Updated October 14, 2026. Research-only comparison: AsumeTech did not install, benchmark, or conduct hands-on tests of these eight subscriptions. Prices, quotas and availability are vendor-published snapshots and can change; tax and local payment methods vary.
The best AI coding assistant is not necessarily the chatbot that writes the prettiest Python snippet. A useful developer tool has to understand an existing repository, change multiple files safely, work with your editor and tests, and leave an auditable diff. This guide compares eight currently released IDE assistants, terminal agents and delegated coding platforms. It is a focused companion to our broader AI chatbots comparison, not a duplicate general-chatbot ranking.
Quick picks: the best AI coding assistants for different developers
| Rank / product | Editorial score /10 | Entry price, US list | Most suitable workflow |
|---|---|---|---|
| 1. GitHub Copilot Pro | 9.1 | US$10/month; 1,000 GitHub AI Credits included on the current usage-based plan | Best broadly compatible coding companion for teams already using GitHub |
| 2. Cursor Pro | 9.0 | US$20/month individual Pro; model-dependent included usage and optional on-demand overages | Best AI-first editor for interactive multi-file changes |
| 3. Claude Code with Claude Pro | 8.9 | Claude Pro US$20/month or US$200/year; shared five-hour-session and weekly limits | Best terminal-first assistant for careful refactors and repository reasoning |
| 4. OpenAI Codex via ChatGPT Plus | 8.8 | ChatGPT Plus US$20/month; Codex included with variable plan usage limits, API billed separately | Best for delegating coding tasks across CLI, IDE, desktop and cloud |
| 5. Devin Desktop Pro (formerly Windsurf pricing path) | 8.4 | US$20/month Pro; daily/weekly refreshed usage allowances, optional extra API-priced usage | Best for an editor-plus-cloud-agent workflow under Cognition |
| 6. JetBrains AI Pro (individual) | 8.3 | US$10/month individual AI Pro with 10 AI Credits per 30 days; organization pricing and quotas differ | Best for IntelliJ, PyCharm and other JetBrains IDE loyalists |
| 7. Gemini Code Assist Standard | 8.1 | US$22.80/user/month on monthly commitment or US$19/user/month with 12-month commitment | Best for organizations building in Google Cloud and supported IDEs |
| 8. Amazon Q Developer Pro | 7.9 | US$19 per user per month; paid agentic quotas and 4,000 Java transformation lines per seat/month pooled by account | Best for AWS-centered development, modernization and governance |
Start here: choose GitHub Copilot for wide IDE and GitHub integration; Cursor for an AI-first editor; Claude Code for command-line collaboration; Codex for multi-surface delegated work; Devin Desktop for a desktop/cloud hybrid; JetBrains AI for an existing JetBrains workflow; Gemini Code Assist for Google Cloud teams; and Amazon Q Developer for AWS-heavy projects. A high score does not mean an agent is safe to merge unreviewed code.
How we ranked these tools without pretending to test them
Our editorial rubric weights workflow and IDE integration (25%), repository context and agent usefulness (25%), cost/quota transparency (20%), security and team governance (15%), and independent evidence, support and portability (15%). Each category is assessed from official feature and pricing documentation, publicly described product limitations, and independent professional or research coverage. We assign a reasoned 0–10 editorial score; these are not hands-on benchmark scores, speed measurements, bug counts, or standardized pass rates. The weights are an editorial decision, not statistical estimates.
For external context, a February 2026 academic analysis of 7,156 AI-agent pull requests found substantial variation by task type and acceptance, including differences between documentation, fixes and new features. It examines historical PR outcomes, not today’s identical-model head-to-head tests, and cannot prove a specific paid plan will pass your own tests. A September 2026 educator comparison discusses workflow distinctions among Cursor, Copilot, Claude Code and other tools; its findings are useful context rather than a substitute for a controlled local trial.
Eight best AI coding assistants in 2026
1. GitHub Copilot Pro — Best broadly compatible coding companion for teams already using GitHub
Research-only editorial score: 9.1/10. Verified plan and price: US$10/month; 1,000 GitHub AI Credits included on the current usage-based plan. Official sources: plan/documentation and additional vendor reference.
