--- title: "ai-gateway vs recurrentgemma" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ferro-labs-ai-gateway-vs-google-deepmind-recurrentgemma" tools: ["ferro-labs-ai-gateway", "google-deepmind-recurrentgemma"] --- # ai-gateway vs recurrentgemma *GraphCanon updated Aug 9, 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 recurrentgemma if recurrentGemma is an open-source language model from Google DeepMind, utilizing the Griffin architecture and supporting JAX and PyTorch for efficient neural network training and inference. [ai-gateway](https://docs.ferrolabs.ai) reports 219 GitHub stars, 33 forks, and 63 open issues, last pushed Aug 7, 2026. [recurrentgemma](https://github.com/google-deepmind/recurrentgemma) has 684 stars, 40 forks, and 4 open issues, last pushed Feb 6, 2026. Figures are from public GitHub metadata via [ai-gateway's repository](https://github.com/ferro-labs/ai-gateway) and [recurrentgemma's repository](https://github.com/google-deepmind/recurrentgemma). | | [ai-gateway](/tools/ferro-labs-ai-gateway.md) | [recurrentgemma](/tools/google-deepmind-recurrentgemma.md) | | --- | --- | --- | | Tagline | Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls | Open weights language model from Google DeepMind, based on Griffin | | Stars | 219 | 684 | | Forks | 33 | 40 | | Open issues | 63 | 4 | | Language | Go | Python | | 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. | RecurrentGemma is an open-source language model from Google DeepMind, utilizing the Griffin architecture and supporting JAX and PyTorch for efficient neural network training and inference on TPUs, CPUs, and GPUs. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 - a permissive free software license | The codebase is distributed under the permissive Apache License, version 2.0, allowing for broad usage but with no warranties expressed or implied. | | 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) | [recurrentgemma](/tools/google-deepmind-recurrentgemma.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 2d | 181d | | Open issues (now) | 63 | 4 | | Full report | [trust report](/tools/ferro-labs-ai-gateway/trust.md) | [trust report](/tools/google-deepmind-recurrentgemma/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: recurrentgemma - **Requirements:** Optimized for TPU using the Flax implementation.; Supports CPU and GPU environments via JAX and PyTorch. - **Adopt for:** RecurrentGemma is an open-source language model from Google DeepMind, utilizing the Griffin architecture and supporting JAX and PyTorch for efficient neural network training and inference on TPUs, CPUs, and GPUs. - **License detail:** The codebase is distributed under the permissive Apache License, version 2.0, allowing for broad usage but with no warranties expressed or implied. ## Choose when ### Choose ai-gateway if… - ai-gateway is primarily Go; recurrentgemma is Python. - 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 recurrentgemma if… - recurrentgemma is primarily Python; ai-gateway is Go. - Requirements: Optimized for TPU using the Flax implementation.; Supports CPU and GPU environments via JAX and PyTorch.. - Tags unique to recurrentgemma: deep-learning, flax, jax, language-model. - If you require high efficiency in neural network training or inferencing specifically optimized for TPUs using the Flax implementation ## 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 recurrentgemma - Do not use if your infrastructure does not support TensorFlow, since RecurrentGemma optimizes efficiency mostly on TPUs which are tightly coupled with TensorFlow's ecosystem - Avoid using this tool if you are working in a restricted environment where setting up virtual environments with tools like Poetry or manually managing dependencies with pip is challenging ## Common questions ### What is the difference between ai-gateway and recurrentgemma? ai-gateway: Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls. recurrentgemma: Open weights language model from Google DeepMind, based on Griffin. See the comparison table for live GitHub stats and shared categories. ### When should I choose ai-gateway over recurrentgemma? Choose ai-gateway over recurrentgemma when ai-gateway is primarily Go; recurrentgemma is Python; 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 recurrentgemma over ai-gateway? Choose recurrentgemma over ai-gateway when recurrentgemma is primarily Python; ai-gateway is Go; Requirements: Optimized for TPU using the Flax implementation.; Supports CPU and GPU environments via JAX and PyTorch.; Tags unique to recurrentgemma: deep-learning, flax, jax, language-model; If you require high efficiency in neural network training or inferencing specifically optimized for TPUs using the Flax implementation. ### 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 recurrentgemma? Do not use if your infrastructure does not support TensorFlow, since RecurrentGemma optimizes efficiency mostly on TPUs which are tightly coupled with TensorFlow's ecosystem Avoid using this tool if you are working in a restricted environment where setting up virtual environments with tools like Poetry or manually managing dependencies with pip is challenging ### Is ai-gateway or recurrentgemma more popular on GitHub? recurrentgemma has more GitHub stars (684 vs 219). Stars measure visibility, not whether either tool fits your constraints. ### Are ai-gateway and recurrentgemma open source? Yes - both are open-source projects on GitHub (ai-gateway: Apache-2.0, recurrentgemma: Apache-2.0). ### Where can I find alternatives to ai-gateway or recurrentgemma? GraphCanon lists graph-backed alternatives at [ai-gateway alternatives](/tools/ferro-labs-ai-gateway/alternatives) and [recurrentgemma alternatives](/tools/google-deepmind-recurrentgemma/alternatives) ([ai-gateway markdown twin](/tools/ferro-labs-ai-gateway/alternatives.md), [recurrentgemma markdown twin](/tools/google-deepmind-recurrentgemma/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-google-deepmind-recurrentgemma.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ai-gateway or recurrentgemma? ai-gateway: Very active. recurrentgemma: Slowing. 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 recurrentgemma? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ai-gateway trust report](/tools/ferro-labs-ai-gateway/trust); [recurrentgemma trust report](/tools/google-deepmind-recurrentgemma/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/_