AI Gateway Analysis: OpenRouter vs Higress

Author: Wang Chen

In classic application architecture, a "gateway" often signifies unified access for user requests, authentication, flow control, protocol transformation, and other functions. Gateways like Nginx, Envoy, and Kong are typical representatives of such capabilities. Whether in microservices architecture or cloud-native architecture, the usage logic for these products is relatively straightforward, and the selection criteria are also quite stable.

However, entering the era of AI applications, the originally clear definition of the "gateway" concept is being reshaped. For example, the recently popular OpenRouter, which previously identified itself as an LLM Marketplace, has begun to position itself as an "AI Gateway. "

This marks three significant changes:

• The types of AI Gateway vendors have diversified: there are not only public cloud vendors, such as Alibaba Cloud API Gateway (Higress), and independent gateway vendors like Kong providing privatized services and open-source solutions but also startups like OpenRouter that have entered the field based on the rigid demands of model invocation.

• The user profile of AI Gateway has become richer: it includes not only operations and SRE responsible for infrastructure but also a large community of programmers using general models and AI programming models to invoke services.

• The capability scope of AI Gateway has been expanded: not limited to support for enterprise delivery scenarios, but also providing traffic governance and user access control capabilities at the large model level when building AI applications, and catering to scenarios where programmers invoke large model services, offering unified, easy-to-use, and cost-effective model integration capabilities.

This brings a certain cognitive burden to developers and enterprise users. In the past, we only needed to compare several hard indicators such as the standards followed by the gateway, kernel, performance, plugin system, upstream and downstream integration capabilities, observability, and other enterprise-level capabilities; today, we need to define different types of AI Gateways by combining user profiles and demand scenarios. This article aims to clarify the correlation and differences between these two different forms of AI Gateway, represented by OpenRouter vs. Higress, from the perspectives of background, development history, positioning, and functions.

1. Background and Evolution

The evolution trajectory of every tech product is deeply influenced by its initial form and customer needs. AI Gateway is no exception. Therefore, understanding the background and evolution of Higress and OpenRouter will deepen our understanding of the two.

OpenRouter: A Product Born from Model Prosperity

OpenRouter was initially launched in 2023 with the goal of addressing the cumbersome issue of "invoking and comparing multiple mainstream large model API performance differences." OpenRouter unified and encapsulated the API interfaces of mainstream model vendors such as OpenAI, Anthropic, Google, DeepSeek, Qwen, Kimi, etc., integrating previously dispersed and structurally inconsistent invocation methods into a unified standard (most of which follow OpenAI's interface specifications), and providing a single API Key management entry, allowing developers to invoke multiple large model vendors' APIs simultaneously. They can use their API Key (BYOK) or recharge to use the platform-provided Key (with a 5% service fee).

The speed of invoking models and the quick landing of popular models are its core advantages, directly addressing the pain points of the programming community.

From the early simple interface unified integration to gradually introducing load balancing between models, continuously optimizing calling performance, invoking log queries, Key permission division, model availability observation, etc., it has gradually evolved from a "model aggregator" to a lightweight "model invocation gateway." By late 2024, OpenRouter clearly stated that it is an "AI Gateway" and expanded its capability boundaries to include model load balancing, traffic limiting, and immediate caching, aligning more closely with gateway capabilities.

The core driving force behind this evolutionary path comes from the genuine needs of enterprise-level customers: how to invoke multiple models with minimal access costs, experiment with model effects, manage Token costs, etc. Therefore, OpenRouter has consistently focused on "simplifying the invocation experience," forming its current model aggregation + lightweight gateway form.

Higress: Evolving with Application Architecture Development

In contrast to OpenRouter's "new species" characteristics, Higress represents the classic route of gateway evolution, developing gradually alongside application architecture.

Higress was open-sourced in 2022, initially aimed at building a gateway for cloud-native scenarios, integrating Istio's service governance philosophy, Envoy's high-performance data plane capabilities, and implementing strong customization capabilities based on a WebAssembly plugin architecture. In 2024, with the arrival of the AI application wave, Higress released v1.4, becoming the first in the country to offer capabilities such as large model proxies, security protection, access authentication, observability, caching, and prompt engineering targeting large model scenarios, quickly attracting the attention of AI developers. In 2025, it further enhanced its open-source offerings, enabling bulk zero-code transition of existing APIs to MCP Servers and offloading the MCP network protocol, eliminating the maintenance work associated with releasing new MCP versions, and launched the Higress MCP Marketplace, becoming the only open-source gateway solution in the domestic MCP scenario.

The evolution of Higress is an extension driven by an upgrade of application architecture, rather than starting from scratch, but integrating AI capabilities into the cloud-native gateway’s foundation through plugins and integration mechanisms. This method naturally aligns with the demands for AI implementation in existing applications, making it friendlier for enterprise-level customers.

