LLM Gateway vs Wire: Which is Better in 2026?
A comprehensive comparison of LLM Gateway and Wire 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 Wire if:
- →You need one link connects any mcp client to a shared context container or per-container database, mcp server and api with scoped permissions
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LLM Gateway vs Wire: At a Glance
Pricing Comparison: LLM Gateway vs Wire
Understanding the pricing differences between LLM Gateway and Wire is crucial for making the right choice. Here's how their plans compare side by side.
LLM Gateway Pricing
Wire Pricing
💡 Pricing takeaway: Both LLM Gateway and Wire 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 Wire stacks up.
What Makes Each Tool Unique
🔵 Unique to LLM Gateway
Features available in LLM Gateway but not in Wire:
- ✓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 Wire
Features available in Wire but not in LLM Gateway:
- ✓One link connects any MCP client to a shared context container
- ✓Per-container database, MCP server and API with scoped permissions
- ✓Agents write entries directly via wire_write, not just file upload
- ✓Container-per-user model for agent products and agencies
- ✓No feature gates — unlimited containers and members on every plan
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: Wire
Wire is shared context storage for AI agents, summarized by its own line: code has GitHub, everything else has Wire. You create a container, put documents, data and notes into it, and connect Claude, Codex or any other MCP client with a single link, so every agent you work with reads and writes to the same place instead of each one starting from an empty context window. Content gets in three ways — direct file upload of PDFs, CSVs, DOCX and Markdown; agents writing entries themselves through wire_write; or a REST API and connectors pushing on a schedule. Each container is an isolated, permissioned environment with its own database, MCP server and API endpoint, so you can spin one up per person, team, project or customer and scope each connected agent to only what it needs. The use cases the vendor targets are more interesting than personal note storage: agent product builders who want every end user to get their own container without building that layer themselves, AI agencies shipping client agents without rebuilding context infrastructure per engagement, and public distribution — publishing a container so any agent can learn about your product through MCP. The recurring technical argument is retrieval over reload: agents that pull the slice they need from a container spend fewer tokens and reach past their context window, rather than re-ingesting a corpus every session.
Ideal use cases:
- •Teams or individuals who need one link connects any mcp client to a shared context container
- •Teams or individuals who need per-container database, mcp server and api with scoped permissions
- •Teams or individuals who need agents write entries directly via wire_write, not just file upload
- •Teams or individuals who need container-per-user model for agent products and agencies
- •Anyone focused on mcp workflows
- •Anyone focused on ai-agents workflows
🤖 Other AI Agent Infrastructure Tools to Consider
LLM Gateway and Wire 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 Wire?
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 Wire provides 5 features including One link connects any MCP client to a shared context container and Per-container database, MCP server and API with scoped permissions. LLM Gateway uses a freemium model with a free tier, while Wire is freemium with free access available. Choose based on which features and pricing model align with your requirements.
Is LLM Gateway cheaper than Wire?
LLM Gateway is cheaper, starting at $0.01/month compared to Wire's $20/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 Wire together?
Yes, many users combine LLM Gateway and Wire in their workflow. LLM Gateway excels at one openai-compatible endpoint for 200+ models across 40+ providers, while Wire shines with one link connects any mcp client to a shared context container. 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 Wire?
While both are ai agent infrastructure tools, LLM Gateway emphasizes one openai-compatible endpoint for 200+ models across 40+ providers, whereas Wire is known for one link connects any mcp client to a shared context container. The best choice depends on your specific workflow and feature priorities.
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