--- title: "gateway vs awesome-generative-ai" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/adaline-gateway-vs-filipecalegario-awesome-generative-ai" tools: ["adaline-gateway", "filipecalegario-awesome-generative-ai"] --- # gateway vs awesome-generative-ai *GraphCanon updated Jul 12, 2026* ## Verdict Pick gateway when license: gateway is MIT, awesome-generative-ai is CC0-1.0; pick awesome-generative-ai when license: awesome-generative-ai is CC0-1.0, gateway is MIT. [gateway](https://www.adaline.ai/docs) reports 599 GitHub stars, 27 forks, and 0 open issues, last pushed Jul 11, 2026. [awesome-generative-ai](https://github.com/filipecalegario/awesome-generative-ai) has 3.5k stars, 821 forks, and 250 open issues, last pushed Dec 18, 2025. Figures are from public GitHub metadata via [gateway's repository](https://github.com/adaline/gateway) and [awesome-generative-ai's repository](https://github.com/filipecalegario/awesome-generative-ai). | | [gateway](/tools/adaline-gateway.md) | [awesome-generative-ai](/tools/filipecalegario-awesome-generative-ai.md) | | --- | --- | --- | | Tagline | The only fully local production-grade Super SDK that provides a simple, unified, and powerful interface for calling more than 200+ LLMs. | A curated list of Generative AI tools, works, models, and references | | Stars | 599 | 3,499 | | Forks | 27 | 821 | | Open issues | 0 | 250 | | Language | TypeScript | - | | Adopt for | Adaline Gateway is a comprehensive SDK for local deployment, capable of calling more than 300 language models with integrated features like batching, caching, and extensible plugins. | - | | Persona | - | - | | Runtime | - | - | | License | MIT | CC0-1.0 | | Categories | AI Agents, Developer Tools, LLM Frameworks | AI Agents, LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [gateway](/tools/adaline-gateway.md) | [awesome-generative-ai](/tools/filipecalegario-awesome-generative-ai.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 205d | | Open issues (now) | 0 | 250 | | Owner type | Organization | User | | Full report | [trust report](/tools/adaline-gateway/trust.md) | [trust report](/tools/filipecalegario-awesome-generative-ai/trust.md) | ## Decision facts: gateway - **Pricing:** unknown - The repository description does not include pricing information. The software is available under the MIT license which allows for free usage but does not detail commercial support costs or enterprise- - **Adopt for:** Adaline Gateway is a comprehensive SDK for local deployment, capable of calling more than 300 language models with integrated features like batching, caching, and extensible plugins. ## Choose when ### Choose gateway if… - License: gateway is MIT, awesome-generative-ai is CC0-1.0. - Pricing: The repository description does not include pricing information. The software is available under the MIT license which allows for free usage but does not detail commercial support costs or enterprise-. - Tags unique to gateway: ai, ai-agents, anthropic, language-model. - Also covers Developer Tools. - - You require a fully local execution environment, thus avoiding any internet dependency or proxy setup. ### Choose awesome-generative-ai if… - License: awesome-generative-ai is CC0-1.0, gateway is MIT. - Tags unique to awesome-generative-ai: ai-art, awesome, awesome-list, chatgpt. - Also covers Vector Databases. ## When NOT to use gateway - - Your project depends on cloud-based API endpoints that require internet connectivity; Gateway operates fully locally and does not function as an online proxy. - - You do not need support from over 300 LLMs or the extensive feature set provided by Gateway, preferring a simpler SDK with fewer integrations. ## When NOT to use awesome-generative-ai - Last GitHub push was 206 days ago (slowing maintenance, Dec 18, 2025). Validate activity before betting a new project on awesome-generative-ai. - 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. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## Common questions ### What is the difference between gateway and awesome-generative-ai? gateway: The only fully local production-grade Super SDK that provides a simple, unified, and powerful interface for calling more than 200+ LLMs.. awesome-generative-ai: A curated list of Generative AI tools, works, models, and references. See the comparison table for live GitHub stats and shared categories. ### When should I choose gateway over awesome-generative-ai? Choose gateway over awesome-generative-ai when License: gateway is MIT, awesome-generative-ai is CC0-1.0; Pricing: The repository description does not include pricing information. The software is available under the MIT license which allows for free usage but does not detail commercial support costs or enterprise-; Tags unique to gateway: ai, ai-agents, anthropic, language-model; Also covers Developer Tools; - You require a fully local execution environment, thus avoiding any internet dependency or proxy setup. ### When should I choose awesome-generative-ai over gateway? Choose awesome-generative-ai over gateway when License: awesome-generative-ai is CC0-1.0, gateway is MIT; Tags unique to awesome-generative-ai: ai-art, awesome, awesome-list, chatgpt; Also covers Vector Databases. ### When should I avoid gateway? - Your project depends on cloud-based API endpoints that require internet connectivity; Gateway operates fully locally and does not function as an online proxy. - You do not need support from over 300 LLMs or the extensive feature set provided by Gateway, preferring a simpler SDK with fewer integrations. ### When should I avoid awesome-generative-ai? Last GitHub push was 206 days ago (slowing maintenance, Dec 18, 2025). Validate activity before betting a new project on awesome-generative-ai. 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. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is gateway or awesome-generative-ai more popular on GitHub? awesome-generative-ai has more GitHub stars (3,499 vs 599). Stars measure visibility, not whether either tool fits your constraints. ### Are gateway and awesome-generative-ai open source? Yes - both are open-source projects on GitHub (gateway: MIT, awesome-generative-ai: CC0-1.0). ### Where can I find alternatives to gateway or awesome-generative-ai? GraphCanon lists graph-backed alternatives at [gateway alternatives](/tools/adaline-gateway/alternatives) and [awesome-generative-ai alternatives](/tools/filipecalegario-awesome-generative-ai/alternatives) ([gateway markdown twin](/tools/adaline-gateway/alternatives.md), [awesome-generative-ai markdown twin](/tools/filipecalegario-awesome-generative-ai/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/adaline-gateway-vs-filipecalegario-awesome-generative-ai.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, gateway or awesome-generative-ai? gateway: Very active. awesome-generative-ai: 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 gateway and awesome-generative-ai? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [gateway trust report](/tools/adaline-gateway/trust); [awesome-generative-ai trust report](/tools/filipecalegario-awesome-generative-ai/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=adaline-gateway`](/api/graphcanon/graph?tool=adaline-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/_