Why the two tables disagree — and which to trust

The same model family scores 51.9% (Opus 4.6 on Scale’s harness) and 69.2% (Opus 4.8 on Anthropic’s own harness) on the same benchmark. Both numbers are real; the difference is the scaffold — retrieval, context management and tool design — not the model. Anthropic reported Fable 5 at 80.3% SWE-bench Pro on its own stack, while Scale’s standardised board tops out at 61.5%.

Treat vendor launch numbers as a ceiling and standardised leaderboards as a floor. A mid-tier model in a strong harness can beat a frontier model in a weak one, which is why the merge data in the tools section below is the more useful guide to what ships.

The Mythos-class frontier: Fable and Mythos

Anthropic’s Mythos-class models sit above Opus. Claude Fable 5 posted the highest SWE-bench scores any model has published, 95.0% on Verified and 80.3% on Pro on Anthropic’s harness, and its restricted sibling is Claude Mythos 5. Their successors, Claude Fable 5.1 and Claude Mythos 5.1, published no SWE-bench figure. Fable 5.1 costs $10/$50 per million tokens and scores 53 on the Artificial Analysis Intelligence Index, five points below Claude Opus 5.5 at $4/$20, and Mythos 5.1 is limited to vetted organisations.

What these benchmark scores actually mean

A SWE-bench Verified score of 88.6% means the model resolved roughly nine in ten real GitHub issues in a controlled harness with generous compute. In a production IDE with latency limits and a private repository, expect lower. SWE-bench tasks are open-source Python issues; on Scale’s private, commercial set the order reshuffles again, with Opus 4.6 leading at 47.1% (Scale).

Best AI coding tools and agents compared

Ranked on how often each tool’s work is merged, how many developers use it, and what independent tests show. Merge figures are each agent’s merged pull requests as a share of all it opened on public GitHub repositories; usage is the share of 12,255 Stack Overflow respondents who used the tool in the past year.

What ships: merge rates and review

Two independent trackers supply the merge figures. PR Arena identifies agent pull requests by branch prefix or bot account; it does not track Claude Code. Amplifying’s State of the Coding Agent Market does, and also sampled 268 merged agent pull requests in significant repositories to see how many a human had reviewed.

Two cautions apply. PR Arena’s headline rate counts only ready-for-review pull requests, which puts GitHub Copilot at 96.0%; the table uses merged pull requests as a share of everything opened, drafts included. And a merge is not proof the code is right: 56% of the merged agent pull requests in Amplifying’s sample had no human reviewer, so a high merge rate partly measures how often nobody looked.

1. Claude Code — most-loved, best model access

Price: Included with Claude Pro ($20 a month, or $17 billed annually) and Max (from $100 a month); also on Team and Enterprise plans and through the API. Not included with the free Claude plan (Anthropic). Runs in: Terminal, desktop app, VS Code and JetBrains extensions, cloud sessions Models: Claude Opus 5.5, Sonnet 5.5, Haiku 5.5

Claude Code is Anthropic’s coding agent and the most-used one in both of the year’s large developer surveys: 65.5% of 12,255 respondents to the Stack Overflow Developer Survey 2026 had used it in the past year, and 39% of professional developers in JetBrains’ survey use it at work, where 31% named it their most-used tool. In JetBrains’ earlier April survey, 46% of developers named it their most-loved tool, against 19% for Cursor and 9% for GitHub Copilot (market analysis). Its pull requests had a 91.5% merge rate in Amplifying’s study, the highest of the agents measured.

It runs Anthropic’s models only. Claude Opus 5.5 scores 58 on the Artificial Analysis Intelligence Index, the highest it has measured, and Claude Sonnet 5.5 scores 56 at half the token price. Claude Code supports subagents, hooks and Model Context Protocol (MCP) connections to outside tools, and select Pro and Max subscribers can try a beta of redesigned Projects in which Claude splits a job across parallel cloud sessions, each on its own branch.

Limitations: Claude models only. Subscription plans carry usage limits. Only 30.5% of its merged pull requests in Amplifying’s sample had a human reviewer, among the lowest shares measured.

Best for: Developers who want one agent for interactive work and hand-offs, on the highest-scoring generally available model.

