LLM Gateway vs Postproxy: Which is Better in 2026?
A comprehensive comparison of LLM Gateway and Postproxy 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 a broader feature set (6 features vs 5)
- →You need one openai-compatible endpoint for 200+ models across 40+ providers or real-time cost tracking and spend controls across every provider
Choose Postproxy if:
- →You need one payload mapped to each platform, with per-platform results returned or comments, dms and reviews through the same api as publishing
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LLM Gateway vs Postproxy: At a Glance
Pricing Comparison: LLM Gateway vs Postproxy
Understanding the pricing differences between LLM Gateway and Postproxy is crucial for making the right choice. Here's how their plans compare side by side.
LLM Gateway Pricing
Postproxy Pricing
💡 Pricing takeaway: Both LLM Gateway and Postproxy 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 Postproxy stacks up.
What Makes Each Tool Unique
🔵 Unique to LLM Gateway
Features available in LLM Gateway but not in Postproxy:
- ✓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 Postproxy
Features available in Postproxy but not in LLM Gateway:
- ✓One payload mapped to each platform, with per-platform results returned
- ✓Comments, DMs and reviews through the same API as publishing
- ✓MCP server plus verified n8n, Make and Zapier integrations
- ✓SDKs for Node, Python and Ruby with webhooks and retries
- ✓Separate per-profile and per-profile-group pricing models
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: Postproxy
Postproxy replaces per-platform social integrations with a single API covering publishing, comments, direct messages, reviews and insights across YouTube, X, TikTok, Threads, Pinterest, LinkedIn, Instagram, Facebook, Telegram, Google Business and Bluesky. You send one payload; the service maps it to each platform's rules and returns a per-platform outcome rather than a single opaque success flag, which is the difference between an integration you can debug and one you cannot. The full engagement flow is exposed, not just publishing — replying to comments, answering DMs and managing reviews all run through the same contract, with webhooks, retries and logs behind it. There are official SDKs for Node, Python and Ruby, verified nodes and apps for n8n, Make and Zapier, and an MCP server so an agent in Claude, Cursor or a similar client can drive it directly. The pricing split is the part that shows who it is actually for: one model billed per connected profile for agents and automations, and a separate one billed per profile group for SaaS products and agencies publishing on behalf of clients, with each group covering up to eleven connected platforms. The documentation and integration pages are published per platform rather than as one combined reference, so the specific constraints of each network are visible before you write against them, and Bluesky is listed as coming soon.
Ideal use cases:
- •Teams or individuals who need one payload mapped to each platform, with per-platform results returned
- •Teams or individuals who need comments, dms and reviews through the same api as publishing
- •Teams or individuals who need mcp server plus verified n8n, make and zapier integrations
- •Teams or individuals who need sdks for node, python and ruby with webhooks and retries
- •Anyone focused on social-media workflows
- •Anyone focused on api workflows
🤖 Other AI Agent Infrastructure Tools to Consider
LLM Gateway and Postproxy 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?
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Frequently Asked Questions
Is LLM Gateway better than Postproxy?
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 Postproxy provides 5 features including One payload mapped to each platform, with per-platform results returned and Comments, DMs and reviews through the same API as publishing. LLM Gateway uses a freemium model with a free tier, while Postproxy is freemium with free access available. Choose based on which features and pricing model align with your requirements.
Is LLM Gateway cheaper than Postproxy?
LLM Gateway is cheaper, starting at $0.01/month compared to Postproxy's $17/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 Postproxy together?
Yes, many users combine LLM Gateway and Postproxy in their workflow. LLM Gateway excels at one openai-compatible endpoint for 200+ models across 40+ providers, while Postproxy shines with one payload mapped to each platform, with per-platform results returned. 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 Postproxy?
While both are ai agent infrastructure tools, LLM Gateway emphasizes one openai-compatible endpoint for 200+ models across 40+ providers, whereas Postproxy is known for one payload mapped to each platform, with per-platform results returned. The best choice depends on your specific workflow and feature priorities.
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