Top LiteLLM Alternatives in 2026: Compared by Cost, Performance & Features

In March 2026, LiteLLM became a supply-chain warning shot for AI infrastructure teams. Malicious versions of the litellm PyPI package, 1.82.7 and 1.82.8, were published with code designed to harvest environment variables, SSH keys, cloud credentials, Kubernetes tokens, database passwords, and other secrets. 

The incident was linked to TeamPCP, and even the shortest public timeline left a dangerous window: LiteLLM’s own security update says the packages were live for about 40 minutes before PyPI quarantine, while third-party researchers reported a longer exposure window. For a package downloaded more than 3 million times per day, that is not a small blast radius.

But security is only half the story. Even before the attack, many production teams were already hitting LiteLLM’s performance and operational limits: proxy overhead, self-hosting burden, observability gaps, and LLM-only coverage. This article compares the best LiteLLM alternatives in 2026 by cost, performance, security posture, and production-readiness.

Quick Comparison - 8 Best LiteLLM Alternatives in 2026

This table gives a fast view of the main LiteLLM competitors, but it should not be read as a universal ranking. The best option depends on the tradeoff your team is willing to make: managed convenience, self-hosted control, open-source flexibility, compliance needs, or model experimentation speed. Eden AI is strongest when teams need a managed gateway that goes beyond LLM routing and supports broader multimodal AI use cases.

What Happened to LiteLLM in 2026: The Supply Chain Attack 

In March 2026, two malicious versions of the litellm PyPI package, 1.82.7 and 1.82.8, were published with code designed to steal sensitive credentials, including environment variables, SSH keys, cloud credentials, Kubernetes tokens, and database passwords. LiteLLM later removed the affected packages and reported that its official Proxy Docker image was not impacted because it used pinned dependencies.

The risk was significant because LiteLLM often runs as a proxy between applications and model providers. In that position, it may handle provider API keys, internal service credentials, request metadata, and access to production environments. For teams using LiteLLM in this way, the incident was a reminder that an AI gateway is not just a developer tool; it is part of the security perimeter.

The same period also raised questions around compliance trust in the AI infrastructure ecosystem, after Delve, a compliance automation vendor, was publicly accused of issuing questionable SOC 2 and ISO 27001 materials. Delve disputed the claims, but the episode reinforced the need to verify compliance evidence carefully rather than relying only on vendor claims.

The decision point is simple: self-hosted proxies give more control, but they also increase the security and compliance work your team must own. Managed gateways reduce part of that burden by shifting infrastructure hardening, provider access management, patching, and gateway maintenance to a dedicated platform.

How to Choose a LiteLLM Alternative

Choosing a LiteLLM alternative is mostly an infrastructure decision. Start with one question: do you want to own the proxy layer, or do you want a managed gateway?

Managed gateway vs. self-hosted proxy

A self-hosted proxy gives you more control. You decide where it runs, how secrets are stored, how logs are handled, and how routing rules are configured.

The tradeoff is operational responsibility. Your team owns deployment, scaling, patching, monitoring, incident response, and security hardening. Because the proxy often handles provider API keys and production traffic, it also becomes part of your security surface.

A managed gateway is easier to adopt. The vendor handles the infrastructure, updates, availability, and provider integrations. Your team can focus more on shipping AI features and less on maintaining gateway services.

The tradeoff is less low-level customization and more dependency on the provider’s roadmap, uptime, and pricing.

Eden AI fits this managed gateway category. It is a good fit for teams that want access to many AI providers, multimodal capabilities, GDPR-conscious infrastructure, and less operational burden than running a self-hosted LiteLLM proxy.

Evaluation checklist

When comparing LiteLLM alternatives, check:

• Latency overhead: aim for less than 10ms added latency when possible.
• Provider coverage: check the number of supported LLMs and model families.
• MCP support: important for agentic workflows and tool-calling.
• Data residency and GDPR compliance: critical for European or regulated teams.
• Observability: look for cost tracking, request logs, traces, errors, and fallback visibility.
• Open-source availability: decide whether you need source access or self-hosting.
• Pricing model: compare per-request pricing, usage-based markups, flat plans, and enterprise contracts.

