Best LLM Gateway Tools for AI Applications Under $100/Month

If your team is building with more than one LLM provider—and most are—you already know the pain. Each provider ships its own SDK, its own API conventions, its own billing dashboard, and its own rate limits. Swap a model and you're rewriting integration code. Lose a key and your whole pipeline goes dark with no fallback. This is the problem an LLM gateway was built to solve: a smart middle layer between your application and the model providers that unifies routing, cost tracking, caching, failover, and observability behind a single OpenAI-compatible endpoint.2

The good news is that the open-source ecosystem has matured rapidly. Several of the strongest gateway tools are free to self-host, and the managed options that matter comfortably clear the $100/month bar. We evaluated five tools across deployment flexibility, provider coverage, production guardrails, and cost—drawing on buyer's guides and pricing data current to 20261—to find the things actually worth buying (or, in several cases, running for free).

How We Evaluated

Every pick below was assessed against four criteria that matter when you're operating under a $100/month ceiling:

• Provider coverage — How many LLM providers and models can it route to? A gateway that only talks to two vendors barely earns the name.
• Deployment model — Can you self-host it on a $5 VPS, or do you need a managed platform? The answer determines your real monthly cost.
• Production features — Failover, caching, guardrails, observability, PII redaction. The gap between a prototype and a production system lives here.
• Total cost — Software license plus infrastructure. Everything here fits under $100/mo, but some are genuinely $0.

We excluded enterprise-only tiers (Kong Enterprise, TrueFoundry's managed platform) that blow past the budget ceiling, and we included both self-hosted open-source options and managed services where the pricing makes sense for small teams.1

1. LiteLLM — Best Overall

LiteLLM is the most widely-used open-source LLM gateway, and for good reason. It wraps 100+ LLM providers behind a single OpenAI-compatible API, meaning your application code stays the same whether you're calling GPT-4o, Claude, Gemini, or a local model.1 Licensed under MIT, the software itself is free; the only cost is the VPS you run it on, which can be as little as $5/month.

What sets LiteLLM apart is breadth and community. It has the widest provider coverage of any gateway we evaluated, and the largest open-source community—roughly 40,000 GitHub stars as of 2026. That translates to fast updates when new models drop, extensive documentation, and a deep library of provider-specific quirks already worked out.

For teams that want maximum flexibility and don't mind running their own infrastructure, LiteLLM is the clear default. Pair it with a load balancer and you get automatic failover across providers for free.

Specs:

• Deployment: Self-hosted (MIT license)
• Provider coverage: 100+ providers
• Cost: Free software + ~$5/mo VPS

2. Portkey — Best for Production Guardrails

If LiteLLM is the flexibility play, Portkey is the safety play. Its open-source gateway (Apache 2.0) connects to 1,600+ AI models and adds production-grade guardrails that self-hosted LiteLLM doesn't offer out of the box: PII redaction, jailbreak detection, and SOC2/HIPAA compliance on the managed tier.2

Portkey's managed platform starts at $49/month for the production plan, which fits comfortably under our $100 ceiling.1 That gets you the guardrails, prompt management, and observability without standing up your own infrastructure. The free tier is available for smaller workloads.

The trade-off is that Portkey's open-source gateway is newer (the Apache 2.0 release landed in March 2026) and its community is smaller than LiteLLM's. But if your use case involves sensitive data or you need compliance certifications, the guardrail features alone justify choosing Portkey over a bare routing layer.

Specs:

• Deployment: Self-hosted or managed
• Provider coverage: 1,600+ models
• Cost: Free tier; $49/mo managed

3. LibertAI — Best for Privacy-First Inference

LibertAI takes a fundamentally different approach: instead of routing to centralized providers, it offers a decentralized inference API that's compatible with OpenAI and Anthropic formats. You get a drop-in alternative to the big hosted APIs, but inference runs on a distributed network with TEE (Trusted Execution Environment) isolation for privacy.

Pricing is pay-per-use with no vendor lock-in—if you're already calling OpenAI's API, swapping the base URL is most of the migration work. For teams that care about data sovereignty, want to avoid sending prompts through a single corporate intermediary, or are building privacy-sensitive applications, LibertAI is the most interesting option on this list. It fits the budget naturally since you only pay for the tokens you consume.

This is a first-party tool we're recommending on its merits. We earn revenue when developers use LibertAI, but the recommendation stands because decentralized, TEE-isolated inference genuinely fills a gap that the other gateways don't address.

Specs:

• Deployment: Managed (decentralized network)
• Provider coverage: OpenAI/Anthropic-compatible API
• Cost: Pay-per-use

4. LocalAI — Best for Full Data Control

LocalAI is a self-hosted, OpenAI-compatible API server that lets you run LLMs entirely on your own hardware—no GPU required. It's free and open-source, and the zero software cost means your only expense is the machine you run it on.

The use case here is narrow but compelling: if your organization has a strict data-residency policy, or you're operating in an air-gapped environment, LocalAI gives you an OpenAI-compatible interface without any traffic leaving your network. It supports a range of model formats and can run on CPU-only hardware, which keeps infrastructure costs minimal.

LocalAI isn't a gateway in the multi-provider routing sense—it's more of a self-hosted inference endpoint. But for teams whose primary requirement is "no data leaves this building," it's the right tool, and it pairs naturally with a routing layer like LiteLLM if you later need to mix local and remote providers.

Specs:

• Deployment: Self-hosted (local, no GPU needed)
• Provider coverage: OpenAI-compatible (local models)
• Cost: Free / open-source

5. vLLM — Best for High-Throughput Serving

vLLM is a high-throughput LLM serving engine designed for production-grade local hosting. Its key innovations—PagedAttention for efficient memory management and continuous batching for maximizing GPU utilization—make it the performance leader if you're serving your own models at scale.

Like LocalAI, vLLM is free and open-source. But where LocalAI prioritizes ease of setup and CPU compatibility, vLLM is built for raw throughput on GPU hardware. If you're running a high-traffic inference workload and need to squeeze the most tokens per second out of your GPUs, vLLM is the engine you want underneath.

The natural architecture here is vLLM as the inference backend with LiteLLM as the gateway in front—LiteLLM handles routing, caching, and failover, while vLLM handles the actual model serving. Together they cost $0 in software plus whatever you're spending on GPU infrastructure, which can still fit under $100/mo if you're using spot instances or modest hardware.

Specs:

• Deployment: Self-hosted (GPU recommended)
• Provider coverage: Self-hosted models
• Cost: Free / open-source

Comparison at a Glance

The Bottom Line

For most teams, LiteLLM is the starting point—it's free, it covers the most providers, and the community support is unmatched. If you need production guardrails and compliance features, Portkey at $49/month is the upgrade path that stays within budget. LibertAI is the pick for privacy-sensitive workloads that benefit from decentralized, TEE-isolated inference. And if your priority is keeping everything on your own hardware, LocalAI and vLLM cover the CPU and GPU ends of self-hosted serving, respectively.

None of these will set you back more than $100/month, and three of them are free. The real cost is the time you'll spend on integration—but that's a one-time investment that pays off every time you don't have to rewrite your API calls.

Recomate may earn affiliate commissions when you sign up for managed services through links in this article. Self-hosted open-source tools are free regardless of how you find them.

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