LLM Gateway

Best LLM Gateways in 2025: Features, Benchmarks, and Builder's Guide

Best LLM Gateways in 2025: Features, Benchmarks, and Builder's Guide
Best LLM Gateways in 2025: Features, Benchmarks, and Builder's Guide
TL;DRLLM gateways unify provider APIs, add failover and load balancing, enforce budgets, and give you observability.Your evaluation should focus on reliability, performance, governance, deployment model, and developer experience.Bifrost stands out for low overhead, automatic fallbacks, virtual keys with budgets, OpenTelemetry, VPC deployment, and an open-source core you can run anywhere.

What Is an LLM Gateway

An LLM gateway is a routing and control layer that sits between your apps and model providers. It:

  • Normalizes request and response formats through a single unified API.
  • Adds reliability features like automatic failover and load balancing.
  • Centralizes governance for auth, RBAC, budgets, and audit trails.
  • Provides observability with tracing, logs, metrics, and cost analytics.
  • Reduces cost with features like budgets, rate limits, or caching; and may reduce latency when semantic caching is available
  • Some gateways simplify migrations with OpenAI-compatible APIs that act as drop-in replacements for common SDKs.

If you run production AI, you want this layer. It keeps you moving while providers change things under your feet.

How to Evaluate an LLM Gateway

Use this checklist when you test gateways in staging. Make vendors prove it.

  • Core API and Compatibility
    • OpenAI-compatible API for drop-in migration.
    • Coverage across major providers and support for custom or on-prem models.
  • Reliability and Performance
    • Automatic provider fallback and retries.
    • Load balancing across weighted keys and accounts.
    • Low added overhead at high RPS with stable tail latency.
    • Published benchmarks or performance data where available.
  • Governance and Security
    • Virtual keys with budgets and rate limits.
    • SSO, RBAC, audit logs, and enforcement, depending on the gateway
    • Secret management integrations vary; some support Vault or cloud secret stores, others rely on environment variables or plugins.
    • VPC or in-VPC deployment options.
  • Observability and Cost Control
    • Prefer gateways with OpenTelemetry, metrics, and structured logs; though support varies significantly between vendors
    • Cost analytics by team, project, and model.
    • Alerts to Slack, PagerDuty, email, and webhooks.
  • Developer Experience
    • Zero-config startup for local testing.
    • Web UI plus API and file-based configuration.
    • Clear migration guides and SDK examples.
    • Extensible plugin or middleware system.
  • Extensibility and Scale
    • Model Context Protocol to connect tools and data sources.
    • Semantic caching to reduce cost and speed up responses.
    • Cluster mode for high availability and scale out.

The Short List: Gateways You Should Know

Comparison Table

Note: The table summarizes capabilities at a high level based on public materials and may evolve.

Capability Bifrost Portkey Cloudflare AI Gateway LiteLLM Kong or Tyk Class
Unified API Across Providers Yes Yes Partial (Cloudflare-hosted models only) Yes Via plugins or config
Automatic Provider Fallback Yes Yes No (no multi-provider routing) Yes Requires custom logic or plugins
Load Balancing Across Keys Yes Yes No (Cloudflare-managed routing only) Basic weighted routing Yes with config
OpenTelemetry and Metrics Yes Prometheus & basic tracing Limited (analytics only, no full OTEL) Basic Yes with plugins
Virtual Keys and Budgets Yes Usage limits (virtual keys deprecated) No Limited Policy-dependent
Secret Management Integrations Vault & cloud secret managers BYOK key management Cloudflare native Env vars & patterns Yes
VPC or In-VPC Deployment Yes (AWS/GCP/Azure/self-host) Hybrid & self-host options Cloudflare edge only Self-hosted possible Yes
Cluster Mode and HA Yes Managed scaling Global edge (Cloudflare-managed) Self-hosted scaling Yes
MCP Integration Yes Yes N/A N/A N/A
Semantic Caching Yes Yes Yes Basic caching Via plugins or custom logic

Deep Dive: Bifrost by Maxim

Bifrost is an open-source LLM gateway that focuses on performance, reliability, and enterprise-grade control. It runs locally, in containers, or inside your VPC.

