LLM Gateway vs Trigger.dev: Which is Better in 2026?
A comprehensive comparison of LLM Gateway and Trigger.dev covering features, pricing, use cases, and which tool is the right choice for your needs.
⚡ Quick Verdict
Choose LLM Gateway if:
- →You want more affordable paid plans (from $0.01/mo)
- →You need one openai-compatible endpoint for 200+ models across 40+ providers or real-time cost tracking and spend controls across every provider
Choose Trigger.dev if:
- →You need long-running typescript tasks with durable retries and queues or concurrency controls and elastic scaling
ChatGPT already recommends LLM Gateway or Trigger.dev. Does it recommend yours?
If you're building an AI tool, run a free AI-visibility scan on your own product — we ask ChatGPT across 5 prompt angles and score how often you get named. ~30 seconds, no signup, no card.
LLM Gateway vs Trigger.dev: At a Glance
Pricing Comparison: LLM Gateway vs Trigger.dev
Understanding the pricing differences between LLM Gateway and Trigger.dev is crucial for making the right choice. Here's how their plans compare side by side.
LLM Gateway Pricing
Trigger.dev Pricing
💡 Pricing takeaway: Both LLM Gateway and Trigger.dev offer free tiers, making it easy to try before you buy. Compare the specific plans to find the best value for your use case.
Feature-by-Feature Comparison
Here's how every feature from LLM Gateway and Trigger.dev stacks up.
What Makes Each Tool Unique
🔵 Unique to LLM Gateway
Features available in LLM Gateway but not in Trigger.dev:
- ✓One OpenAI-compatible endpoint for 200+ models across 40+ providers
- ✓Real-time cost tracking and spend controls across every provider
- ✓Automatic provider routing plus custom routing rules
- ✓Prompt caching, guardrails and reliability failover
- ✓Bring-your-own-keys on the free tier
- ✓MCP server, AI SDK provider and a token cost calculator
🟣 Unique to Trigger.dev
Features available in Trigger.dev but not in LLM Gateway:
- ✓Long-running TypeScript tasks with durable retries and queues
- ✓Concurrency controls and elastic scaling
- ✓Durable cron scheduling without timeouts
- ✓Realtime streaming from tasks to a frontend
- ✓Official MCP server with agent chat and prompt management
- ✓Open source and self-hostable
Use Case Recommendations
Best for: LLM Gateway
LLM Gateway is an open-source, OpenAI-compatible routing layer that puts one API in front of more than 200 models across 40-plus providers, including OpenAI, Anthropic and Google. The problem it solves is operational rather than intellectual: teams that use several providers end up juggling separate keys, separate dashboards, separate billing and separate SDK quirks, and switching provider for a given model means a code change. Pointing an existing OpenAI-compatible client at the gateway collapses that into one endpoint with real-time cost tracking across all of it. Around the core routing sit the features that make a gateway worth running in production — automatic provider selection and custom routing rules, budgets and spend controls, prompt caching, guardrails, reliability failover, and activity logs with exportable data. The commercial model is unusual and worth reading carefully: the free tier is free forever with all 200+ models available and bring-your-own-keys included, and the platform fee is 5% on credit usage rather than a monthly subscription, so cost scales with spend rather than seats. Metadata retention is free while full payload storage is billed at $0.01 per million tokens. Supporting surfaces include an MCP server, an AI SDK provider, a token cost calculator, model comparison and rankings pages, and the vendor states it is SOC 2 Type II certified.
