Comparison
instruct-eval vs ai-berkshire
Verdict
Pick instruct-eval when license: instruct-eval is Apache-2.0, ai-berkshire is MIT; pick ai-berkshire when license: ai-berkshire is MIT, instruct-eval is Apache-2.0.
Markdown twin · instruct-eval alternatives · ai-berkshire alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | instruct-eval | ai-berkshire |
|---|---|---|
| Maintenance | Dormant (853d since push) As of today · github_public_v1 | Very active (0d 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) | 83 low (83 low) As of today · osv@v1 | No MCP manifest As of today · mcp_manifest |
Tagline
- instruct-eval
- Code for evaluating instruction-tuned language models like Alpaca and Flan-T5
- ai-berkshire
- AI-era Berkshire: a value investing research framework utilizing Claude Code / Codex with methodologies from Warren Buffett, Charlie Munger among others and multi-Agent adversarial analysis.
Stars
- instruct-eval
- 552
- ai-berkshire
- 13k
Forks
- instruct-eval
- 45
- ai-berkshire
- 1.8k
Open issues
- instruct-eval
- 24
- ai-berkshire
- 17
Language
- instruct-eval
- Python
- ai-berkshire
- Python
Adopt for
- instruct-eval
- -
- ai-berkshire
- ai-berkshire implements a unique approach to value investing research through AI agents powered by Claude Code/Codex, inspired by the methodologies of Warren Buffett and Charlie Munger amongst other investors. The tool's
Persona
- instruct-eval
- -
- ai-berkshire
- -
Runtime
- instruct-eval
- -
- ai-berkshire
- -
License
- instruct-eval
- Apache-2.0
- ai-berkshire
- MIT
Last pushed
- instruct-eval
- Mar 10, 2024
- ai-berkshire
- Jul 11, 2026
Categories
- instruct-eval
- Evaluation & Observability
- ai-berkshire
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- instruct-eval
- Dormant (18%)
- ai-berkshire
- Very active (96%)
Days since push
- instruct-eval
- 853d
- ai-berkshire
- 0d
Open issues (now)
- instruct-eval
- 24
- ai-berkshire
- 17
Owner type
- instruct-eval
- Organization
- ai-berkshire
- User
Security scan
- instruct-eval
- 83 low (83 low)
- ai-berkshire
- No MCP manifest
Full report
- instruct-eval
- Trust report
- ai-berkshire
- Trust report
Choose instruct-eval if…
- License: instruct-eval is Apache-2.0, ai-berkshire is MIT.
- Tags unique to instruct-eval: evaluation, safety-evaluation, performance-assessment, llm.
When NOT to use instruct-eval
- Last GitHub push was 854 days ago (dormant maintenance, Mar 10, 2024). Validate activity before betting a new project on instruct-eval.
- Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
Choose ai-berkshire if…
- License: ai-berkshire is MIT, instruct-eval is Apache-2.0.
- Tags unique to ai-berkshire: investment-research, ai, portfolio-management, value-investing.
- Also covers AI Agents.
- You need to leverage multi-Agent adversarial analysis for deep fundamental stock market assessment aligned with renowned investor philosophies.
When NOT to use ai-berkshire
- If your investment research requires real-time trading data or dynamic algorithmic trading strategies which are not the tool's expertise.
- When you prefer a more manual or traditional approach to value investing that does not integrate AI-driven adversarial agent methodologies.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (declare-lab/instruct-eval) · observed Jul 11, 2026
- GitHub forks (declare-lab/instruct-eval) · observed Jul 11, 2026
- Last push (declare-lab/instruct-eval) · observed Mar 10, 2024
- License file (Apache-2.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (xbtlin/ai-berkshire) · observed Jul 11, 2026
- GitHub forks (xbtlin/ai-berkshire) · observed Jul 11, 2026
- Last push (xbtlin/ai-berkshire) · observed Jul 11, 2026
- License file (MIT) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: instruct-eval 552 · ai-berkshire 13k (synced Jul 11, 2026).
Common questions
- What is the difference between instruct-eval and ai-berkshire?
- instruct-eval: Code for evaluating instruction-tuned language models like Alpaca and Flan-T5. ai-berkshire: AI-era Berkshire: a value investing research framework utilizing Claude Code / Codex with methodologies from Warren Buffett, Charlie Munger among others and multi-Agent adversarial analysis.. See the comparison table for live GitHub stats and shared categories.
- When should I choose instruct-eval over ai-berkshire?
- Choose instruct-eval over ai-berkshire when License: instruct-eval is Apache-2.0, ai-berkshire is MIT; Tags unique to instruct-eval: evaluation, safety-evaluation, performance-assessment, llm.
- When should I choose ai-berkshire over instruct-eval?
- Choose ai-berkshire over instruct-eval when License: ai-berkshire is MIT, instruct-eval is Apache-2.0; Tags unique to ai-berkshire: investment-research, ai, portfolio-management, value-investing; Also covers AI Agents; You need to leverage multi-Agent adversarial analysis for deep fundamental stock market assessment aligned with renowned investor philosophies.
- When should I avoid instruct-eval?
- Last GitHub push was 854 days ago (dormant maintenance, Mar 10, 2024). Validate activity before betting a new project on instruct-eval. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
- When should I avoid ai-berkshire?
- If your investment research requires real-time trading data or dynamic algorithmic trading strategies which are not the tool's expertise. When you prefer a more manual or traditional approach to value investing that does not integrate AI-driven adversarial agent methodologies.
- Is instruct-eval or ai-berkshire more popular on GitHub?
- ai-berkshire has more GitHub stars (12,711 vs 552). Stars measure visibility, not whether either tool fits your constraints.
- Are instruct-eval and ai-berkshire open source?
- Yes - both are open-source projects on GitHub (instruct-eval: Apache-2.0, ai-berkshire: MIT).
- Where can I find alternatives to instruct-eval or ai-berkshire?
- GraphCanon lists graph-backed alternatives at instruct-eval alternatives and ai-berkshire alternatives (instruct-eval markdown twin, ai-berkshire 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, instruct-eval or ai-berkshire?
- instruct-eval: Dormant. ai-berkshire: Very 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 instruct-eval and ai-berkshire?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: instruct-eval trust report; ai-berkshire trust report.