The 8 Best LiteLLM Alternatives in 2026

The best LiteLLM alternatives in 2026 are Eden AI, Portkey, Bifrost,Kong AI Gateway, Helicone AI Gateway, Vercel AI Gateway, OpenRouter and Cloudflare AI Gateway. We give you in-depth analysis of their pros and cons, best use cases and pricing below.  

1. Eden AI - best managed LiteLLM alternative for GDPR, multimodal AI, and European teams

Eden AI is not a one-to-one clone of LiteLLM. That is precisely why it belongs in this list.

LiteLLM is primarily an LLM proxy. Eden AI is a managed AI gateway that gives developers unified access to hundreds of LLMs and specialized AI models through a single API. That includes text generation, embeddings, vision, OCR, document parsing, speech-to-text, text-to-speech, translation, image analysis, moderation, and other AI capabilities.

That difference matters in production. Many AI products do not stop at chat completion. A real workflow might extract text from a PDF, classify a document, translate the result, run an LLM over it, generate a summary, and return structured JSON. If each capability requires a separate provider integration, your backend becomes harder to maintain. Eden AI reduces that complexity by standardizing access across multiple AI categories.

Why choose Eden AI over LiteLLM? 

Choose Eden AI if your team wants:

• A fully managed AI gateway
• One API for LLMs and specialized AI models
• Built-in provider comparison
• Routing by price, performance, and region
• Fallbacks for production reliability
• Unified billing and monitoring
• GDPR-ready infrastructure
• European data residency options
• Less internal infrastructure to maintain

This makes Eden AI especially relevant for European SaaS companies, B2B products handling sensitive customer data, and teams that need AI capabilities beyond LLM routing.

Where Eden AI is better than LiteLLM

Eden AI is stronger when the problem is not only “How do we proxy LLM calls?” but “How do we manage AI providers across the whole product?”

For example, a support automation product may need LLMs, OCR, translation, speech transcription, and moderation. A compliance product may need document extraction, entity recognition, classification, and summarization. A video intelligence product may need transcription, visual analysis, and structured text generation.

LiteLLM can help with the LLM layer. Eden AI can cover more of the AI stack.

Eden AI also makes more sense when your team wants a managed platform rather than another self-hosted service. You do not need to deploy the gateway, maintain proxy infrastructure, or build internal tooling for provider management from scratch.

Where LiteLLM may still be better

LiteLLM may be a better choice if you specifically want to self-host your LLM proxy and keep the gateway layer fully under your control. It is also a strong fit for engineering teams that want to customize routing logic deeply and are comfortable operating the infrastructure.

Eden AI is best when the priority is managed access, compliance, multimodal coverage, and production simplicity.

Best fit: Eden AI is the best LiteLLM alternative for teams that want a managed, GDPR-ready, multimodal AI gateway rather than a self-hosted LLM-only proxy.

2. Portkey - best LiteLLM alternative for LLM gateway controls

Portkey is one of the closest alternatives to LiteLLM if your main focus is LLM routing, reliability, and observability.

It provides an AI gateway with features like automatic retries, fallbacks, caching, load balancing, cost controls, virtual keys, and observability. It is built for teams that want a serious control plane in front of their LLM providers, without necessarily building and maintaining everything themselves.

LiteLLM vs Portkey

The litellm vs portkey comparison usually comes down to control versus managed product experience.

LiteLLM is attractive because it is open source, self-hostable, and flexible. You can run it as your own proxy and shape it around your infrastructure.

Portkey is attractive because it packages gateway features into a more productized platform. It is useful when your team wants reusable gateway configs, observability, fallbacks, caching, retries, and cost management without treating the gateway as a purely internal engineering project.