What you actually buy: Copilot Pro is an individual subscription to IDE suggestions, chat and supported coding-agent workflows, not a license to every third-party model without metering. GitHub’s June 2026 transition replaced the old premium-request multiplier scheme for new billing with GitHub AI Credits. The current Pro allowance is 1,000 credits, and model/token choice determines consumption. Do not quote the old 300-premium-request figure as the 2026 allowance. Pro+ and organization seats are separate products with different budgets and controls.
Workflow and IDE fit: Copilot is particularly attractive when your day already involves VS Code, JetBrains or other supported editors and GitHub pull requests. Inline completions keep small edits close to the cursor; agent and issue-to-PR features are more relevant for changes that cross files. Availability of third-party agents, advanced models and code-review features varies by subscription and rollout. A repository’s tests, permissions and branch protections still decide whether the resulting patch is acceptable.
Cost and governance: Personal Pro is not interchangeable with Business at US$19 per granted seat monthly or Enterprise at US$39. Organizations should compare code-use policies, audit needs and identity management before granting seats. Select the model and monthly budget deliberately: a long repository task can consume more credits than a quick completion. The precise AI Credit burn rate is model and token dependent, not a fixed count of edits.
Evidence and drawback: The comparative 2026 pull-request study below includes Copilot but does not prove it will win on your repository. Copilot is the most natural choice when editor breadth and GitHub workflow matter more than a single agent’s maximum autonomy. It is less transparent to budget if developers assume all agent interactions cost the same.
Who should choose it: Best broadly compatible coding companion for teams already using GitHub. Who should compare alternatives: teams that need a different editor, model policy, deployment boundary, or billing model should trial another shortlisted product against the same representative repository and tests.
2. Cursor Pro — Best AI-first editor for interactive multi-file changes
Research-only editorial score: 9.0/10. Verified plan and price: US$20/month individual Pro; model-dependent included usage and optional on-demand overages. Official sources: plan/documentation and additional vendor reference.
What you actually buy: Cursor Pro is an AI-centric desktop code editor, rather than an extension that adds one chat panel to an existing JetBrains installation. Its pricing documentation lists Pro at US$20/month, Pro+ at US$60 and Ultra at US$200. Included usage is a pool, not an unlimited entitlement to the most expensive frontier model; usage depends on model and tokens. After the included allowance, Cursor offers pay-as-you-go use or a plan upgrade, so set spending alerts before allowing long unattended agent runs.
Editing experience: Cursor’s agent and Composer workflows make repository search, file changes and iteration feel like one integrated editor. It can be strong for a developer who reviews diffs continually and wants to switch among supported frontier models. It is not the same as saying Cursor runs natively inside every IDE: a JetBrains-only shop should account for the cost of changing editor. Its cloud agents and Bugbot code review have plan, usage or separate-billing considerations.
Context and privacy: Codebase indexing and remote model calls deserve a specific security review. For confidential repositories, check privacy-mode enforcement, retention and the vendor’s current policy for the chosen plan rather than assuming local editor files never leave the machine. Team plans add central administration, SSO and team-wide privacy controls, but Pro does not automatically inherit every enterprise safeguard.
Independent perspective: A September 2026 educator comparison characterized Cursor as the AI-first-editor choice, while a February study of real agent-created PRs found task-type differences between agents. Neither supplies an audited universal success rate for Cursor Pro on a new codebase. Its best fit is the developer who spends most of the day in one AI-oriented editor and can supervise iterative changes.
Who should choose it: Best AI-first editor for interactive multi-file changes. Who should compare alternatives: teams that need a different editor, model policy, deployment boundary, or billing model should trial another shortlisted product against the same representative repository and tests.
3. Claude Code with Claude Pro — Best terminal-first assistant for careful refactors and repository reasoning
Research-only editorial score: 8.9/10. Verified plan and price: Claude Pro US$20/month or US$200/year; shared five-hour-session and weekly limits. Official sources: plan/documentation and additional vendor reference.
Plan identity: Claude Code is a coding agent available through eligible Claude subscriptions and API billing. The consumer Claude Pro subscription is US$20 monthly or US$200 annually. This does not purchase unlimited token output. Claude and Claude Code share a five-hour session allowance and a weekly cap, and users can purchase additional usage credits or move to Max when their workload outgrows Pro. A shell configured with an ANTHROPIC_API_KEY may charge the API account instead of drawing from the subscription, an important operational trap.