2. OpenAI Codex — highest merge rate, now on GPT-6

Price: Included with ChatGPT Plus ($20 a month) and the Pro, Business and Enterprise plans Runs in: Command line, IDE extension, desktop app, cloud, GitHub, Slack and mobile (OpenAI) Models: GPT-6 Astra, GPT-6.1 Sol

Codex’s delegated work ships more often than any other agent PR Arena tracks: 87.5% of the roughly 7.8 million public pull requests it has opened were merged, more pull requests than every other tracked agent combined. Amplifying reports the same merge rate and found 69.2% of Codex’s merged pull requests touch tests, the highest share it measured. Its use at work rose from 3% to 16% of professional developers in six months in JetBrains’ survey.

The models are strong on agent benchmarks. GPT-6 Astra scores 62 on Artificial Analysis’s Coding Agent Index, level with Claude Fable 5.1, and GPT-6.1 Sol scores 60 at maximum effort for $0.72 per completed index task, at a fifth of Astra’s token price.

Limitations: OpenAI models only. Only 28.6% of its merged pull requests in Amplifying’s sample had a human reviewer, the lowest share of the five agents ranked on merge data. OpenAI published no SWE-bench figure for the GPT-6 models.

Best for: Developers and teams who hand off many well-defined tasks and want pull requests with tests attached.

3. GitHub Copilot — broadest reach, now usage-based

Price: Free plan with limited chat and agent use and 2,000 completions a month; Pro $10 a month, Pro+ $39, Max $100, each with a monthly allowance of AI credits; Business and Enterprise are usage-based (GitHub) Runs in: VS Code, JetBrains, Neovim, Visual Studio, Xcode, Eclipse, the command line and GitHub itself Models: Claude, GPT, Gemini and Grok models

GitHub Copilot is the incumbent, used by 58.7% of Stack Overflow respondents in the past year, and it supports more editors than any rival. Its coding agent takes a GitHub issue, works in a cloud environment and opens a draft pull request under the repository’s existing permissions and review rules. That shows in the data: 80.5% of the agent’s merged pull requests in Amplifying’s sample had a human reviewer, the highest share measured.

Its merge rate is lower than the two leaders’. On PR Arena, 72.3% of everything the agent opened was merged; the 96.0% headline figure excludes the quarter of its pull requests that are drafts.

Limitations: A lower merge rate than Claude Code or Codex. Credit-based billing makes heavy agent use harder to forecast. Its use at work fell from 29% to 21% in JetBrains’ survey.

Best for: Teams on GitHub that want agent work to pass through the same review as everyone else’s, and developers on JetBrains, Neovim or Xcode.

4. Cursor — most popular editor (now a SpaceX company)

Price: Hobby plan free; Individual $20 a month; Teams $40 a user a month (Cursor) Runs in: Its own editor, built on VS Code; cloud agents; command line Models: Grok, Cursor’s own Composer, Claude and Gemini; OpenAI’s models until 12 November 2026

Cursor is an AI editor with an agent for multi-file changes and cloud agents that open pull requests. On PR Arena, 67.8% of the pull requests its agents opened were merged, and Amplifying found 77.8% of its merged pull requests had a human reviewer.

SpaceX’s $60 billion acquisition of Cursor’s maker, Anysphere, closed on 14 August 2026. On 30 August, OpenAI said it will stop supplying its models to Cursor on 12 November 2026, stating it cannot be confident SpaceX will honour its terms of service. Claude, Gemini, Grok and Composer are unaffected.

Limitations: OpenAI’s models leave on 12 November 2026. No native JetBrains or Vim version. Its use at work fell from 18% to 12% in JetBrains’ survey.

Best for: Developers who want assisted editing and agents in one VS Code-style editor.

5. Devin Desktop (formerly Windsurf) — agent baked in

Price: From $20 a month Runs in: Its own cloud environment, reached from Slack, Linear or Jira; Devin Desktop editor Models: Several, through the open Agent Client Protocol in Devin Desktop

Devin, from Cognition, takes a ticket and returns a pull request with no developer driving it. Cognition retired the Windsurf brand on 2 June 2026 and relaunched that editor as Devin Desktop, with the Devin agent built in. On PR Arena, 62.6% of the pull requests Devin opened were merged, the lowest share of the five agents with merge data, and 2.9% of Stack Overflow respondents had used it in the past year.

Limitations: The lowest merge rate of the ranked agents with merge data, and a small user base.