Why choose Portkey over LiteLLM?

Choose Portkey if you want:

• Managed LLM gateway features
• Advanced routing configs
• Fallback chains
• Load balancing
• Automatic retries
• Simple and semantic caching
• Observability built into the gateway
• Cost controls and virtual keys
• A more polished operational layer around LLM routing

Portkey can be a strong fit for companies running multiple LLM-powered features across different teams. Instead of every team implementing retries, fallbacks, caching, and logs independently, Portkey centralizes those concerns.

Where LiteLLM may still be better

LiteLLM is still compelling if you want to keep everything self-hosted and avoid depending on another managed control plane. It can also be simpler for small teams that only need a lightweight proxy with model aliases and provider switching.

Best fit

Portkey is best for teams that want an LLM-focused gateway with strong reliability and observability features, especially when they prefer a more managed experience than LiteLLM.

3. Bifrost - best open-source LiteLLM proxy replacement for performance-focused teams

Bifrost is one of the most relevant options for teams looking for litellm alternatives open source.

It positions itself as a high-performance AI gateway that unifies access to multiple providers through an OpenAI-compatible API. The main pitch is speed, resilience, and production-grade routing with automatic failover, load balancing, and caching.

Why choose Bifrost over LiteLLM?

Choose Bifrost if you want:

• An open-source AI gateway
• A self-hosted LiteLLM proxy replacement
• OpenAI-compatible API access
• Provider failover
• Load balancing
• Semantic caching
• Low gateway overhead
• More focus on performance and scalability

If your team is latency-sensitive, Bifrost is worth benchmarking against LiteLLM in your own environment. Gateway overhead is rarely the only latency factor in LLM applications, but for high-throughput workloads, every additional layer matters.

Where Bifrost is strongest

Bifrost is strongest for engineering teams that want to own the gateway layer but are evaluating alternatives to LiteLLM’s architecture. If your team has infrastructure experience and wants an open-source routing layer designed for performance, it should be on the shortlist.

Where Bifrost may not be enough

Bifrost is still an infrastructure component you operate. If your real problem is that you do not want to manage an AI gateway at all, Bifrost does not remove that responsibility. In that case, a managed gateway like Eden AI, Portkey, OpenRouter, Vercel AI Gateway, or Cloudflare AI Gateway may be more practical.

Best fit

Bifrost is the best LiteLLM open source alternative for teams that want a self-hosted, performance-oriented AI gateway.

4. Kong AI Gateway - best for enterprises already using API gateway infrastructure

Kong AI Gateway is different from most tools on this list. It is not just an LLM proxy. It is an AI gateway layer built into Kong’s broader API gateway ecosystem.

That makes it especially relevant for enterprise teams that already use Kong to manage API traffic, security, plugins, observability, and governance. Instead of adding a separate LLM proxy, they can extend their existing gateway strategy to AI traffic.

Why choose Kong AI Gateway over LiteLLM?

Choose Kong AI Gateway if your team needs:

• AI traffic management inside an enterprise API gateway
• Existing Kong plugin compatibility
• Centralized governance for API and AI traffic
• Semantic routing
• Semantic caching
• Guardrails
• Prompt transformations
• Load balancing
• Audit logs and metrics
• Secrets management
• Integration with broader API security controls

This is useful for larger organizations where AI traffic is not treated as a special side system. It becomes part of the same governance model as other production APIs.

Where Kong is stronger than LiteLLM

Kong is stronger when AI gateway requirements overlap with enterprise API management. If your organization already has API platform teams, security reviews, traffic policies, and centralized governance, Kong can fit naturally into that operating model.

LiteLLM is simpler and more developer-native for LLM-specific proxying. Kong is broader and more enterprise-oriented.

Where LiteLLM may still be better

If you only need an internal OpenAI-compatible LLM proxy, Kong may be more infrastructure than you need. LiteLLM is easier to evaluate quickly and may be a better fit for smaller teams that do not already operate Kong.