2. Product Positioning and Functions

Although both OpenRouter and Higress promote themselves as “AI Gateways,” from the perspective of product positioning and functions, the two are not direct competitors but have each made their own deconstruction and reconstruction of the "gateway" capabilities from different starting points.

In summary: OpenRouter is designed for programmers to invoke AI services, while Higress is built for enterprises delivering AI applications. Next, we will explore the positioning and core functions of each project based on their user interfaces.

OpenRouter: Born for Programmers to Invoke AI Services

OpenRouter's positioning revolves around "standardized model invocation experience", continuously providing value-added SaaS services. Functionally, OpenRouter focuses on two core dimensions: model aggregation (Model) and invocation experience (Chat).

Model Aggregation (Model): It supports multiple model vendors, providing a unified API, allowing users to access hundreds of AI models through a single endpoint, and includes white screen parameter configurations such as input types, supported context lengths, and unit price filtering for models.

OpenRouter provides completion APIs compatible with OpenAI for over 400 models and vendors, which can be directly invoked or called using the OpenAI SDK. Additionally, it offers some third-party SDKs.

Invocation Experience (Chat): An online multi-model conversation tool that provides a unified conversation interface, making it easy for developers to view output differences, compare model response effects, debug prompts, and evaluate context performance.

Ranking: It uses tokens as measurement units to provide rankings of invocation volume across three dimensions: general models, Coding models, and Agents.

Moreover, it offers many experience optimizations around model invocation, such as:

• Routing and policy control: Provides lightweight control capabilities such as model priority settings, request condition routing, token usage monitoring, and failure retries, helping developers optimize invocation stability and cost efficiency.

• Permission and multi-tenant support: Supports setting access scopes and frequency limits for each API Key, facilitating resource sharing among teams while ensuring secure isolation.

• Availability detection and model status feedback: Particularly suitable for scenarios that involve high-frequency iterations such as prompt experiments and A/B tuning.

Overall, OpenRouter is inherently suitable for constructing an abstract layer for model invocation; however, it still has significant shortcomings in lower-level network protocols, granular security governance, and enterprise application integration.

Higress: Built for Enterprises Delivering AI Applications

Higress's positioning: A gateway created for enterprises to deliver AI applications, supporting the production-based landing of enterprise AI applications. This means that the clients served by Higress are not programmers but enterprises, ensuring that enterprises can reliably deliver model services to users. Its three main usage scenarios are as follows:

• Container and microservices gateway: Provides management from cluster entry traffic to backend microservices, including routing forwarding, security certification, protocol conversion, and combines microservice governance capabilities to provide full-link grayscale and traffic limiting to ensure link stability.

• Large model gateway: Unifies and proxies various mainstream large models and self-built large model services, providing OpenAI-compatible access methods, and offering secondary API KEY issuance, traffic limiting, security protection, observation, and other governance capabilities.

• MCP gateway: Supports rapid conversion from API to MCP and provides MCP Server proxy, security authentication, as well as unified observation and traffic limiting governance capabilities.

Therefore, from the Higress console, it provides routing, domain, and service source configurations for enterprise application integration, along with consumer management, certificate management, and observability metrics for the gateway's CPU, Memory, and user requests.

Additionally, through a wealth of plugins, it expands the capabilities of the gateway, such as traffic limiting, intent recognition, content review, etc.

In the Higress MCP marketplace, existing APIs can be converted into Remote MCP Servers and uploaded to the marketplace.

It supports rapid integration and invocation of mainstream open-source Agents in the country.

Moreover, Higress is friendly to multi-cloud and privatization deployments. Its architecture supports various deployment forms, allowing flexible integration into the existing application architecture systems of enterprises. Hence, Higress is an enterprise-level AI gateway targeting "complex access scenarios + high stability requirements," suitable for carrying the foundational infrastructure role for the landing of internal AI applications for enterprises.

3. Services and Billing

From a positioning perspective, OpenRouter and Higress represent two completely different AI Gateways in terms of usage scenarios, thus their service and billing models are completely different.

Since OpenRouter provides model invocation services, it operates under the billing rules of various model vendors:

• Apply for each model's API Key through OpenRouter: Recharge OpenRouter's Credit limit and incur a 5.5% toll fee (supporting cryptocurrency, with a 5% toll fee), and Credit is consumed at an equivalent value based on the model vendor's pricing.

• Using one's own API Key (BYOK), OpenRouter charges an additional 5% toll fee, which can be offset using the Credit limit.

• Some capabilities are open-sourced through SDK, such as openrouter-runner (Star 1k), which provides access to multiple models and fallback capabilities.

The core of Higress is based on Istio and Envoy, and its core capabilities are all open-source, following the Apache-2.0 license, supporting multiple deployment modes such as public cloud, private cloud, and hybrid cloud. In addition, it offers a cloud-hosted version of Alibaba Cloud API Gateway, enhancing performance, stability, usability, security, cloud product integration, observability, and other enterprise-level capabilities.