Serve more tokens.
Spend less per workload.
Lower AI infrastructure costs without changing your GPUs.
Built for AI infrastructure companies who need more performance per GPU
Openai GPT OSS 120B
+24% tok/s | 19% Cost ↓
Multi-GPU (753B)
+27% tok/s | 21% Cost ↓
Qwen3-235B-A22B
+138% tok/s | 58% Cost ↓
Nova AI Engine delivers higher throughput at lower GPU cost, proven on the models you already run.
Configure your workload, optimize your stack, and validate performance gains against your baseline.
GPU Kernels
Optimize GPU operations to reduce execution time and improve hardware utilization.
Serving Configuration
Tune batching, concurrency, and runtime settings for your workload and performance targets.
KV Cache Optimization
Improve cache efficiency to reduce memory pressure and support more concurrent requests.
Speculative Decoding
Accelerate token generation by drafting candidate tokens and verifying them with the target model.
Quantization
Use lower-precision representations to reduce memory requirements, with quality checks against your baseline.
Graph Optimization
Streamline the execution graph to reduce redundant operations and runtime overhead.
Nova Inference
Deploy optimized inference for public, private, or fine-tuned models without rebuilding your serving stack.
Optimized vLLM and SGLang deployments
Higher throughput and lower cost per request
OpenAI-compatible API configuration
Re-optimization as workloads and infrastructure evolve
Nova Training
Run supervised fine-tuning and LoRA jobs using optimized training configurations on customer-provided or provisioned GPU infrastructure.
Supervised fine-tuning and LoRA
Lower training time and GPU cost
Training metrics, checkpoints, and performance reporting
Dataset validation and training configuration
READY FOR PRODUCTION