Best for: Teams with a backlog of repetitive, clearly specified tickets such as migrations and dependency upgrades.

6. Google Antigravity 2.0 — multi-agent platform

Price: Free individual plan; higher limits with Google AI Pro and Ultra; business plans from $30 a seat a month (Google) Runs in: Desktop app, command line and SDK Models: Gemini

Google launched Antigravity 2.0 at Google I/O on 19 May 2026 as an agent platform in which a manager view runs several agents in parallel. 16.0% of Stack Overflow respondents had used it in the past year and 6% of professional developers in JetBrains’ survey use it at work. Neither merge tracker covers it.

Best for: Developers already paying for Google AI plans who want to run several agents at once.

7. Amazon Kiro — best-value spec-driven agent

Price: Free plan with 50 credits a month; Pro $20 a user a month for 1,000 credits; Pro+ $40; Pro Max $100; Power $200 (Kiro) Runs in: VS Code-style editor, JetBrains and the command line Models: Claude and GPT models on paid plans, plus open-weight models

Kiro writes a specification first and then builds against it. Paid plans include Claude and GPT models and an Auto mode that mixes models; the free plan runs open-weight models. Neither merge tracker nor the Stack Overflow survey lists it.

Best for: AWS-heavy teams that want specifications and standards enforced before code is written.

8. Cline — best open-source, bring-your-own-model

Price: Free; you bring your own API keys Runs in: VS Code extension Models: Any, including local models

Cline is an open-source coding agent that runs whichever model you connect, from Claude and GPT to open-weight models you host yourself. It is the cheapest serious setup when paired with a low-cost model, and it carries no vendor lock-in.

Best for: Privacy-conscious teams and cost optimisers who want control over the model and every token.

Feature comparison: the full matrix

Use-case specific recommendations

For professional full-stack developers

Winner: Claude Code with Claude Opus 5.5 (from $20/month)

The most-used coding agent paired with the highest-scoring generally available model. Use Opus 5.5 for complex, multi-file work and route quick edits to Haiku 5.5 to control cost. Alternative: OpenAI Codex if you hand off many tasks and want pull requests back; Cursor ($20/month) if you prefer an AI-first editor.

For large enterprise codebases

Winner: GitHub Copilot’s coding agent, or Claude Code with a 1M-token context

Copilot’s agent works inside GitHub’s permissions, branch protections and review rules, and 80.5% of its merged work had a human reviewer. Claude Opus 5.5 and Sonnet 5.5 both offer a 1M-token context at standard rates, which matters on big refactors. Alternative: Devin Desktop for an embedded agent on large monorepos.

For terminal and DevOps workflows

Winner: OpenAI Codex with GPT-6 Astra or GPT-6.1 Sol

GPT-6 Astra scores 62 on Artificial Analysis’s Coding Agent Index and 57.7% on Terminal-Bench 4.0 on OpenAI’s harness; GPT-6.1 Sol scores 60 at a fifth of the token price. Claude Code is the close alternative: Claude Sonnet 5.5 leads Terminal-Bench 4.0 at 70.6% on Anthropic’s harness and 64% on Artificial Analysis’s.

For rapid prototyping and MVPs

Winner: Lovable or Bolt.new for the build, Cursor or Claude Code for the finish

Generate a working full-stack app from prompts, then hand off to an agentic editor for the last 30%. Add v0 for production-quality UI components. The builders are ranked on best AI app builders.

For cost optimisation

Winner: Cline with a low-cost model, and a router

Claude Haiku 5.5 costs $0.10/$0.50 per million tokens for prompts up to 100,000 tokens and DeepSeek V4.1-Flash $0.15/$0.60 off-peak, against $4/$20 for Opus 5.5. Pin routine traffic to a cheap model and reserve a flagship for the hard changes; a classifier-based router (for example Morph Router) automates the split. Best value at the top end: GPT-6.1 Sol at $0.72 per completed index task.

For maximum privacy and compliance

Winner: Cline with local or self-hosted models, or DeepSeek V4.1-Flash (MIT)

DeepSeek V4.1-Flash’s MIT licence means the top model on our open-weight ranking is self-hostable outright for air-gapped work, and GLM-5.3 scores 45 on the Artificial Analysis index under its own licence. Best local LLMs covers what runs on your own hardware. For enterprise compliance on a hosted tool, GitHub Copilot offers audit logs and IP indemnity.