Ideal use cases:
- •Teams or individuals who need one openai-compatible endpoint for 200+ models across 40+ providers
- •Teams or individuals who need real-time cost tracking and spend controls across every provider
- •Teams or individuals who need automatic provider routing plus custom routing rules
- •Teams or individuals who need prompt caching, guardrails and reliability failover
- •Anyone focused on llm-gateway workflows
- •Anyone focused on api workflows
Best for: Trigger.dev
Trigger.dev is an open-source platform for writing long-running AI agents and background workflows in TypeScript and running them as fully managed infrastructure. The problem it exists to solve is the one every serverless deployment hits the moment an agent gets interesting: a task that needs to run for ten minutes, retry a flaky model call, fan out to a hundred sub-tasks and survive a redeploy does not fit a request-response timeout. Tasks are ordinary TypeScript functions with durable execution around them — retries, queues, concurrency limits and elastic scaling are configuration, not code you write. Scheduled tasks give durable cron without timeouts. Realtime connects a frontend directly to a running task so a UI can stream progress rather than poll. Observability and tracing are first-class, with custom dashboards, log retention and alert destinations tiered by plan. The team ships an official MCP server, which as of the current changelog carries agent chat, prompt management and reports, so the platform is drivable from a coding agent as well as from code. It is genuinely open source and self-hostable, with a documented self-hosting guide, and the cloud plans are a convenience layer over that rather than the only way to run it. Cal.com's booking engine is the reference deployment. The pricing model is credits plus concurrency, which maps cleanly onto how agent workloads actually consume resources.
Ideal use cases:
- •Teams or individuals who need long-running typescript tasks with durable retries and queues
- •Teams or individuals who need concurrency controls and elastic scaling
- •Teams or individuals who need durable cron scheduling without timeouts
- •Teams or individuals who need realtime streaming from tasks to a frontend
- •Anyone focused on typescript workflows
- •Anyone focused on background-jobs workflows
🤖 Other AI Agent Infrastructure Tools to Consider
LLM Gateway and Trigger.dev aren't the only options. Here are other popular tools in the same space:
SuperAGI
Open-source autonomous AI agent framework with visual dashboard — 14K GitHub stars
MetaGPT
Multi-agent AI framework simulating software teams — 45K GitHub stars, builds full apps from prompts
Cerebras
Fastest LLM inference powered by the Wafer Scale Engine.
Scale AI
AI data platform for training data and model evaluation.
Roboflow
End-to-end computer vision platform for developers.
Labelbox
Enterprise data labeling platform for ML training datasets.
Is one of these your tool?
This page ranks for "LLM Gateway vs Trigger.dev" — buyers comparing the two land here, and ChatGPT and Perplexity cite it. Claim your listing for $19 one-time — no subscription, nothing to cancel — and get a Featured badge, top placement in your category, and a permanent dofollow backlink. Prefer it ongoing? Monthly is one click away on the next page.
Frequently Asked Questions
Is LLM Gateway better than Trigger.dev?
It depends on your needs. LLM Gateway offers 6 key features including One OpenAI-compatible endpoint for 200+ models across 40+ providers and Real-time cost tracking and spend controls across every provider, while Trigger.dev provides 6 features including Long-running TypeScript tasks with durable retries and queues and Concurrency controls and elastic scaling. LLM Gateway uses a freemium model with a free tier, while Trigger.dev is freemium with free access available. Choose based on which features and pricing model align with your requirements.
Is LLM Gateway cheaper than Trigger.dev?
LLM Gateway is cheaper, starting at $0.01/month compared to Trigger.dev's $10/month. Both tools offer free tiers, so you can try each before committing. Always check the official websites for the most current pricing.
Can I use LLM Gateway and Trigger.dev together?
Yes, many users combine LLM Gateway and Trigger.dev in their workflow. LLM Gateway excels at one openai-compatible endpoint for 200+ models across 40+ providers, while Trigger.dev shines with long-running typescript tasks with durable retries and queues. Using both allows you to leverage the strengths of each tool, though this means managing two subscriptions — though free tiers can help manage costs.
What's the main difference between LLM Gateway and Trigger.dev?
While both are ai agent infrastructure tools, LLM Gateway emphasizes one openai-compatible endpoint for 200+ models across 40+ providers, whereas Trigger.dev is known for long-running typescript tasks with durable retries and queues. The best choice depends on your specific workflow and feature priorities.
Learn More
📬 Get the best new AI tools delivered weekly
One concise email with fresh launches, trending picks, and featured standouts.