Sourcegraph Cody vs GitHub Copilot: Enterprise AI Coding 2026

Note: Sourcegraph discontinued Cody Free and Cody Pro on July 23, 2025. This is now a pure enterprise comparison — Copilot Business/Enterprise ($19–$39/seat) versus Cody Enterprise (~$59/seat). Individual developers are not Cody’s target anymore; Sourcegraph’s new product for solo devs is Amp.

If your team runs across multiple repositories, Cody Enterprise is the stronger tool. If you’re already deep in the GitHub ecosystem or your headcount is under ~30, Copilot Business wins on economics and integration breadth.

Who this is for

Engineering teams evaluating AI coding tools at the team or org level. If you’re a solo developer looking for an individual tier, Cody no longer has one — your options are Copilot (Free through Pro+) or a separate category of tools like Cursor, Amp, or Continue.

What changed (and why this comparison matters in 2026)

Two years ago this was a tight individual-developer matchup. Then Sourcegraph killed Cody Free and Cody Pro. As of July 23, 2025, anyone on a free or pro plan lost access, and Cody is now enterprise-only.

That repositions the comparison entirely. You’re no longer comparing $10/month tools. You’re comparing Copilot Business at $19/seat against Cody Enterprise at roughly $59/seat — more than 3× the per-seat cost. The reason to pay that premium is context.

Context quality: where Cody earns the price gap

Cody uses search-first retrieval. When you ask it a question, it searches across your indexed codebase using Sourcegraph’s engine — semantic and exact match — and retrieves relevant code from multiple repositories simultaneously before generating a response. It shows you which files it used.

Copilot uses a suggestion-first model. Context is the current file, your open tabs, and recently viewed files. Copilot Enterprise adds org-wide knowledge bases for GitHub-hosted repos, but the scope is still a single organization’s GitHub.com repos, not a cross-host picture of your full codebase.

That difference matters in three specific situations:

Onboarding to a large codebase. Ask Cody “how does authentication work in this app?” on a 500K-line TypeScript monorepo and it returns a cited answer from the actual auth middleware, JWT handlers, and session management files — pointing at the code it used. Ask Copilot the same question without having those files open and you get a generic answer or nothing useful.

Cross-service debugging. A bug tracing from an API gateway through a shared auth library to a database service — across 3 separate Git repos, potentially on different hosts. Cody handles this natively; you connect all three repos to your Sourcegraph instance and ask the question once. Copilot can’t cross repositories. You switch repos, re-explain context, repeat.

Org-specific conventions. When a codebase has enough indexed material, Cody learns internal patterns and replicates them accurately. Copilot’s training on billions of public repos means it knows standard patterns very well, but it has no mechanism to infer your team’s non-standard choices from across the codebase.

Sourcegraph’s own test (bias noted: they ran it, not a neutral party) showed Cody scoring 9.5/10 versus Copilot’s 5/10 on a production PHP application — correct environment setup, correct inline property suggestions, correct AWS API calls versus several plausible-but-wrong hallucinations from Copilot. The specific failure modes they documented (Copilot suggesting npm start on a project with no such script; suggesting a nonexistent ->fps property) are consistent with what you’d expect from a tool that can’t see the repo. Take the score with a grain of salt; the failure taxonomy is plausible.

Where Copilot holds its own on context: common patterns in popular languages. On well-trodden TypeScript, Go, or Python, Copilot’s training breadth compensates for lack of local search. HN developer commentary from 2024 (pre-pivot, weight accordingly) consistently noted Copilot as marginally better for TypeScript import suggestions and multiline completions on standard patterns. For niche languages with sparse local examples — Zig, Erlang, esoteric DSLs — Copilot’s training data depth wins over Cody’s RAG on thin context.

Model flexibility

Cody Enterprise supports bring-your-own-key (BYOK). You can route inference through Anthropic directly, Amazon Bedrock, Microsoft Azure OpenAI, Google Gemini/Vertex, OpenAI, Fireworks AI, Hugging Face TGI, or any OpenAI-compatible endpoint. Admins control which models users can access and can hot-swap between them.

Copilot has no BYOK support. GitHub decides which models are available at each tier. Claude Opus 4.7 and 4.8 are available from Pro+ upward (Pro+, Max, Business, and Enterprise); Claude Opus 4.5 and 4.6 are restricted to Business and Enterprise. Claude Sonnet and Gemini models are available from Copilot Pro ($10/month) upward. You can’t route to your own Bedrock endpoint or a privately deployed model regardless of tier.

For most teams, the model catalog difference is negligible. For regulated industries that need to keep inference inside a private cloud deployment, Cody’s BYOK is often a hard requirement, not a preference.

Enterprise controls

Both tools offer zero data retention for Business/Enterprise tiers — inputs and outputs are not stored beyond generation time. Neither vendor trains on customer code. These are table-stakes in 2026; anyone citing them as a differentiator is working from a stale checklist.