Best fit

Kong AI Gateway is best for enterprises that want AI gateway capabilities inside an existing API gateway strategy.

5. Helicone - best LiteLLM alternative for observability-first teams

Helicone started with a strong focus on LLM observability and has expanded into gateway capabilities. It gives teams a way to route requests through a unified interface while tracking costs, latency, usage, errors, and request-level behavior.

If your production pain is not just routing but understanding what is happening across LLM calls, Helicone is worth evaluating.

Why choose Helicone over LiteLLM?

Choose Helicone if your team cares about:

• LLM observability
• Request logging
• Cost tracking
• Latency monitoring
• User-level analytics
• Debugging production prompts
• OpenAI-compatible gateway access
• Automatic fallbacks
• Provider routing
• Fast integration with existing LLM apps

Helicone is useful when engineering and product teams need visibility into how AI features behave in production. For example, you may want to know which users generate the most cost, which prompts produce errors, which model is slowest, or how fallback behavior changes during provider incidents.

Where Helicone is stronger than LiteLLM

LiteLLM can handle routing and proxying. Helicone shines when observability is the central requirement. If your team already has routing logic but lacks visibility into LLM usage, Helicone may solve the more urgent problem.

Where LiteLLM may still be better

If observability is secondary and you mainly need a self-hosted proxy, LiteLLM may be more direct. Helicone is strongest when monitoring, debugging, and cost analysis are first-class requirements.

Best fit

Helicone is best for teams that want a gateway and observability layer in one product.

6. Vercel AI Gateway - best for teams building with Vercel and the AI SDK

Vercel AI Gateway is a strong option for teams already building AI applications on Vercel, especially with the Vercel AI SDK.

It provides one API key, access to many models, spend monitoring, load balancing, fallbacks, and compatibility with multiple API formats. For frontend-heavy or full-stack teams already using Vercel, this can be a very natural way to add model routing without introducing a separate gateway product.

Why choose Vercel AI Gateway over LiteLLM?

Choose Vercel AI Gateway if:

• Your app is already deployed on Vercel
• You use the Vercel AI SDK
• You want simple access to many models
• You want spend monitoring
• You need retries, load balancing, and fallbacks
• You want minimal setup for full-stack AI apps
• You prefer platform-native infrastructure

The biggest advantage is developer experience. If your team is already in the Vercel ecosystem, adopting Vercel AI Gateway may require less operational work than deploying LiteLLM.

Where Vercel is stronger than LiteLLM

Vercel AI Gateway is stronger for teams that want AI infrastructure embedded directly into their deployment platform. It reduces the number of separate services to configure and can make experimentation easier.

Where LiteLLM may still be better

LiteLLM is more ecosystem-neutral. If your backend is not built around Vercel, or if you want to self-host your gateway independently, LiteLLM may be a better architectural fit.

Best fit

Vercel AI Gateway is best for teams already using Vercel who want a platform-native AI gateway with minimal setup.

7. OpenRouter - best for model discovery and marketplace-style access

OpenRouter is one of the best-known managed gateways for accessing many AI models through a single API. It is especially useful for developers who want to test models quickly, compare options, and avoid integrating each provider separately.

LiteLLM vs OpenRouter

The litellm vs openrouter comparison is really a comparison between self-hosted proxy control and managed model marketplace access.

LiteLLM gives you a proxy you can run and control. OpenRouter gives you immediate access to many models through one endpoint, with managed routing and provider abstraction.

If your goal is internal infrastructure control, LiteLLM is closer to what you want. If your goal is fast access to a broad model catalog, OpenRouter is usually easier.

Why choose OpenRouter over LiteLLM?

