If you’re building LLM applications at scale, your gateway can’t be the bottleneck. That’s why we built Bifrost, a high-performance, fully self-hosted LLM gateway in Go. It’s 50× faster than LiteLLM, built for speed, reliability, and full control across multiple providers.
Get involved:
The project is fully open-source. Try it, star it, or contribute directly: <a href="https://github.com/maximhq/bifrost" target="_blank" rel="noopener nofollow">https://github.com/maximhq/bifrost</a>
Key Highlights:
<ul>
<li>Ultra-low overhead: ~11µs per request at 5K RPS, scales linearly under high load.</li>
<li>Adaptive load balancing: Distributes requests across providers and keys based on latency, errors, and throughput limits.</li>
<li>Cluster mode resilience: Nodes synchronize in a peer-to-peer network, so failures don’t disrupt routing or lose data.</li>
<li>Drop-in OpenAI-compatible API: Works with existing LLM projects, one endpoint for 250+ models.</li>
<li>Full multi-provider support: OpenAI, Anthropic, AWS Bedrock, Google Vertex, Azure, and more.</li>
<li>Automatic failover: Handles provider failures gracefully with retries and multi-tier fallbacks.</li>
<li>Semantic caching: deduplicates similar requests to reduce repeated inference costs.</li>
<li>Multimodal support: Text, images, audio, speech, transcription; all through a single API.</li>
<li>Observability: Out-of-the-box OpenTelemetry support for observability. Built-in dashboard for quick glances without any complex setup.</li>
<li>Extensible &amp; configurable: Plugin based architecture, Web UI or file-based config.</li>
<li>Governance: SAML support for SSO and Role-based access control and policy enforcement for team collaboration.</li>
</ul>
Benchmarks : Setup: Single t3.medium instance. Mock llm with 1.5 seconds latency
<table>
<thead>
<tr>
<th>Metric</th>
<th>LiteLLM</th>
<th>Bifrost</th>
<th>Improvement</th>
</tr>
</thead>
<tbody>
<tr>
<td>p99 Latency</td>
<td>90.72s</td>
<td>1.68s</td>
<td>~54× faster</td>
</tr>
<tr>
<td>Throughput</td>
<td>44.84 req/sec</td>
<td>424 req/sec</td>
<td>~9.4× higher</td>
</tr>
<tr>
<td>Memory Usage</td>
<td>372MB</td>
<td>120MB</td>
<td>~3× lighter</td>
</tr>
<tr>
<td>Mean Overhead</td>
<td>~500µs</td>
<td>11µs @ 5K RPS</td>
<td>~45× lower</td>
</tr>
</tbody>
</table>
Why it matters:
Bifrost behaves like core infrastructure: minimal overhead, high throughput, multi-provider routing, built-in reliability, and total control. It’s designed for teams building production-grade AI systems who need performance, failover, and observability out of the box.

The official daily.dev AI community. Led by thought leaders and AI experts. Stay tuned for insights, news and discussions. 

Bifrost is an open-source, self-hosted LLM gateway written in Go that claims 50× faster performance than LiteLLM. It provides ultra-low latency (~11µs overhead at 5K RPS), adaptive load balancing across multiple providers (OpenAI, Anthropic, AWS Bedrock, Google Vertex, Azure), automatic failover, semantic caching, and OpenAI-compatible API supporting 250+ models. Features include cluster mode resilience with peer-to-peer synchronization, multimodal support, OpenTelemetry observability, SAML SSO, and role-based access control. Benchmarks show 54× faster p99 latency, 9.4× higher throughput, and 3× lower memory usage compared to LiteLLM on a t3.medium instance.

Bifrost: An LLM Gateway built for enterprise-grade reliability, governance, and scale(50x Faster than LiteLLM)

This benchmark is extremely crazy, Bifrost is extremely fast that it feels impossible to believe.
I have never had a reason to use an LLM gateway but when the reason comes I will make sure I use this your product.
Good luck 🤞