Where the two diverge:

Data residency. Copilot launched dedicated data residency regions in April 2026 — US and EU live now, with Australia and Japan on the roadmap for later in 2026. Inference stays in the designated region. Cody Enterprise offers single-tenant cloud deployment, which provides isolation but not the same regional specificity.

FedRAMP compliance. As of April 2026, Copilot’s underlying infrastructure is FedRAMP Moderate authorized; Copilot itself is pending full authorization. Cody is SOC 2 Type II, GDPR, CCPA — solid commercial compliance, but FedRAMP is a different certification track. US government contractors and DoD work: track Copilot’s authorization status before treating it as the compliant option.

Context filtering. Cody’s Context Filters let admins define declarative rules blocking specific repository paths from ever being sent to an LLM. You want /src/payments/ never touching an external model endpoint? That’s a config rule. Copilot Enterprise has file-level content exclusions, but the controls are less explicit and don’t apply uniformly across all agent-mode scenarios.

Audit logs. Copilot Business/Enterprise keeps audit logs covering seat assignments, policy changes, and feature enablement — exportable to JSON/CSV and streamable to SIEM. Cody Enterprise has audit logging capability; the retention depth and SIEM integration options depend on your Sourcegraph instance configuration.

GitHub ecosystem integration

Copilot is a GitHub product. That means native integration with GitHub Actions, GitHub.com-hosted repos, pull request workflows, Copilot Spaces for curated context bundles, and the tooling built on top of GitHub’s APIs. If your CI/CD runs in GitHub Actions and your code review process lives in GitHub pull requests, Copilot meets you where you already work.

Cody integrates with GitHub-hosted repos but is not a GitHub product. It’s built around Sourcegraph’s own code intelligence platform. The integration story with GitHub is solid for indexing and context; it’s not as tight for workflow automation that touches GitHub-native features.

Pricing

Plan	Price
Copilot Free	$0/user/month
Copilot Business	$19/seat/month
Copilot Enterprise	$39/seat/month
Cody Enterprise	~$59/user/month (contact sales; $16K+ platform starting price)

Cody’s $59/user/month figure comes from multiple independent reviews; Sourcegraph’s own pricing page does not publish a per-seat rate and requires a sales conversation for exact numbers. Budget-model as “contact sales around $59” and verify before committing.

The price gap is $40/seat/month at Business vs Cody Enterprise. At 20 developers, that’s $9,600/year. At 100 developers, $48,000/year. The context and BYOK advantages need to be worth that number to your team.

Adoption data

Stack Overflow’s 2025 Developer Survey shows GitHub Copilot at 67.9% adoption among developers who use AI tools — second only to ChatGPT at 81.7%. Cody does not appear in the survey’s listed tools, reflecting its enterprise-niche positioning rather than low quality.

84% of developers now use or plan to use AI coding tools. 51% of professional developers use them daily (47.1% across all survey respondents). The tooling category has commoditized enough that adoption rate alone tells you nothing about fit — the question is which capabilities match your specific workflow.

Verdict

	Copilot	Cody Enterprise
Multi-repo context	No	Yes (multiple repos)
Cross-host repos (GitHub + GitLab + Bitbucket)	No	Yes
BYOK / private inference	No	Yes
Individual dev access	Yes (Free–Pro+)	No
GitHub ecosystem native	Yes	Partial
FedRAMP	Infrastructure authorized; app authorization pending (April 2026)	No
SOC 2 Type II	Yes	Yes
Data residency (US/EU live; AU/JP planned 2026)	Yes	Single-tenant option
Price (team tier)	$19–$39/seat	~$59/seat
Training breadth on common patterns	High	Depends on indexed codebase

Pick Copilot Business if:

Your codebase is on GitHub and you work with standard frameworks
Teams under ~30 seats where the price gap adds up fast
You need FedRAMP or data residency by region
Individual developers on your team need their own access
Your workflow is tightly coupled to GitHub Actions and pull requests

Pick Cody Enterprise if:

Your codebase spans multiple repositories, including cross-host (GitHub + GitLab, or GitHub + Bitbucket)
Context across 300K+ repositories matters — large-scale Sourcegraph installations are a documented use case
You need BYOK to route inference through a private Bedrock or Azure endpoint
Declarative context filtering (blocking /src/payments/ from any LLM) is a compliance requirement
Your team is already on Sourcegraph for code search

Caveats

No independent third-party benchmark comparing Cody Enterprise against Copilot Enterprise was found. The 9.5 vs 5/10 test result is Sourcegraph’s own work — they wrote the test, ran it on a codebase they chose, and published the result. The failure modes are plausible, but the score is not a neutral number.

The HN developer sentiment cited here is from 2024, before Cody went enterprise-only. Developers who were Cody advocates as individuals may have moved to Cursor, Continue, or Amp. Community sentiment around Cody has likely shifted.

Copilot Pro new signups were temporarily paused at research time (June 2026). Status may have changed. The Free and Business tiers were unaffected.

Cody previously supported Ollama for local/offline inference. After the enterprise-only pivot, local model support status under the enterprise product is unclear — verify with Sourcegraph before including it in your evaluation criteria.