Why Teams Pick Bifrost

  • Fast Path Performance
    In Bifrost’s published benchmarks on a t3.xlarge, overhead is ~11 µs per request at 5k RPS. See the performance section on the site and in the README for numbers and setup.
  • Reliability and Failover
    Weighted key selection, adaptive load balancing, and automatic provider fallback keep services stable during throttling and provider hiccups.
  • Unified Interface and Drop-in Replacement
    Use an OpenAI-compatible API. Migration is usually a one-line base URL change for OpenAI, Anthropic, and Google GenAI SDKs.
  • Governance and Cost Control
    Virtual keys per team or customer. Budgets, rate limits, SSO, RBAC, audit logs, and log export.
  • Observability Built In
    OpenTelemetry support, distributed tracing, logs, and Prometheus metrics. A built-in UI for quick checks.
  • Enterprise Deployment Options
    VPC deployment on AWS, GCP, Azure, and self-hosted environments. Secret management via HashiCorp Vault, AWS Secrets Manager, Google Secret Manager, and Azure Key Vault.
  • Extensibility
    Plugin framework for governance, logging, semantic caching, telemetry, and custom logic. Model Context Protocol support to connect tools, filesystems, and data sources safely.

Quick Start

Local and Docker:

npx -y @maximhq/bifrost

# or
docker run -p 8080:8080 maximhq/bifrost

Open http://localhost:8080 to use the web UI and send your first request.

Drop-in Replacement Examples

Point your SDKs to Bifrost. Keep your existing code.

See the Integration Guides for code snippets across Python, Node, and Go.

Performance Profile

  • Gateway overhead: the README reports 11 µs added latency per request at 5k RPS on t3.xlarge with 100 percent success.
  • Site benchmarks show comparative P99 latency, memory usage, and throughput under load. Use these as references when building your own tests.
  • Performance page: getmaxim.ai/bifrost
  • GitHub Performance Analysis: see linked docs and README in the repo

Enterprise Features

  • Governance and Budgeting
    Virtual keys, quotas, SSO, RBAC, budgets and audit logs.
  • Adaptive Load Balancing and Fallback
    Keep latency predictable when a provider slows down.
  • Cluster Mode
    Multi-node, high availability setup for production scale.
  • Alerts and Exports
    Alerts to Slack, PagerDuty, Teams, email, and webhooks. Log exports for compliance and analytics.
  • VPC Deployment and Secrets
    Run inside your cloud with strong secret management and audit trails.

Talk to the team: Schedule a demo

How Other Gateways Fit

  • Portkey AI Gateway
    Unified API, monitoring, and cost control features in a managed setup. Fits teams that want a managed layer with developer tooling. Docs: portkey.ai/docs
  • Cloudflare AI Gateway
    Network-native approach for caching, retries, and analytics. A good fit if your edge is already standardized on Cloudflare. Docs: developers.cloudflare.com/ai-gateway
  • LiteLLM
    A practical layer to unify calls across providers. Good for quick unification and basic routing. Validate behavior at higher RPS if you plan to scale. Docs: docs.litellm.ai
  • Kong, IBM API Connect, GitLab, Tyk
    If your org already runs a general-purpose API gateway, you can extend it to manage LLM traffic with plugins and policies. Expect more work to match LLM-specific features like semantic caching or MCP unless provided by vendor plugins.
    Docs:

Example Deployment Patterns

  • Prototype Locally
    Start with NPX or Docker. Point your OpenAI SDK to the local gateway. Validate routes, budgets, and UI flows.
  • Staging in Shared Cloud
    Deploy Bifrost to your staging cluster or VM. Store provider keys in a secret manager. Enable virtual keys and per-team budgets. Wire OpenTelemetry, Prometheus, and log exports.
  • Production in VPC with HA
    Run cluster mode across zones for high availability. Configure provider fallback and adaptive load balancing. Enforce SSO, RBAC, audit logs, and alerts. Stream logs to your SIEM.

