Solutions
Inference at scale, without the bill.
Production inference services that hold their own at hundreds of millions of tokens per day. The same models, the same hardware, run faster and priced lower because the runtime is ours.
At scale
What customers in production look like.
Capabilities
Built for production traffic.
20× faster on identical hardware
Speculative decoding, FP8 quantization, kernel fusion. Run the same model and measure for yourself.
Autoscaling with SLO targeting
Set a P99 latency target, set a queue-depth bound, the autoscaler holds both. No manual tuning.
Custom model deployment
Bring your own weights — fine-tunes, full pre-trains, proprietary architectures. Same speed, same SLOs.
Network isolation
VPC interconnect peers your private subnet directly into the inference cluster. No public-internet hop.
Multi-region deployment
Replicate endpoints into US East, US West, EU Central, APAC. Failover between regions inside the same SDK.
Function calling and tools
Structured-output mode, parallel tool calls, JSON-mode with grammar enforcement at the kernel level.
Reference architectures
What these services typically look like.
Real-time assistant
P95 < 500ms. 8K context. Chat-shaped traffic with peaks. Continuous batching, speculative decoding, regional autoscale.
Batch inference
Async queue, 24-hour SLA, throughput-optimized. INT4 quantization, large batch sizes, off-peak scheduling for additional discount.
Long-context analytics
1M-token contexts. Multi-document QA. Legal, code, financial. Sparse attention pattern selected per request, results cached for re-asks.
FAQ
Production questions.#
Send your traffic. Measure the result.
Trial credits cover thousands of dollars of throughput. No commitment.