For students and beginners

Winner: GitHub Copilot’s free plan

Copilot’s free plan includes chat, agent mode and 2,000 completions a month, and Cursor, Google Antigravity and Amazon Kiro also have free plans. Pair one with a structured course to handle the “70% problem” yourself.

The vibe-coding scene: building apps from prompts

“Vibe coding” — describing an app and letting AI build it — is now mainstream, and the build phase is largely commoditised across tools; pricing, integrations and the last-30% experience differentiate them. The prompt-to-app platforms are ranked on their own page, best AI app builders.

Lovable — best for full-stack apps

Price: From $20/month (Hobby) up through Pro tiers Lovable is the category leader, valued at $13.3 billion after a $400 million Series C on 12 August 2026 (Lovable). It builds complete full-stack apps (frontend, database, auth, payments) from prompts — the lowest barrier to a working SaaS. Still hits the 70% wall on complex business logic.

Bolt.new — best for frontend speed

Price: Free tier, paid from ~$20/month Bolt.new (StackBlitz) builds JavaScript web apps in the browser with live preview, and mobile apps through Expo, and syncs projects to GitHub. Zapier ranks it second of more than 50 vibe coding tools, for flexibility and speed (Zapier).

Replit Agent — best all-in-one

Price: Free tier, paid from ~$25/month Replit bundles app generation with a full dev environment, database and hosting — idea to live URL without touching infrastructure. Agent 4, launched on 11 March 2026, builds web and mobile apps from one project (Replit). Effort-based pricing can climb on complex projects.

Base44 — best for business apps

Price: Free tier, paid from ~$20/month Base44 (owned by Wix) focuses on internal/business apps — CRMs, portals, task managers — with auth, database, role-based permissions and hosting built in. Notably, Base44’s team publicly praised Fable 5 for “one-shotting full apps” at the model’s launch.

v0 by Vercel — best component quality

Price: Free tier (credits), paid from ~$20/month v0 is Zapier’s pick for production-ready code among vibe coding tools (Zapier). Plus costs $30 a user a month, and the free plan allows 7 messages a day.

Recommendation: v0 for components, Bolt for quick frontends, Replit for full-stack with instant deploy, Base44 for internal tools, Lovable for complete SaaS — then hand off to Claude Code or Cursor for the final 30%.

Specialised AI coding tools by category

Code review and QA

• Cursor Bugbot — built-in PR review agent tuned for low false positives; included with Cursor.
• Qodo (formerly Codium) — automated PR reviews across GitHub/GitLab/Bitbucket; ~$19/user/month.
• CodeRabbit — line-by-line AI reviews; free for open source, ~$12/user/month for teams.
• Snyk DeepCode AI — security-focused analysis that catches vulnerabilities in AI-generated code.
• Claude Security — Anthropic’s codebase scanner that finds and proposes fixes for vulnerabilities; its scans run on the restricted Claude Mythos 5 (from 28 August 2026, up from Opus 4.7), the model Anthropic will not sell direct access to, and customers never prompt it directly.

Documentation generation

• Mintlify — auto-generated API docs that track your Git workflow.
• Docuwriter.ai — READMEs, API docs and inline comments; free tier plus paid.

Terminal and CLI tools

• Warp — AI terminal (Agent Mode) that explains commands and generates scripts.
• Aider — open-source terminal pair-programming, model-agnostic.
• WarpGrep — semantic codebase search subagent that upgrades the harness for any model; free tier.

Testing automation

• testRigor — generate tests from plain English.
• Mabl — auto-healing tests that adapt to UI changes.

Open-source / self-hosted assistants

• Continue.dev — VS Code/JetBrains extension with full model flexibility.
• Tabby — self-hosted Copilot alternative running open models locally.
• Cline — see above; the leading BYOK agent.

Pricing comparison: what you’ll actually pay

Tools (typical monthly cost)

Models (per million tokens, USD)

The token price is not the bill. Claude Sonnet 5.5 costs half as much per token as Opus 5.5 but more per completed task at maximum effort, because it uses more output tokens. Subscriptions are cheaper than API billing for steady use until their limits bite. The cheapest reliable pattern is routing: routine work to a low-cost model, hard changes to a flagship.