Choose OpenRouter if you want:

• Access to hundreds of models through one API
• Fast model experimentation
• OpenAI SDK compatibility
• Automatic fallbacks
• A marketplace-style experience
• Less setup than self-hosting a proxy
• Easy switching between popular proprietary and open-weight models

OpenRouter is particularly useful for early-stage product teams, indie developers, and AI teams that benchmark many models frequently.

Where OpenRouter is stronger than LiteLLM

OpenRouter is stronger when model access and experimentation speed matter more than owning gateway infrastructure. It abstracts away many provider relationships and lets you move quickly.

Where LiteLLM may still be better

LiteLLM may be better if you need to bring your own provider accounts, enforce custom internal routing rules, control logging, or run the proxy inside your own environment.

Best fit

OpenRouter is best for teams that want fast access to a large model marketplace without operating a gateway.

8. Cloudflare AI Gateway - best for edge-native AI apps and Cloudflare teams

Cloudflare AI Gateway gives developers visibility and control over AI traffic, with analytics, logging, caching, rate limiting, retries, and model fallback.

It is especially compelling for teams already using Cloudflare Workers, Cloudflare’s edge network, or other Cloudflare developer products. If your application already runs close to Cloudflare’s ecosystem, AI Gateway can fit naturally into your infrastructure.

Why choose Cloudflare AI Gateway over LiteLLM?

Choose Cloudflare AI Gateway if you want:

• AI traffic analytics
• Request logging
• Caching
• Rate limiting
• Retries and model fallbacks
• Integration with Cloudflare infrastructure
• Edge-native application patterns
• A managed control layer instead of a self-hosted proxy

For some workloads, caching and rate limiting are more important than complex model routing. Cloudflare is strong when AI traffic management looks like a natural extension of your existing edge and security stack.

Where Cloudflare is stronger than LiteLLM

Cloudflare AI Gateway is stronger when your team already uses Cloudflare and wants to manage AI traffic close to the edge. It is also useful when you need quick analytics, cost visibility, caching, and rate limiting without deploying a separate proxy service.

Where LiteLLM may still be better

LiteLLM is more focused on LLM provider abstraction and self-hosted proxy behavior. If you want a dedicated LLM gateway inside your own infrastructure, LiteLLM or Bifrost may be a better fit.

Best fit

Cloudflare AI Gateway is best for teams building on Cloudflare that want managed AI traffic control, caching, rate limiting, and fallback features.

LiteLLM Proxy Alternatives - Understanding the Difference

LiteLLM can be used in two ways: as a Python SDK or as a proxy server. 

The SDK is used directly inside your application code. It lets developers call different LLM providers without manually integrating each provider one by one. 

The proxy server works differently. It runs as a centralized, OpenAI-compatible gateway between your applications and model providers. In production, when teams search for litellm proxy alternatives, they are usually looking to replace this proxy layer, not just switch to another SDK. 

This distinction matters because a proxy sits directly in the request path. That means it can enforce rules centrally across all services, including:

• Authentication
• Rate limits
• Logging
• Provider routing
• Fallbacks
• Cost controls
• Compliance policies

For example, if five internal services call LLMs, they can all go through the same gateway. This makes governance much easier. With a library-based approach, every service needs to implement the same logic separately, which becomes harder to manage as AI usage grows across teams.

Among the alternatives in this list, Eden AI, Kong AI Gateway, Bifrost, and Cloudflare AI Gateway operate as true gateway or proxy-style layers. They sit between your application and model providers, even if their deployment models are different.

Portkey, Helicone, and OpenRouter also provide gateway-style access, but their positioning is slightly different: Portkey focuses more on observability and governance, Helicone on monitoring and cost visibility, and OpenRouter on model access and discovery.

Vercel AI SDK is different. It is primarily an application library for building AI features in TypeScript and web frameworks. It can work with Vercel AI Gateway, but the SDK itself is not a proxy replacement.

For infrastructure decisions, the key is simple: compare proxy to proxy, not SDK to gateway.

FAQ - LiteLLM Alternatives