--- title: "whichllm vs ai-gateway" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/andyyyy64-whichllm-vs-ferro-labs-ai-gateway" tools: ["andyyyy64-whichllm", "ferro-labs-ai-gateway"] --- # whichllm vs ai-gateway *GraphCanon updated Sep 20, 2026* ## Verdict Pick whichllm if whichllm is designed to help users identify and benchmark local large language models that perform well on their specific hardware configuration via real-time benchmarks; 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. [whichllm](https://github.com/Andyyyy64/whichllm) reports 6.7k GitHub stars, 368 forks, and 13 open issues, last pushed Sep 19, 2026. [ai-gateway](https://docs.ferrolabs.ai) has 256 stars, 35 forks, and 68 open issues, last pushed Sep 10, 2026. Figures are from public GitHub metadata via [whichllm's repository](https://github.com/Andyyyy64/whichllm) and [ai-gateway's repository](https://github.com/ferro-labs/ai-gateway). | | [whichllm](/tools/andyyyy64-whichllm.md) | [ai-gateway](/tools/ferro-labs-ai-gateway.md) | | --- | --- | --- | | Tagline | Command-line tool to find and benchmark local LLM performance | Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls | | Stars | 6,666 | 256 | | Forks | 368 | 35 | | Open issues | 13 | 68 | | Language | Python | Go | | Adopt for | whichllm is designed to help users identify and benchmark local large language models that perform well on their specific hardware configuration via real-time benchmarks. | 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. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 - a permissive free software license | | Categories | Evaluation & Observability, Inference & Serving | Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [whichllm](/tools/andyyyy64-whichllm.md) | [ai-gateway](/tools/ferro-labs-ai-gateway.md) | | --- | --- | --- | | Days since push | 0d | 2d | | Open issues (now) | 13 | 68 | | Stars delta | +441 (30d) | +37 (30d) | | Open issues delta | -9 (30d) | +5 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/andyyyy64-whichllm/trust.md) | [trust report](/tools/ferro-labs-ai-gateway/trust.md) | ## Shared compatibility - **Python**: [whichllm](/tools/andyyyy64-whichllm.md) - Python runtime; [ai-gateway](/tools/ferro-labs-ai-gateway.md) - Python runtime ## Decision facts: whichllm - **Adopt for:** whichllm is designed to help users identify and benchmark local large language models that perform well on their specific hardware configuration via real-time benchmarks. ## 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 ## Choose when ### Choose whichllm if… - whichllm is primarily Python; ai-gateway is Go. - License: whichllm is MIT, ai-gateway is Apache-2.0. - Tags unique to whichllm: ai, apple-silicon, benchmarks, cli. - Also covers Evaluation & Observability. - When you need to quickly discover which locally available LLM runs most efficiently on your Apple Silicon or GPU infrastructure using Python scripts ### Choose ai-gateway if… - ai-gateway is primarily Go; whichllm is Python. - License: ai-gateway is Apache-2.0, whichllm is MIT. - Tags unique to ai-gateway: ai-gateway, litellm, llm-cost, llm-proxy. - Also covers Model Training. - When you need to integrate more than 30 different LLM services including OpenAI and Anthropic ## When NOT to use whichllm - In scenarios where extensive customization of benchmarking criteria beyond what this tool offers is required - When you are working in a non-Python environment and prefer not to introduce Python scripts into your workflow ## 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 ## Common questions ### What is the difference between whichllm and ai-gateway? whichllm: Command-line tool to find and benchmark local LLM performance. ai-gateway: Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls. See the comparison table for live GitHub stats and shared categories. ### When should I choose whichllm over ai-gateway? Choose whichllm over ai-gateway when whichllm is primarily Python; ai-gateway is Go; License: whichllm is MIT, ai-gateway is Apache-2.0; Tags unique to whichllm: ai, apple-silicon, benchmarks, cli; Also covers Evaluation & Observability; When you need to quickly discover which locally available LLM runs most efficiently on your Apple Silicon or GPU infrastructure using Python scripts. ### When should I choose ai-gateway over whichllm? Choose ai-gateway over whichllm when ai-gateway is primarily Go; whichllm is Python; License: ai-gateway is Apache-2.0, whichllm is MIT; Tags unique to ai-gateway: ai-gateway, litellm, llm-cost, llm-proxy; Also covers Model Training; When you need to integrate more than 30 different LLM services including OpenAI and Anthropic. ### When should I avoid whichllm? In scenarios where extensive customization of benchmarking criteria beyond what this tool offers is required When you are working in a non-Python environment and prefer not to introduce Python scripts into your workflow ### 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 ### Is whichllm or ai-gateway more popular on GitHub? whichllm has more GitHub stars (6,666 vs 256). Stars measure visibility, not whether either tool fits your constraints. ### Are whichllm and ai-gateway open source? Yes - both are open-source projects on GitHub (whichllm: MIT, ai-gateway: Apache-2.0). ### Where can I find alternatives to whichllm or ai-gateway? GraphCanon lists graph-backed alternatives at [whichllm alternatives](/tools/andyyyy64-whichllm/alternatives) and [ai-gateway alternatives](/tools/ferro-labs-ai-gateway/alternatives) ([whichllm markdown twin](/tools/andyyyy64-whichllm/alternatives.md), [ai-gateway markdown twin](/tools/ferro-labs-ai-gateway/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/andyyyy64-whichllm-vs-ferro-labs-ai-gateway.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, whichllm or ai-gateway? whichllm: Very active. ai-gateway: 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 whichllm and ai-gateway? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [whichllm trust report](/tools/andyyyy64-whichllm/trust); [ai-gateway trust report](/tools/ferro-labs-ai-gateway/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=andyyyy64-whichllm`](/api/graphcanon/graph?tool=andyyyy64-whichllm) - 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/_