Developer workflow: Claude Code works in a terminal and supported IDE integrations including VS Code and JetBrains, with the terminal also usable inside other editors. It can inspect files, propose coordinated changes, run approved commands and iterate against tests. It suits engineers comfortable with shell tools, git and explicit permissions. Repository-scale context does not remove the need to specify scope, inspect generated patches and run security checks.
Privacy and model routing: The Claude Code model family is Anthropic’s, not an open marketplace for arbitrary third-party model providers. Consumer Claude Pro/Max sessions have distinct data-control and retention rules from commercial API or enterprise deployments. Anthropic says consumer data may be used for improvement when the user elects to allow it. A zero-data-retention API agreement is not automatically a zero-retention guarantee for a consumer Pro account.
Evidence and caution: The February 2026 pull-request analysis found Claude Code particularly strong in some task categories, but its data do not guarantee performance on any one repository. Anthropic also documented and corrected April 2026 quality regressions, illustrating why pinning workflows and rerunning tests matter. Choose Claude Code for disciplined command-line collaboration, not a promise of flawless autonomous code.
Who should choose it: Best terminal-first assistant for careful refactors and repository reasoning. Who should compare alternatives: teams that need a different editor, model policy, deployment boundary, or billing model should trial another shortlisted product against the same representative repository and tests.
4. OpenAI Codex via ChatGPT Plus — Best for delegating coding tasks across CLI, IDE, desktop and cloud
Research-only editorial score: 8.8/10. Verified plan and price: ChatGPT Plus US$20/month; Codex included with variable plan usage limits, API billed separately. Official sources: plan/documentation and additional vendor reference.
Plan identity: Codex is a coding agent, not merely the general-purpose ChatGPT chat window. As of this October 2026 review, Codex is available through eligible ChatGPT plans, including Plus at US$20/month; plan-specific rate limits apply. Codex Cloud is subject to eligibility and workspace rollout, while API usage remains a separate meter. The product offers a CLI, an IDE extension, desktop workflows and web/cloud tasks. Do not assume the Plus subscription buys unlimited parallel cloud workers or OpenAI API credits.
How it fits a repository: Codex can be assigned a bounded change, read relevant files, propose multi-file edits and execute permitted tests. The CLI works in a developer’s terminal, while the VS Code-family extension and desktop surfaces support closer editor integration. Cloud execution can make asynchronous issue-to-patch workflows attractive, but environment setup, repository access and the time needed to review a returned diff are real costs. In non-VS Code IDEs, a terminal workflow is safer to promise than a native plugin.
Models, safety and privacy: Available Codex models and quotas can change by plan; verify the selector at run time rather than promising one permanent model ID. Review sandbox permissions, secret exposure, connected repositories and branch protections. Consumer data controls differ from Business/Enterprise policies; the exact retention and training position depends on the account and workspace. The separate API key path can produce a second bill if a user confuses subscription login with API authentication.
Independent evidence: The peer-reviewed/preprint comparative PR study included Codex and reported relatively strong acceptance across task categories, but acceptance is not a controlled benchmark of current 2026 models and does not measure security. Codex is especially compelling when a developer values multiple surfaces and asynchronous work, provided every patch gets human review.
Who should choose it: Best for delegating coding tasks across CLI, IDE, desktop and cloud. Who should compare alternatives: teams that need a different editor, model policy, deployment boundary, or billing model should trial another shortlisted product against the same representative repository and tests.
5. Devin Desktop Pro (formerly Windsurf pricing path) — Best for an editor-plus-cloud-agent workflow under Cognition
Research-only editorial score: 8.4/10. Verified plan and price: US$20/month Pro; daily/weekly refreshed usage allowances, optional extra API-priced usage. Official sources: plan/documentation and additional vendor reference.
2026 naming check: The former Windsurf pricing URL now redirects to Devin’s official pricing page. For October 14, 2026, this comparison therefore evaluates the released Devin Desktop Pro offering, not a stale US$15 Windsurf plan copied from older reviews. Devin lists Free, Pro at US$20 and Max at US$200 for individuals. Pro includes unlimited Tab completions and inline edits, access to additional frontier models and cloud agents; its paid agent allowance refreshes daily and weekly. Extra usage can be purchased at API pricing. Exact request counts are not promised publicly because task complexity and selected model affect cost.
