---
title: "tree-of-thought-llm vs agentflow"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/princeton-nlp-tree-of-thought-llm-vs-simonmesmith-agentflow"
tools: ["princeton-nlp-tree-of-thought-llm", "simonmesmith-agentflow"]
---

# tree-of-thought-llm vs agentflow

*GraphCanon updated Aug 17, 2026*

## Verdict

Pick tree-of-thought-llm if the 'Tree of Thoughts' approach provides a structured way to deliberate problem-solving using large language models and is well-suited for tasks requiring exploration through a tree-like structure; pick agentflow if agentflow simplifies the creation of complex workflows for large language models through simple JSON configurations.

[tree-of-thought-llm](https://arxiv.org/abs/2305.10601) reports 6.0k GitHub stars, 624 forks, and 8 open issues, last pushed Jan 16, 2025. [agentflow](https://github.com/simonmesmith/agentflow) has 320 stars, 27 forks, and 13 open issues, last pushed Aug 11, 2023. Figures are from public GitHub metadata via [tree-of-thought-llm's repository](https://github.com/princeton-nlp/tree-of-thought-llm) and [agentflow's repository](https://github.com/simonmesmith/agentflow).

| | [tree-of-thought-llm](/tools/princeton-nlp-tree-of-thought-llm.md) | [agentflow](/tools/simonmesmith-agentflow.md) |
| --- | --- | --- |
| Tagline | [NeurIPS 2023] Tree of Thoughts: Deliberate Problem Solving with Large Language Models | Complex LLM Workflows from Simple JSON |
| Stars | 6,048 | 320 |
| Forks | 624 | 27 |
| Open issues | 8 | 13 |
| Language | Python | Python |
| Adopt for | The 'Tree of Thoughts' approach provides a structured way to deliberate problem-solving using large language models and is well-suited for tasks requiring exploration through a tree-like structure. | Agentflow simplifies the creation of complex workflows for large language models through simple JSON configurations. |
| Persona | - | - |
| Runtime | - | - |
| License | MIT | MIT |
| Categories | LLM Frameworks, Model Training | AI Agents, LLM Frameworks |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [tree-of-thought-llm](/tools/princeton-nlp-tree-of-thought-llm.md) | [agentflow](/tools/simonmesmith-agentflow.md) |
| --- | --- | --- |
| Days since push | 577d | 1100d |
| Open issues (now) | 8 | 13 |
| Stars delta | +18 (30d) | -1 (30d) |
| Owner type | Organization | User |
| Full report | [trust report](/tools/princeton-nlp-tree-of-thought-llm/trust.md) | [trust report](/tools/simonmesmith-agentflow/trust.md) |

## Shared compatibility

- **Python**: [tree-of-thought-llm](/tools/princeton-nlp-tree-of-thought-llm.md) - Python runtime; [agentflow](/tools/simonmesmith-agentflow.md) - Python runtime

## Decision facts: tree-of-thought-llm

- **Requirements:** Min 4 GB RAM
- **Adopt for:** The 'Tree of Thoughts' approach provides a structured way to deliberate problem-solving using large language models and is well-suited for tasks requiring exploration through a tree-like structure.

## Decision facts: agentflow

- **Adopt for:** Agentflow simplifies the creation of complex workflows for large language models through simple JSON configurations.

## Choose when

### Choose tree-of-thought-llm if…

- Requirements: Min 4 GB RAM.
- Tags unique to tree-of-thought-llm: llm, prompting, tree-of-thoughts, tree-search.
- Also covers Model Training.
- - Use 'tree-of-thought-llm' when you need an approach that handles deliberative reasoning problems, like the game of 24, leveraging large language models.

### Choose agentflow if…

- Tags unique to agentflow: json, python, workflow-management.
- Also covers AI Agents.
- When you need to rapidly prototype LLM workflows with minimal coding via JSON configs

## When NOT to use tree-of-thought-llm

- - Avoid using 'tree-of-thought-llm' for problems that do not benefit from tree-like exploration or where the solution does not involve deliberate reasoning or step-by-step evaluation.
- - If real-time decision-making is critical and computational resources are limited, this tool might be too slow due to its reliance on large language models like GPT-4 which may introduce latency.

## When NOT to use agentflow

- Avoid if requiring advanced customization that goes beyond basic JSON configurations
- Not suitable for scenarios needing real-time dynamic changes in workflow setup during execution

## Common questions

### What is the difference between tree-of-thought-llm and agentflow?

tree-of-thought-llm: [NeurIPS 2023] Tree of Thoughts: Deliberate Problem Solving with Large Language Models. agentflow: Complex LLM Workflows from Simple JSON. See the comparison table for live GitHub stats and shared categories.

### When should I choose tree-of-thought-llm over agentflow?

Choose tree-of-thought-llm over agentflow when Requirements: Min 4 GB RAM; Tags unique to tree-of-thought-llm: llm, prompting, tree-of-thoughts, tree-search; Also covers Model Training; - Use 'tree-of-thought-llm' when you need an approach that handles deliberative reasoning problems, like the game of 24, leveraging large language models.

### When should I choose agentflow over tree-of-thought-llm?

Choose agentflow over tree-of-thought-llm when Tags unique to agentflow: json, python, workflow-management; Also covers AI Agents; When you need to rapidly prototype LLM workflows with minimal coding via JSON configs.

### When should I avoid tree-of-thought-llm?

- Avoid using 'tree-of-thought-llm' for problems that do not benefit from tree-like exploration or where the solution does not involve deliberate reasoning or step-by-step evaluation. - If real-time decision-making is critical and computational resources are limited, this tool might be too slow due to its reliance on large language models like GPT-4 which may introduce latency.

### When should I avoid agentflow?

Avoid if requiring advanced customization that goes beyond basic JSON configurations Not suitable for scenarios needing real-time dynamic changes in workflow setup during execution

### Is tree-of-thought-llm or agentflow more popular on GitHub?

tree-of-thought-llm has more GitHub stars (6,048 vs 320). Stars measure visibility, not whether either tool fits your constraints.

### Are tree-of-thought-llm and agentflow open source?

Yes - both are open-source projects on GitHub (tree-of-thought-llm: MIT, agentflow: MIT).

### Where can I find alternatives to tree-of-thought-llm or agentflow?

GraphCanon lists graph-backed alternatives at [tree-of-thought-llm alternatives](/tools/princeton-nlp-tree-of-thought-llm/alternatives) and [agentflow alternatives](/tools/simonmesmith-agentflow/alternatives) ([tree-of-thought-llm markdown twin](/tools/princeton-nlp-tree-of-thought-llm/alternatives.md), [agentflow markdown twin](/tools/simonmesmith-agentflow/alternatives.md)), 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](/compare/princeton-nlp-tree-of-thought-llm-vs-simonmesmith-agentflow.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, tree-of-thought-llm or agentflow?

tree-of-thought-llm: Dormant. agentflow: Dormant. 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 tree-of-thought-llm and agentflow?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [tree-of-thought-llm trust report](/tools/princeton-nlp-tree-of-thought-llm/trust); [agentflow trust report](/tools/simonmesmith-agentflow/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=princeton-nlp-tree-of-thought-llm`](/api/graphcanon/graph?tool=princeton-nlp-tree-of-thought-llm)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_