Comparison
TinyZero vs Agent-Reach
Verdict
Pick TinyZero when license: TinyZero is Apache-2.0, Agent-Reach is MIT; pick Agent-Reach when license: Agent-Reach is MIT, TinyZero is Apache-2.0.
Markdown twin · TinyZero alternatives · Agent-Reach alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | TinyZero | Agent-Reach |
|---|---|---|
| Maintenance | Slowing (134d since push) As of today · github_public_v1 | Very active (0d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Personal account As of today · github_public_v1 | Not a fork · Personal account As of today · github_public_v1 |
| Security (OSV) | No criticals As of today · osv@v1 | No MCP manifest As of today · mcp_manifest |
Tagline
- TinyZero
- Minimal reproduction of DeepSeek R1-Zero
- Agent-Reach
- Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.
Stars
- TinyZero
- 13k
- Agent-Reach
- 55k
Forks
- TinyZero
- 1.6k
- Agent-Reach
- 4.5k
Open issues
- TinyZero
- 82
- Agent-Reach
- 144
Language
- TinyZero
- Python
- Agent-Reach
- Python
Adopt for
- TinyZero
- TinyZero is a scaled-down version of the R1-Zero architecture from DeepSeek, focusing on minimal setup with essential components.
- Agent-Reach
- -
Persona
- TinyZero
- -
- Agent-Reach
- -
Runtime
- TinyZero
- -
- Agent-Reach
- -
License
- TinyZero
- TinyZero is licensed under Apache-2.0, allowing for broad usage with attribution requirements.
- Agent-Reach
- MIT
Last pushed
- TinyZero
- Feb 27, 2026
- Agent-Reach
- Jul 10, 2026
Categories
- TinyZero
- LLM Frameworks
- Agent-Reach
- AI Agents, LLM Frameworks, Developer Tools
Trust and health
Maintenance
- TinyZero
- Slowing (36%)
- Agent-Reach
- Very active (96%)
Days since push
- TinyZero
- 134d
- Agent-Reach
- 0d
Open issues (now)
- TinyZero
- 82
- Agent-Reach
- 144
Security scan
- TinyZero
- No criticals
- Agent-Reach
- No MCP manifest
Full report
- TinyZero
- Trust report
- Agent-Reach
- Trust report
Choose TinyZero if…
- License: TinyZero is Apache-2.0, Agent-Reach is MIT.
- Pricing: The framework itself is free and can be used without charge;.
- Requirements: Min 4 GB RAM; Specific Python environment setup (Python 3.9) and dependency installation steps are outlined in the README..
- Tags unique to TinyZero: ray, deepseek, vllm, r1-zero.
- When you need a streamlined implementation of the R1-Zero architecture without unnecessary complexity.
When NOT to use TinyZero
- If your project demands extensive customization options not available in this minimal version.
- When working with environments where specific versions of PyTorch older than 2.4.0 are required, as TinyZero mandates the use of PyTorch 2.4.0 or allows vLLM to manage its installation.
Choose Agent-Reach if…
- License: Agent-Reach is MIT, TinyZero is Apache-2.0.
- Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code.
- Also covers AI Agents, Developer Tools.
When NOT to use Agent-Reach
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (Jiayi-Pan/TinyZero) · observed Jul 12, 2026
- GitHub forks (Jiayi-Pan/TinyZero) · observed Jul 12, 2026
- Last push (Jiayi-Pan/TinyZero) · observed Feb 27, 2026
- 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 (Panniantong/Agent-Reach) · observed Jul 11, 2026
- GitHub forks (Panniantong/Agent-Reach) · observed Jul 11, 2026
- Last push (Panniantong/Agent-Reach) · observed Jul 10, 2026
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: TinyZero 13k · Agent-Reach 55k (synced Jul 12, 2026).
Common questions
- What is the difference between TinyZero and Agent-Reach?
- TinyZero: Minimal reproduction of DeepSeek R1-Zero. Agent-Reach: Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.. See the comparison table for live GitHub stats and shared categories.
- When should I choose TinyZero over Agent-Reach?
- Choose TinyZero over Agent-Reach when License: TinyZero is Apache-2.0, Agent-Reach is MIT; Pricing: The framework itself is free and can be used without charge;; Requirements: Min 4 GB RAM; Specific Python environment setup (Python 3.9) and dependency installation steps are outlined in the README.; Tags unique to TinyZero: ray, deepseek, vllm, r1-zero; When you need a streamlined implementation of the R1-Zero architecture without unnecessary complexity.
- When should I choose Agent-Reach over TinyZero?
- Choose Agent-Reach over TinyZero when License: Agent-Reach is MIT, TinyZero is Apache-2.0; Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code; Also covers AI Agents, Developer Tools.
- When should I avoid TinyZero?
- If your project demands extensive customization options not available in this minimal version. When working with environments where specific versions of PyTorch older than 2.4.0 are required, as TinyZero mandates the use of PyTorch 2.4.0 or allows vLLM to manage its installation.
- When should I avoid Agent-Reach?
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. 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.
- Is TinyZero or Agent-Reach more popular on GitHub?
- Agent-Reach has more GitHub stars (54,715 vs 13,192). Stars measure visibility, not whether either tool fits your constraints.
- Are TinyZero and Agent-Reach open source?
- Yes - both are open-source projects on GitHub (TinyZero: Apache-2.0, Agent-Reach: MIT).
- Where can I find alternatives to TinyZero or Agent-Reach?
- GraphCanon lists graph-backed alternatives at TinyZero alternatives and Agent-Reach alternatives (TinyZero markdown twin, Agent-Reach 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, TinyZero or Agent-Reach?
- TinyZero: Slowing. Agent-Reach: 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 TinyZero and Agent-Reach?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: TinyZero trust report; Agent-Reach trust report.