Machine Learning · head to head
MLflow vs Sourcegraph Cody
MLflow
Machine Learning
Open source platform for managing the ML lifecycle
- From
- Free
- Free plan
- Yes
Sourcegraph Cody
AI
Enterprise AI coding assistant with whole-codebase context
- From
- $59/month
- Free plan
- No
The short version
- Only MLflow has a free tier, so it costs nothing to try first.
- Each has a real cost: MLflow requires infrastructure setup: teams must manage MLflow tracking server, database, and artifact storage themselves; Sourcegraph Cody no longer available to individual developers or small teams after free and Pro tiers were discontinued in mid-2025
- They diverge on capability: MLflow covers Experiment tracking, Sourcegraph Cody covers Multi-repository context.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which MLflow and Sourcegraph Cody actually diverge.
| Attribute | MLflow | Sourcegraph Cody |
|---|---|---|
| Starting price | Free | $59/month |
| Pricing model | open-source | quote |
| Free tier | Yes | No |
| Platforms | Web, Python API, REST API | web, windows, mac, linux |
| Category | Machine Learning | AI |
| Founded | 2018 | 2013 |
Identical on both: user rating (Not yet rated).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in MLflow
- Experiment tracking
- Model registry
- Model packaging
- Deployment
- Project organization
- TensorFlow
- PyTorch
- scikit-learn
Only in Sourcegraph Cody
- Multi-repository context
- Large context window
- Context filters
- Model flexibility
- IDE integration
What people use each for
The jobs each tool is most often brought in to do.
MLflow
- Machine learningnot Sourcegraph Cody
- Data analysisnot Sourcegraph Cody
- Model trainingnot Sourcegraph Cody
- Predictive analyticsnot Sourcegraph Cody
Sourcegraph Cody
- Cross-repository code understanding for large engineering orgsnot MLflow
- AI-assisted code review and refactoring at enterprise scalenot MLflow
- Enforcing data-boundary controls when using third-party LLMsnot MLflow
- Codebase-aware chat and autocomplete for developersnot MLflow
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
MLflow
- Requires infrastructure setup: teams must manage MLflow tracking server, database, and artifact storage themselves
- Basic UI and visualization: lacks rich interactive dashboards and real-time monitoring compared to commercial platforms
- Limited collaboration: no built-in role-based access control or multi-user management features
- Production monitoring gaps: drift detection, explainability, and alerting require separate dedicated tools
Sourcegraph Cody
- No longer available to individual developers or small teams after free and Pro tiers were discontinued in mid-2025
- Priced substantially higher than many competing AI coding assistants, with Enterprise plans typically requiring annual contracts
- Sourcegraph has shifted its individual-developer focus to a separate product, Amp, creating uncertainty about Cody's long-term product priority
- Requires integration with Sourcegraph's broader code intelligence platform rather than working as a lightweight standalone extension
Pricing, plan by plan
MLflow
Free- Open SourceFree
- Experiment tracking
- Model registry
- Deployment tools
Sourcegraph Cody
$59/month- Enterprise$59/month
- Whole-codebase AI context
- Context filters for sensitive code
- Multi-repository analysis
Which should you pick?
Choose MLflow if
- You need experiment tracking.
- You want to start without paying.
- You work on Web, Python API, REST API.
- You also want model registry.
Choose Sourcegraph Cody if
- You need multi-repository context.
- You work on web, windows, mac, linux.
- You also want large context window.
Questions people ask
- Is MLflow or Sourcegraph Cody better?
- Neither clearly leads. MLflow starts at Free and Sourcegraph Cody at $59/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, MLflow or Sourcegraph Cody?
- MLflow has a free tier; the other does not. Paid plans start at Free for MLflow and $59/month for Sourcegraph Cody.
- Does MLflow or Sourcegraph Cody run on more platforms?
- MLflow runs on Web, Python API, REST API. Sourcegraph Cody runs on web, windows, mac, linux.
- Can I use MLflow for free?
- Yes. MLflow has a free tier, so you can try it without paying. Sourcegraph Cody starts at $59/month.
- What is MLflow best used for?
- MLflow is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Sourcegraph Cody is typically brought in for.
- What can MLflow do that Sourcegraph Cody cannot?
- MLflow covers Experiment tracking, Model registry, Model packaging, Deployment. Sourcegraph Cody covers Multi-repository context, Large context window, Context filters, Model flexibility.
Answered from the vendors’ own pages
MLflow: Is MLflow free to use?
Yes, MLflow is completely open-source and free. However, teams typically incur infrastructure costs for hosting and maintaining the MLflow tracking server. Databricks offers Managed MLflow as a commercial option for cloud deployment.
SourceSourcegraph Cody: Is Sourcegraph Cody still available to individual developers?
No, as of mid-2025 Cody Free and Pro plans were discontinued; Cody is now sold only as part of Sourcegraph's Enterprise plan, which requires an annual contract.
SourceMLflow: Can MLflow track experiments for different ML frameworks?
Yes, MLflow is framework-agnostic and works with TensorFlow, PyTorch, scikit-learn, XGBoost, and any other ML framework. This flexibility is a core design principle allowing teams to use diverse tools.
SourceSourcegraph Cody: How much does Sourcegraph Enterprise cost?
Enterprise plans start around $16,000 and scale with team size and seat count, including bundled AI credits; exact pricing requires a sales quote.
SourceMLflow: Does MLflow include a model registry?
Yes, MLflow Model Registry (added in 2018) provides a central model store with versioning, stage transitions, and deployment tracking. This enables production model governance and lineage tracking.
SourceSourcegraph Cody: How does the AI credit system work on Enterprise plans?
Each plan includes a pooled allocation of AI credits shared across the organization; credits do not expire and roll over at renewal, with volume credit add-ons available.
SourceMLflow: What are MLflow's main limitations?
MLflow requires significant infrastructure setup and maintenance. The UI is basic compared to commercial tools, collaboration is limited without third-party RBAC solutions, and production monitoring requires separate tools for drift detection and alerting.
SourceSourcegraph Cody: What happens if my organization exceeds its credit allocation?
Sourcegraph's pricing page addresses overage and offers additional volume credit buckets for teams that need more than their committed allocation.
SourceMLflow: Can MLflow handle LLM and agent tracing?
MLflow added LLM and agent tracing capabilities in recent versions, though the native support is limited compared to specialized LLM observability platforms that replaced weak LLM tracing.
SourceSourcegraph Cody: Is a free trial available for Sourcegraph Enterprise?
Sourcegraph's pricing page lists free trial availability as one of its published FAQ topics for prospective Enterprise customers.
SourceRelated pages
More on Sourcegraph Cody
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