Development & Code

Baseten

Models to production fast

88 views

Visit baseten.co

ComfyUI workflows plug straight into Baseten. Deploy across any cloud provider you want. Custom VPCs work too. No wrestling with infrastructure quirks. Baseten handles cross-cloud deployment and keeps 99.99% uptime.

ML engineers at scaling startups — this inference platform actually performs. It deploys AI models in production with purpose-built infrastructure. Pre-optimized Model APIs let you test ideas quickly. Then commit to full deployment when ready.

Baseten's Inference Stack packs custom kernels and advanced caching. Cold starts happen fast. Real-time audio streaming works for AI phone calls and voice agents without the usual headaches.

Your embedding service is choking under load and costing too much? Baseten Embeddings Inference delivers 2x higher throughput. 10% lower latency compared to competitors. GPU usage improves 6x with Baseten Chains for compound AI systems.

Forward Deployed Engineers provide hands-on support from prototype to production. They'll optimize performance for your specific use case rather than giving generic advice. Single-tenant and self-hosted options exist if shared infrastructure won't work.

Training capabilities include one-click deployment to inference-optimized infrastructure. Baseten raised $300M Series E funding and hit a $5B valuation. They're not going anywhere soon. Dedicated inference handles high-scale workloads without performance drops you'd expect from shared systems.

Frequently asked

7 questions

How much faster are Baseten's cold starts compared to other platforms?

Baseten doesn't give exact cold start times -- but they say their custom kernels and advanced caching make things happen fast. Their infrastructure's pre-optimized for quick model startup. This really matters when you've got intermittent traffic and models keep spinning down between requests.

What's the difference between Baseten's Model APIs and full deployment?

Model APIs let you test AI models quickly without the full infrastructure commitment. It's like a sandbox for experimenting. When you're ready for production scale, you can deploy that same model with dedicated resources -- plus custom optimization from their Forward Deployed Engineers.

Can Baseten handle real-time voice applications without audio lag?

Yeah, Baseten specifically supports real-time audio streaming for AI phone calls and voice agents. Their infrastructure eliminates those usual latency headaches that mess up voice AI. No more awkward pauses in conversational AI.

How does Baseten Chains improve GPU efficiency for complex AI workflows?

Baseten Chains optimizes compound AI systems where multiple models work together. They claim 6x better GPU usage compared to running separate model instances. This is huge when you're chaining different AI models together -- like retrieval systems feeding into language models.

What kind of hands-on support do Baseten's Forward Deployed Engineers provide?

Forward Deployed Engineers work directly on your specific use case (not generic advice). They'll optimize performance from prototype through production deployment. This isn't just docs and tutorials -- it's actual engineering support tailored to your models and traffic patterns.

Does Baseten work with private cloud setups and custom VPCs?

Yes, Baseten supports custom VPCs and can deploy across any cloud provider you choose. They also offer single-tenant and self-hosted options if shared infrastructure doesn't meet your security requirements. This flexibility's crucial for enterprises with strict data governance policies.

How much better is Baseten Embeddings compared to other embedding services?

Baseten claims 2x higher throughput and 10% lower latency for embeddings compared to competitors. These improvements come from their optimized inference stack. If your current embedding service is struggling with cost or performance under load -- these gains could significantly reduce both latency and infrastructure costs.