What the agent does: Devin Desktop combines fast in-editor assistance with the option to delegate larger work to cloud agents. The current official plan describes models from multiple providers and integration with GitHub, GitLab and Bitbucket. The interface and branding have changed during 2026, so buyers should verify the installed app and available editor/CLI integrations rather than assuming every feature of the older Windsurf Cascade interface survives unchanged.
Privacy and team economics: Cloud sessions need explicit repository permissions and security review. The official Teams plan is not simply US$40 per user: it includes an US$80/month team base fee plus US$40/month per full developer seat. Enterprise offers more advanced controls. For sensitive code, confirm the current data-use policy, region, identity management and third-party model routing. Do not use consumer Pro as a proxy for enterprise retention guarantees.
Evidence and tradeoff: Independent 2026 reviews of Windsurf are useful historical context, but their screenshots and quotas may be obsolete after the product transition. The current Devin pricing page is authoritative for today’s purchase. This option rewards developers who want to move between direct editing and delegated cloud tasks; it is less straightforward for anyone seeking a stable, vendor-neutral plugin for an existing IDE.
Who should choose it: Best for an editor-plus-cloud-agent workflow under Cognition. Who should compare alternatives: teams that need a different editor, model policy, deployment boundary, or billing model should trial another shortlisted product against the same representative repository and tests.
6. JetBrains AI Pro (individual) — Best for IntelliJ, PyCharm and other JetBrains IDE loyalists
Research-only editorial score: 8.3/10. Verified plan and price: US$10/month individual AI Pro with 10 AI Credits per 30 days; organization pricing and quotas differ. Official sources: plan/documentation and additional vendor reference.
Exact edition: JetBrains AI Pro is a license tier for AI in supported JetBrains IDEs. The vendor’s 2026 documentation distinguishes an individual US$10 tier with 10 AI Credits per 30 days from an organization US$20 tier with 20 credits; some regional or annual purchase pages display localized pricing. AI Ultimate and AI Enterprise are separate. Credits are consumed by cloud-backed features, and top-up credits have their own validity. It is misleading to promise 10,000 free requests or an unlimited agent from the US$10 license.
Workflow: The value lies in IDE-native context: code completion, project navigation, code explanation and supported agent workflows within tools developers already use for refactoring, inspections and tests. For a Kotlin, Java or Python team committed to JetBrains, that can be more important than moving to a standalone VS Code fork. The exact AI feature set depends on IDE version, plugin, license and supported model/agent; do not assume every third-party agent runs in every JetBrains product.
Models, local options and governance: JetBrains supports a mixture of cloud and configurable AI workflows; model choice and bring-your-own-model support vary by feature. Local or BYO model modes are not automatically equivalent to cloud AI Pro functionality. Enterprise admins should inspect pooled credit arrangements and JetBrains Central controls, because organizational credit accounting differs from a single user’s 30-day quota. Check project confidentiality, telemetry and data handling for the specific agent being invoked.
Testing evidence: JetBrains’ own IDE inspections and debugger are useful independent verification tools after an AI change, but the presence of those features is not evidence that the AI itself passed a benchmark. A cautious buyer should compare how often the assistant’s suggestions compile and survive unit tests on their own project. AI Pro is strongest for developers who want incremental AI assistance without changing their primary IDE.
Who should choose it: Best for IntelliJ, PyCharm and other JetBrains IDE loyalists. Who should compare alternatives: teams that need a different editor, model policy, deployment boundary, or billing model should trial another shortlisted product against the same representative repository and tests.
7. Gemini Code Assist Standard — Best for organizations building in Google Cloud and supported IDEs
Research-only editorial score: 8.1/10. Verified plan and price: US$22.80/user/month on monthly commitment or US$19/user/month with 12-month commitment. Official sources: plan/documentation and additional vendor reference.
Exact edition and price: Gemini Code Assist Standard is Google’s paid developer-seat offering, distinct from the consumer Gemini chat app. Google Cloud publishes hourly seat rates that correspond to about US$22.80 per month with a monthly commitment or US$19 per month on a 12-month commitment (using a 730-hour billing month). Standard is not Enterprise: private-repository code customization and additional Cloud Assist capabilities are reserved for higher tiers. October 2026 reports indicate the older free individual IDE entitlement ended in June, so do not treat a personal Google AI Pro subscription as a Standard seat.