What developers actually think

The trust paradox deepened

Use is near-universal: 90% of professional developers in JetBrains’ survey used an AI coding agent at work at least weekly, and 73% of respondents to the Stack Overflow Developer Survey 2026 use AI daily. Trust is conditional: 48% trust AI output when they can validate it and 67% when the code is familiar, while only 16% extend that trust to most non-critical tasks. A year earlier, the Stack Overflow 2025 survey found only 29% trusted AI output to be accurate and 3% “highly trusted” it, with 66% citing code that is “almost right, but not quite”.

Productivity is real but uneven

In METR’s randomised trial, experienced open-source developers took 19% longer with AI tools on codebases they knew well, while believing they were faster. The trial used earlier tools than the agents on this page. Only 44% of the merged agent pull requests in Amplifying’s sample had a human reviewer, so much of the speed comes from work nobody else read.

Tool preferences

In the Stack Overflow Developer Survey 2026, 65.5% of 12,255 respondents had used Claude Code in the past year, ahead of GitHub Copilot (58.7%), OpenAI Codex (29.5%) and Cursor (25.5%). In JetBrains’ survey, 39% used Claude Code at work, up from 18% in January, against 21% for GitHub Copilot (down from 29%), 16% for Codex (up from 3%) and 12% for Cursor (down from 18%). Developers run more than one tool: typically one for completions and another for agent work.

Trust varies by geography

In the Stack Overflow 2025 survey, combined trust ranged from India at 56% down to Germany at 22%, a 34-point spread (Stack Overflow). In JetBrains’ survey, Claude Code’s use at work reached 47% among professional developers in the United States.

Recent launches reshaping the market

• Meta shipped Muse Wonder and Muse Wonder Full (12 October 2026). On the table Meta published, Muse Wonder Full scores 79.0 on DeepSWE 1.1 and 57.5 on SWE-Marathon, ahead of Claude Opus 5.5 and GPT-6 Astra, and trails both on Terminal-Bench 4.0 (57.1). It is available only inside Muse Code; Muse Wonder is on the Meta Model API at $4/$20. Meta published no SWE-bench figure.
• Anthropic shipped Claude Haiku 5.5 (7 October 2026). Claude Haiku 5.5 costs $0.10/$0.50 per million tokens for prompts up to 100,000 tokens, 90% below Haiku 4.5, and scores 43 on the Artificial Analysis index.
• OpenAI shipped GPT-6.1 Sol (29 September 2026). GPT-6.1 Sol keeps GPT-6 Sol’s $2/$10 and scores 60 on Artificial Analysis’s Coding Agent Index at maximum effort, two points below GPT-6 Astra.
• Anthropic shipped Claude Sonnet 5.5 (28 September 2026). Claude Sonnet 5.5 scores 56 on the Intelligence Index and leads Terminal-Bench 4.0 at 70.6% on Anthropic’s harness.
• Anthropic and OpenAI both cut prices (22 September 2026). Claude Opus 5.5 shipped at $4/$20, a fifth below Opus 5, and GPT-6 Sol at $2/$10, half the GPT-5.6 rate.
• OpenAI said it will stop supplying Cursor (30 August 2026). Its models leave Cursor on 12 November 2026, following SpaceX’s acquisition of Cursor’s maker.

Frequently asked questions

Which AI coding tool should I use in 2026?

For most developers, Claude Code with Claude Opus 5.5: it is the most-used coding agent in the Stack Overflow and JetBrains surveys and had the highest merge rate in Amplifying’s study, at 91.5%. OpenAI Codex is the better choice for handing off many tasks that come back as pull requests, GitHub Copilot for teams that review everything in GitHub or work in JetBrains, and Cursor for an AI-first editor.

What’s the best AI model for coding right now?

Claude Opus 5.5 is the best generally available model for coding, with the highest score Artificial Analysis has measured on its Intelligence Index (58) and 66.4% on Terminal-Bench 4.0 on Anthropic’s harness. Claude Sonnet 5.5 scores higher on Terminal-Bench 4.0 at half the token price, and GPT-6.1 Sol is the best value at $0.72 per completed index task.

Is Claude Code better than OpenAI Codex?

Claude Code is the better all-round tool and Codex the better one for bulk delegation. Claude Code has the higher merge rate in Amplifying’s study (91.5% against 87.5%) and more than twice the usage in the Stack Overflow survey (65.5% against 29.5%). Codex has opened about 7.8 million public pull requests, and more of its merged work touches tests (69.2% against 47.5%).

