--- title: "ai-gateway vs LLM-FineTuning-Large-Language-Models" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ferro-labs-ai-gateway-vs-rohan-paul-llm-finetuning-large-language-models" tools: ["ferro-labs-ai-gateway", "rohan-paul-llm-finetuning-large-language-models"] --- # ai-gateway vs LLM-FineTuning-Large-Language-Models *GraphCanon updated Aug 25, 2026* ## Verdict Pick ai-gateway if ai-gateway from Ferro Labs supports over 30 LLMs with integrated caching, guardrails, A/B testing, and cost controls, making it ideal for managing multiple language models in a production environment; pick LLM-FineTuning-Large-Language-Models if lLM-FineTuning-Large-Language-Models is a Jupyter Notebook repository focused on fine-tuning large language models including GPT-3, GPT3-Turbo, LLaMA2, and Mistral-7B using Pytorch. [ai-gateway](https://docs.ferrolabs.ai) reports 219 GitHub stars, 33 forks, and 63 open issues, last pushed Aug 7, 2026. [LLM-FineTuning-Large-Language-Models](https://github.com/rohan-paul/LLM-FineTuning-Large-Language-Models) has 577 stars, 136 forks, and 2 open issues, last pushed Apr 1, 2025. Figures are from public GitHub metadata via [ai-gateway's repository](https://github.com/ferro-labs/ai-gateway) and [LLM-FineTuning-Large-Language-Models's repository](https://github.com/rohan-paul/LLM-FineTuning-Large-Language-Models). | | [ai-gateway](/tools/ferro-labs-ai-gateway.md) | [LLM-FineTuning-Large-Language-Models](/tools/rohan-paul-llm-finetuning-large-language-models.md) | | --- | --- | --- | | Tagline | Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls | LLM FineTuning | | Stars | 219 | 577 | | Forks | 33 | 136 | | Open issues | 63 | 2 | | Language | Go | Jupyter Notebook | | Adopt for | ai-gateway from Ferro Labs supports over 30 LLMs with integrated caching, guardrails, A/B testing, and cost controls, making it ideal for managing multiple language models in a production environment. | LLM-FineTuning-Large-Language-Models is a Jupyter Notebook repository focused on fine-tuning large language models including GPT-3, GPT3-Turbo, LLaMA2, and Mistral-7B using Pytorch. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 - a permissive free software license | The license information for LLM-FineTuning-Large-Language-Models was not explicitly provided in the repository details given. | | Categories | Inference & Serving, Model Training | Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ai-gateway](/tools/ferro-labs-ai-gateway.md) | [LLM-FineTuning-Large-Language-Models](/tools/rohan-paul-llm-finetuning-large-language-models.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 2d | 510d | | Open issues (now) | 63 | 2 | | Stars delta | Unknown | +1 (30d) | | Open issues delta | Unknown | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/ferro-labs-ai-gateway/trust.md) | [trust report](/tools/rohan-paul-llm-finetuning-large-language-models/trust.md) | ## Decision facts: ai-gateway - **Adopt for:** ai-gateway from Ferro Labs supports over 30 LLMs with integrated caching, guardrails, A/B testing, and cost controls, making it ideal for managing multiple language models in a production environment. - **License detail:** Apache-2.0 - a permissive free software license ## Decision facts: LLM-FineTuning-Large-Language-Models - **Adopt for:** LLM-FineTuning-Large-Language-Models is a Jupyter Notebook repository focused on fine-tuning large language models including GPT-3, GPT3-Turbo, LLaMA2, and Mistral-7B using Pytorch. - **License detail:** The license information for LLM-FineTuning-Large-Language-Models was not explicitly provided in the repository details given. ## Choose when ### Choose ai-gateway if… - ai-gateway is primarily Go; LLM-FineTuning-Large-Language-Models is Jupyter Notebook. - Tags unique to ai-gateway: ai-gateway, litellm, llm-cost, llm-proxy. - When you need to integrate more than 30 different LLM services including OpenAI and Anthropic ### Choose LLM-FineTuning-Large-Language-Models if… - LLM-FineTuning-Large-Language-Models is primarily Jupyter Notebook; ai-gateway is Go. - Tags unique to LLM-FineTuning-Large-Language-Models: gpt-3, gpt3-turbo, llama2, mistral-7b. - When you specifically need to work with GPT-3, GPT3-Turbo, LLaMA2, or Mistral-7B