Comparison
BIG-bench vs code-review-graph
Verdict
Pick BIG-bench when license: BIG-bench is Apache-2.0, code-review-graph is MIT; pick code-review-graph when license: code-review-graph is MIT, BIG-bench is Apache-2.0.
Markdown twin · BIG-bench alternatives · code-review-graph alternatives
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Trust & integrity
| Signal | BIG-bench | code-review-graph |
|---|---|---|
| Maintenance | Archived (722d since push) As of today · github_public_v1 | Active (26d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Personal account As of today · github_public_v1 |
| Security (OSV) | 324 low (324 low) As of today · osv@v1 | No MCP manifest As of today · mcp_manifest |
Tagline
- BIG-bench
- Collaborative benchmark for language model capabilities
- code-review-graph
- Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo w
Stars
- BIG-bench
- 3.2k
- code-review-graph
- 19k
Forks
- BIG-bench
- 615
- code-review-graph
- 2.1k
Open issues
- BIG-bench
- 106
- code-review-graph
- 185
Language
- BIG-bench
- Python
- code-review-graph
- Python
Adopt for
- BIG-bench
- Decision-critical facts for BIG-bench
- code-review-graph
- -
Persona
- BIG-bench
- -
- code-review-graph
- -
Runtime
- BIG-bench
- -
- code-review-graph
- -
License
- BIG-bench
- Apache-2.0
- code-review-graph
- MIT
Last pushed
- BIG-bench
- Jul 19, 2024
- code-review-graph
- Jun 14, 2026
Categories
- BIG-bench
- Evaluation & Observability
- code-review-graph
- LLM Frameworks, Developer Tools, Evaluation & Observability
Trust and health
Maintenance
- BIG-bench
- Archived (8%)
- code-review-graph
- Active (82%)
Days since push
- BIG-bench
- 722d
- code-review-graph
- 26d
Archived on GitHub
- BIG-bench
- Yes
- code-review-graph
- No
Open issues (now)
- BIG-bench
- 106
- code-review-graph
- 185
Owner type
- BIG-bench
- Organization
- code-review-graph
- User
Security scan
- BIG-bench
- 324 low (324 low)
- code-review-graph
- No MCP manifest
Full report
- BIG-bench
- Trust report
- code-review-graph
- Trust report
Choose BIG-bench if…
- License: BIG-bench is Apache-2.0, code-review-graph is MIT.
- Requirements: Python 3.5-3.8 required.; `pytest` is necessary for running automated tests..
- Tags unique to BIG-bench: tasks creation, evaluation, seqio, language-models.
- When you need a comprehensive benchmark that evaluates language models across various tasks and includes methods for extrapolating model capabilities.
When NOT to use BIG-bench
- If you are looking for a tool that simplifies benchmarking with minimal configuration, BIG-bench requires setting up an environment and can be more complex compared to streamlined benchmark tools.
- As BIG-bench relies on collaboration across various tasks and contributions from the community, it might not be ideal if you need benchmark tasks or evaluations immediately available without potential
- If your project does not require advanced extrapolation techniques for measuring model capabilities over a wide range of benchmarks, simpler evaluation tools may suffice.
Choose code-review-graph if…
- License: code-review-graph is MIT, BIG-bench is Apache-2.0.
- Tags unique to code-review-graph: graphrag, ai-coding, incremental, llm.
- Also covers LLM Frameworks, Developer Tools.
When NOT to use code-review-graph
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
- Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (google/BIG-bench) · observed Jul 12, 2026
- GitHub forks (google/BIG-bench) · observed Jul 12, 2026
- Last push (google/BIG-bench) · observed Jul 19, 2024
- License file (Apache-2.0) · observed Jul 12, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (tirth8205/code-review-graph) · observed Jul 11, 2026
- GitHub forks (tirth8205/code-review-graph) · observed Jul 11, 2026
- Last push (tirth8205/code-review-graph) · observed Jun 14, 2026
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: BIG-bench 3.2k · code-review-graph 19k (synced Jul 12, 2026).
Common questions
- What is the difference between BIG-bench and code-review-graph?
- BIG-bench: Collaborative benchmark for language model capabilities. code-review-graph: Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo w. See the comparison table for live GitHub stats and shared categories.
- When should I choose BIG-bench over code-review-graph?
- Choose BIG-bench over code-review-graph when License: BIG-bench is Apache-2.0, code-review-graph is MIT; Requirements: Python 3.5-3.8 required.;
pytestis necessary for running automated tests.; Tags unique to BIG-bench: tasks creation, evaluation, seqio, language-models; When you need a comprehensive benchmark that evaluates language models across various tasks and includes methods for extrapolating model capabilities. - When should I choose code-review-graph over BIG-bench?
- Choose code-review-graph over BIG-bench when License: code-review-graph is MIT, BIG-bench is Apache-2.0; Tags unique to code-review-graph: graphrag, ai-coding, incremental, llm; Also covers LLM Frameworks, Developer Tools.
- When should I avoid BIG-bench?
- If you are looking for a tool that simplifies benchmarking with minimal configuration, BIG-bench requires setting up an environment and can be more complex compared to streamlined benchmark tools. As BIG-bench relies on collaboration across various tasks and contributions from the community, it might not be ideal if you need benchmark tasks or evaluations immediately available without potential If your project does not require advanced extrapolation techniques for measuring model capabilities over a wide range of benchmarks, simpler evaluation tools may suffice.
- When should I avoid code-review-graph?
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
- Is BIG-bench or code-review-graph more popular on GitHub?
- code-review-graph has more GitHub stars (19,416 vs 3,248). Stars measure visibility, not whether either tool fits your constraints.
- Are BIG-bench and code-review-graph open source?
- Yes - both are open-source projects on GitHub (BIG-bench: Apache-2.0, code-review-graph: MIT).
- Where can I find alternatives to BIG-bench or code-review-graph?
- GraphCanon lists graph-backed alternatives at BIG-bench alternatives and code-review-graph alternatives (BIG-bench markdown twin, code-review-graph markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, BIG-bench or code-review-graph?
- BIG-bench: Archived. code-review-graph: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for BIG-bench and code-review-graph?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: BIG-bench trust report; code-review-graph trust report.