Docs for clustering, governance, and VPC patterns: docs.getbifrost.ai

Practical Tips Before You Decide

  • Reproduce Numbers in Your Environment
    Test with your models, context sizes, providers, and concurrency. Measure P50, P95, P99, and error rates.
  • Test Incident Behavior
    Throttle keys. Change regions. Inject timeouts. Verify how fallbacks and retries behave under pressure.
  • Wire Budgets Early
    Use virtual keys per team with budgets and alerts. Avoid surprise invoices.
  • Trace Everything
    Turn on OpenTelemetry from day one. Without traces and logs, you are guessing.
  • Plan for Drift
    Providers deprecate models and rename endpoints. Make sure your gateway handles catalogs and route updates cleanly.

FAQ

  • What Is an LLM Gateway
    An LLM gateway is a control and routing layer that normalizes provider APIs, adds failover and load balancing, enforces budgets and policies, and provides observability across models and vendors.
  • How Do Gateways Improve Reliability
    Some gateways retry transient failures, perform provider fallback, and balance traffic across keys and regions depending on feature support to control tail latency.
  • Can I Migrate Without Rewriting Code
    Yes. Use an OpenAI-compatible base URL and keep your SDKs. See Bifrost’s drop-in replacement patterns and code snippets in the docs.
  • How Do I Control Costs
    Create virtual keys per team or customer. Set budgets, rate limits, and alerts. Review cost analytics by model and route.
  • Should I Self-Host or Use Managed
    If you need strict data controls, VPC deployment and self-hosting are the safer path. If you want speed and less ops, a managed gateway can be enough. Always test incident behavior and cost guardrails.

Selection Checklist for Product Managers

  • Integration
    • OpenAI-compatible API and drop-in for your SDKs.
    • Coverage for providers you use today and plan to use next.
  • Reliability
    • Automatic fallback between providers and regions.
    • Stable P99 under your target RPS.
  • Governance and Compliance
    • SSO, RBAC, audit logs.
    • Virtual keys and budgets per team or customer.
    • Secret management integrations and data residency options.
  • Observability
    • OpenTelemetry, logs, metrics, and alerts.
    • Cost analytics and export options.
  • Deployment
    • VPC deployment guides and cluster mode.
    • Backup, recovery, and HA patterns.
    • Clear SLOs and runbooks.
  • Vendor Openness
    • Open-source core or transparent docs.
    • Reproducible benchmarks.
    • Clear roadmap and support options.

How a Gateway Fits with Evaluation and Observability

A gateway is one piece of a reliable AI stack. Pair it with evaluation, tracing, and monitoring to move faster without breaking production.

Maxim’s platform integrates with Bifrost so teams can design tests, simulate traffic, observe production behavior, and maintain quality as models and prompts evolve.

Summary and Next Steps

A great LLM gateway fades into the background. It keeps your apps up when providers wobble, controls tail latency with routing and fallback, and puts budgets and rate limits on cost. Among current choices, Bifrost stands out for low overhead, strong reliability features, enterprise controls, and an open-source foundation you can run in your own environment.

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Best TrueFoundry Alternative in 2025: Why Bifrost is the Superior AI Gateway

Best TrueFoundry Alternative in 2025: Why Bifrost is the Superior AI Gateway

TL;DR * TrueFoundry is a comprehensive MLOps platform with AI gateway as one component among training, deployment, and infrastructure management capabilities * Bifrost is a purpose-built AI gateway designed exclusively for high-performance model access, routing, and management * Zero-config deployment: Bifrost starts in seconds without complex Kubernetes setup or infrastructure management * Performance-first
Kamya Shah