UnieInfra — agent inference, optimized to the token
UnieInfra is an inference platform tuned for AI agents, not just LLM calls — up to 4× throughput at low load and a fifth of the latency under high load, with automatic parameter tuning that maximizes throughput on the hardware you already have, across AMD, Nvidia, Qualcomm and Intel.
UnieInfra
Scheduler · Kernels · Autotune
Throughput at low load, speeding up AI responses
lower latency under concurrency (TTFT)
GPU memory utilization in production deployments
Accelerator ecosystems: AMD · Nvidia · Qualcomm · Intel
High throughput and low time-to-first-token — at the same time.
Total throughput
higher is betterQwen3.5-122B-A10B (FP16) · Nvidia H200 × 2 · test by InferenceMAX.
concurrency
Throughput vs. time-to-first-token
up & right is betterUnieInfra holds high throughput while collapsing TTFT as concurrency rises.
Why inference decides the economics of agents.
Higher throughput
Up to 2× throughput at low load — faster AI responses.
Lower latency
A fifth of the latency under high load — less waiting.
Automatic parameter tuning
Auto-tunes batching, scheduling and memory to your hardware.
Kernel optimization
Tuned kernels squeeze more out of each accelerator.
Multi-hardware deployment
One engine across AMD, Nvidia, Qualcomm, Intel.
Private deployment
Run inside your data center with full control.
One inference engine across four accelerator ecosystems
Inference that makes agents affordable
When an agent makes many model calls per task, throughput density is what determines cost and scalability. UnieInfra is built for exactly that workload.
- Lower token cost at scale
- Stable under high concurrency
- Runs on the hardware you already have
Token-efficient throughput density means the work of four racks on a stock open-source stack runs on a single rack with UnieInfra.