What does the SpaceX–Cursor deal mean for me?

Cursor remains a capable AI editor, and its agents’ merged work is reviewed by a person more often than Claude Code’s or Codex’s. The change to plan for is model access: OpenAI’s models leave Cursor on 12 November 2026, while Claude, Gemini, Grok and Cursor’s own Composer models stay.

Is Claude better than GPT for coding?

Claude leads on the independent composite and GPT on price for performance. Claude Opus 5.5 scores 58 on the Artificial Analysis Intelligence Index against 53 for GPT-6 Astra, and Claude Sonnet 5.5 leads Terminal-Bench 4.0. GPT-6 Astra scores 62 on Artificial Analysis’s Coding Agent Index, and GPT-6.1 Sol reaches 60 at $0.72 per completed index task, a fraction of what either Claude model costs per task.

Can I use Claude Fable 5 or Mythos 5 now?

Fable, yes. Claude Fable 5 and its successor Claude Fable 5.1 are generally available at $10/$50 per million tokens. Claude Mythos 5 and Mythos 5.1 are limited to vetted organisations. For most coding, Claude Opus 5.5 scores higher on the Artificial Analysis index than Fable 5.1 at less than half the price.

Why do benchmark scores disagree so much?

Because the harness around a model moves the score as much as the model does. The highest vendor-reported SWE-bench Pro score is 80.3%, on Anthropic’s own harness, while Scale’s standardised board tops out at 61.5%. Vendor figures are a ceiling and standardised figures a floor, and none of the current flagships has published a SWE-bench figure at all.

Are open-source models good enough now?

For routine work, yes. DeepSeek V4.1-Flash scores 39 on the Artificial Analysis Intelligence Index with MIT-licensed weights at $0.15/$0.60 per million tokens off-peak, and GLM-5.3 scores 45. The flagships still lead on the hardest tasks: Claude Opus 5.5 scores 58.

How much does AI coding actually cost?

Most tools start at about $20 a month: Claude Code with Claude Pro, Codex with ChatGPT Plus, Cursor Individual and Amazon Kiro Pro, with GitHub Copilot Pro at $10. GitHub Copilot, Cursor, Google Antigravity, Kiro and Cline have free plans. Through the API, model prices run from $0.10/$0.50 per million tokens for Claude Haiku 5.5 to $10/$50 for GPT-6 Astra.

Do AI coding tools make developers faster?

The evidence is mixed. METR’s randomised trial found experienced developers took 19% longer with AI tools on code they knew well, using tools older than the current agents. In JetBrains’ survey, 90% of professional developers used an AI coding agent at work at least weekly.

Can AI replace developers yet?

No. Agents now finish a large share of well-specified tasks, but only 44% of merged agent pull requests in Amplifying’s sample had a human reviewer, and developers in the Stack Overflow survey trust AI output mainly when they can validate it. The work is shifting from writing each line to specifying, reviewing and directing agents.

The future: what’s coming

Autonomy is becoming the default. Devin, Antigravity and Kiro all run for long stretches on a specification, and Claude Code and Codex both run cloud sessions that return finished branches.

Model access is now strategic. OpenAI’s models leave Cursor on 12 November 2026 after SpaceX bought its maker. Multi-model tools and open protocols are the hedge.

The open tier keeps closing the gap. MIT-licensed DeepSeek V4.1-Flash and GLM-5.3, the successor to GLM-5.2, make self-hosted coding workable for routine tasks.

The harness matters as much as the model. The gap between vendor and standardised SWE-bench Pro scores comes from retrieval, context and tool design, not the model name in the dropdown.

Conclusion: how to choose

• Best overall: Claude Code with Claude Opus 5.5.
• Best for delegated pull requests: OpenAI Codex.
• Best for GitHub teams and the widest editor support: GitHub Copilot.
• Best AI-first editor: Cursor.
• Best for unattended tickets: Devin.
• Best open-source setup: Cline with DeepSeek V4.1-Flash.
• Best model: Claude Opus 5.5; best value: GPT-6.1 Sol.

Pick the tool that fits where your code and your review already live, pick the model by the cost of a finished task rather than the token price, and keep a person reading anything that touches data, infrastructure or security.