Workflow and context: The Standard tier includes code completion, chat, code transformations, local codebase awareness, agent mode and Gemini CLI for supported IDEs such as VS Code and IntelliJ. It is especially useful when code tasks overlap Google Cloud, Firebase, SQL or BigQuery. The official pricing page lists Gemini models and services at the product-family level; model assignment may change without a separate SKU change. Avoid asserting that every developer has a permanently fixed model or unlimited context.
Usage and security: Google documents a per-seat entitlement rather than a pay-per-edit retail purchase. Independent October 2026 summaries report around 1,500 agent/CLI requests daily on Standard, subject to Google’s current quota policy. Enterprise-grade security and indemnification are described on the official plan, but buyers should still verify account region, billing entity, workspace access and code handling. Cloud service charges are separate from Code Assist license fees.
Where it falls short: A solo developer outside Google Cloud may find onboarding and seat procurement less direct than GitHub Copilot or a consumer editor. Standard’s appeal is the combined IDE and cloud workflow, not a claim that its model beats all competitors. Confirm your chosen IDE and region before budgeting a team rollout.
Who should choose it: Best for organizations building in Google Cloud and supported IDEs. Who should compare alternatives: teams that need a different editor, model policy, deployment boundary, or billing model should trial another shortlisted product against the same representative repository and tests.
8. Amazon Q Developer Pro — Best for AWS-centered development, modernization and governance
Research-only editorial score: 7.9/10. Verified plan and price: US$19 per user per month; paid agentic quotas and 4,000 Java transformation lines per seat/month pooled by account. Official sources: plan/documentation and additional vendor reference.
Exact product: Amazon Q Developer Pro is a US$19/user/month developer subscription, not Amazon Q Business or the consumer shopping assistant. The free tier has 50 agentic requests monthly; Pro increases limits but AWS does not present that as an unlimited blanket guarantee. The Pro subscription also allocates 4,000 Java-upgrade transformation lines per user per month, pooled at the payer-account level, with US$0.003 per additional submitted line where applicable. Billing can activate when a subscribed user actually invokes qualifying coding features, so admins should monitor seat assignment and usage.
IDE and cloud fit: Q Developer supports IDE plugins and CLI workflows and is closely integrated with AWS troubleshooting, code generation and modernization. The service can use supported Claude models, but exact versions and region availability change. Its reference tracking and suppression of public-code suggestions are relevant to teams with licensing controls. It can work on code outside AWS, although the highest value is generally for a team already invested in AWS services and Identity Center.
Security and organization: AWS says Pro is automatically opted out of data collection and includes identity administration and IP indemnification. These statements are product-specific; they do not mean a developer can grant the agent production credentials without risk. Keep least-privilege IAM roles, require review of generated infrastructure changes and avoid exposing secrets in prompts. Check which Identity Center regions support your subscriptions before committing to a rollout.
Evidence and limits: AWS documents quota and security terms clearly, but the available independent 2026 comparisons are not controlled tests of the exact Pro seat on a fixed AWS repository. Treat its editorial score as a fit assessment, not a measured code-quality result. For developers outside AWS, Copilot or a general IDE agent may offer a smoother starting point.
Who should choose it: Best for AWS-centered development, modernization and governance. Who should compare alternatives: teams that need a different editor, model policy, deployment boundary, or billing model should trial another shortlisted product against the same representative repository and tests.
IDE support, CLI access and model routing: what to verify before subscribing
VS Code users: GitHub Copilot, Claude Code, Codex and Gemini Code Assist have documented VS Code-compatible workflows; Cursor and Devin Desktop are editor products rather than universal drop-in extensions. JetBrains users: Copilot, Claude Code, JetBrains AI and Gemini Code Assist are the more direct starting points, with exact IDE/version support to be checked. Neovim and terminal users: do not equate terminal access with a native Neovim plugin. CLI tools can run alongside Neovim; verify any native plugin and authentication method separately. Cloud agents: repo connection, runner permissions, branch rules and review gates matter as much as the model.
Model selection changes faster than product branding. Copilot, Cursor and Devin expose varying multi-provider options, while Claude Code is Anthropic-centered, Codex uses supported OpenAI coding models, and cloud-specific assistants route through their supported provider stacks. A tool may use a newer model tomorrow without changing its subscription name. Record the actual model, settings, usage tier and date whenever you compare outputs.
