Home / Companies / Braintrust / Blog / Post Details
Content Deep Dive

AI gateway comparison: the 6 best ranked (2026)

Blog post from Braintrust

Post Details
Company
Date Published
Author
Braintrust Team
Word Count
2,862
Company Posts That Month
30
Language
English
Hacker News Points
-
Post removed?
No
Summary

An AI gateway acts as a control layer through which all large language model (LLM) traffic passes before reaching a model provider, unifying access controls, quotas, cost tracking, and audit logging across providers. This facilitates production governance and developer routing by offering model routing and a unified API within the same core layer. AI gateways are categorized into infrastructure-first gateways, which extend existing API management systems to AI traffic, and LLM-native gateways, which focus on model access and provider abstraction. Key criteria for selecting an AI gateway include provider and model breadth, rate limiting, access control, governance, caching, cost tracking, audit logging, and actionable observability. Several AI gateways, such as Braintrust, Portkey, LiteLLM, Kong AI Gateway, SUSE AI Universal Proxy, and Cloudflare AI Gateway, offer varying capabilities depending on team needs, from production governance and observability to infrastructure control and edge caching. Braintrust Gateway stands out by integrating routed model requests into the release control process, enhancing evaluation workflows, and offering comprehensive logging and tracing capabilities, making it a preferred choice for teams focusing on production AI applications.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
LLM 23 6,292 1,205 252 -36%
MCP 16 7,755 862 214 0%
Observability 16 4,261 791 201 +16%
Kubernetes 7 2,083 321 111 +3%
Secrets Management 2 2,539 400 136 +9%
Local AI 1 69 40 20 +23%
OpenTelemetry 1 970 179 58 +1%
RAG 1 1,005 263 108 -56%
Use This Data

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.