models within a Jupyter Notebook environment for fine-tuning tasks. ## When NOT to use ai-gateway - If your project only involves one or two LLMs which does not necessitate the gateway's broad compatibility features - For small-scale projects that do not require comprehensive cost analysis tools - When custom integration for specific guardrails is required, as ai-gateway offers generalized settings ## When NOT to use LLM-FineTuning-Large-Language-Models - Do not use this repository if you are looking to work with frameworks other than Pytorch, as it is specifically tied to Pytorch implementations. - Avoid choosing this tool if you do not need model finetuning capabilities and instead require only inference or serving services from your language models. ## Common questions ### What is the difference between ai-gateway and LLM-FineTuning-Large-Language-Models? ai-gateway: Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls. LLM-FineTuning-Large-Language-Models: LLM FineTuning. See the comparison table for live GitHub stats and shared categories. ### When should I choose ai-gateway over LLM-FineTuning-Large-Language-Models? Choose ai-gateway over LLM-FineTuning-Large-Language-Models when ai-gateway is primarily Go; LLM-FineTuning-Large-Language-Models is Jupyter Notebook; Tags unique to ai-gateway: ai-gateway, litellm, llm-cost, llm-proxy; When you need to integrate more than 30 different LLM services including OpenAI and Anthropic. ### When should I choose LLM-FineTuning-Large-Language-Models over ai-gateway? Choose LLM-FineTuning-Large-Language-Models over ai-gateway when LLM-FineTuning-Large-Language-Models is primarily Jupyter Notebook; ai-gateway is Go; Tags unique to LLM-FineTuning-Large-Language-Models: gpt-3, gpt3-turbo, llama2, mistral-7b; When you specifically need to work with GPT-3, GPT3-Turbo, LLaMA2, or Mistral-7B models within a Jupyter Notebook environment for fine-tuning tasks. ### When should I avoid ai-gateway? If your project only involves one or two LLMs which does not necessitate the gateway's broad compatibility features For small-scale projects that do not require comprehensive cost analysis tools When custom integration for specific guardrails is required, as ai-gateway offers generalized settings ### When should I avoid LLM-FineTuning-Large-Language-Models? Do not use this repository if you are looking to work with frameworks other than Pytorch, as it is specifically tied to Pytorch implementations. Avoid choosing this tool if you do not need model finetuning capabilities and instead require only inference or serving services from your language models. ### Is ai-gateway or LLM-FineTuning-Large-Language-Models more popular on GitHub? LLM-FineTuning-Large-Language-Models has more GitHub stars (577 vs 219). Stars measure visibility, not whether either tool fits your constraints. ### Are ai-gateway and LLM-FineTuning-Large-Language-Models open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to ai-gateway or LLM-FineTuning-Large-Language-Models? GraphCanon lists graph-backed alternatives at [ai-gateway alternatives](/tools/ferro-labs-ai-gateway/alternatives) and [LLM-FineTuning-Large-Language-Models alternatives](/tools/rohan-paul-llm-finetuning-large-language-models/alternatives) ([ai-gateway markdown twin](/tools/ferro-labs-ai-gateway/alternatives.md), [LLM-FineTuning-Large-Language-Models markdown twin](/tools/rohan-paul-llm-finetuning-large-language-models/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/ferro-labs-ai-gateway-vs-rohan-paul-llm-finetuning-large-language-models.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ai-gateway or LLM-FineTuning-Large-Language-Models? ai-gateway: Very active. LLM-FineTuning-Large-Language-Models: 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 ai-gateway and LLM-FineTuning-Large-Language-Models? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ai-gateway trust report](/tools/ferro-labs-ai-gateway/trust); [LLM-FineTuning-Large-Language-Models trust report](/tools/rohan-paul-llm-finetuning-large-language-models/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ferro-labs-ai-gateway`](/api/graphcanon/graph?tool=ferro-labs-ai-gateway) - 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/_