What the price really buys in October 2026
A US$20 seat does not buy a uniform number of solved issues. Copilot meters GitHub AI Credits; Cursor meters model-dependent included usage; Claude Code has shared session and weekly limits; Codex has plan-specific quotas; Devin’s allowance refreshes daily and weekly; JetBrains uses AI Credits; Gemini sells per-seat Standard subscriptions; and Amazon Q has product-specific agent and modernization limits. Overage behavior also differs. Before assigning a team budget, run one typical task through each shortlisted plan, note the actual credits or quota consumed, and multiply by realistic weekly frequency. Include review time and CI minutes rather than treating AI output as production-ready code.
In particular, GitHub’s June 2026 shift from legacy premium requests to AI Credits means older pricing comparisons are stale. Likewise, the Windsurf pricing address now points to Devin’s current plans, and Google’s consumer Gemini Code Assist access changed during 2026. Historical discounts, legacy subscriptions and geographic offers are not interchangeable with the current products listed above.
Privacy, training and retention checklist for confidential repositories
Before sending proprietary code to any coding agent, identify the account tier, model provider, data sent off-device, training opt-in/out, retention policy, cloud execution region, and permission to run commands or open PRs. Consumer, team and enterprise terms can differ within the same brand. For example, Anthropic distinguishes consumer Claude Code data choices from commercial/API agreements; AWS documents Pro data-collection opt-out and reference controls; GitHub and Cursor have team-level administration; and Google differentiates Standard and Enterprise capabilities. A marketing statement about privacy mode is not proof that every connected third-party model has identical terms.
For codebases with secrets, regulated data or customer information, use synthetic fixtures in a trial; deny production credentials; require branch protection, code-owner review, dependency scans and test execution. An agent’s successful test run is not evidence that it has found all vulnerabilities. For teams managing repository changes, our earlier Claude Code workflow explainer provides additional historical context, but this buyer’s guide uses current plan details.
A practical evaluation protocol that avoids invented benchmarks
- Choose three real but non-sensitive repository tasks: one small bug, one cross-file refactor and one test/documentation improvement.
- Keep the repository commit, instructions, allowed tools, tests and time budget identical across products.
- Record the exact model/plan, prompts, permissions, token or credit consumption, manual interventions, test outcomes and final diff.
- Have a developer review correctness, security, maintainability and whether the change meets the acceptance criteria.
- Compare total developer time and cost, not just whether an agent produced code. Repeat trials because models and tool versions change.
These steps are a recommended method for readers; AsumeTech has not claimed to run this experiment. Public benchmark scores such as SWE-bench, Terminal-Bench or pull-request acceptance studies should be quoted only with the model version, harness, date, dataset and evaluator. Vendor demos are not neutral evidence of production reliability.
Frequently asked questions
Which AI coding assistant is best for a beginner?
Copilot’s familiar IDE workflow can be easier to adopt than an autonomous terminal agent. Cursor is attractive for someone willing to switch editors. Start with completion and explanation tasks, then grant file-edit and command-execution privileges only after learning to inspect diffs.
Are AI coding agents safe to use on private repositories?
They can be used under appropriate account terms and controls, but no agent is automatically safe. Review data processing, secrets, execution privileges, branch protection, generated dependencies and license issues. Never assume a consumer subscription has enterprise retention guarantees.
Can these assistants run fully offline?
Not by default. Many headline features depend on hosted inference or cloud runners. Some ecosystems support local/BYO models for selected workflows, but feature parity, hardware needs and policy must be verified separately. A terminal interface alone does not imply offline operation.
Which is cheaper for heavy daily use?
There is no universal winner. Model mix, context size, rate limits, retries and overage policy dominate the effective cost. A nominal US$10 or US$20 plan may be economical for completions yet insufficient for repeated long agent tasks. Track actual consumption during a trial.
Should developers trust AI-generated code without reviewing it?
No. Treat AI output as an untrusted patch until a human has inspected the diff and relevant tests, security checks and licensing constraints have passed. Even independently reported PR acceptance is not a substitute for your organization’s standards.
Sources, disclosure and update policy
Vendor links inside each of the eight sections are primary sources for prices, quotas and product claims. Independent context includes Pinna et al., 2026, comparative PR acceptance analysis, Scrimba’s September 2026 comparison and No Code MBA’s 2026 editor review (historical Windsurf context only). No referral links or affiliate placements are required for this ranking. Editorial scores are research judgments, not laboratory measurements. We will revisit vendor names, billing changes and model routing when official documentation changes.