Novita AI vs Wafer

One endpoint for 200+ text, image, audio and video models, callable with existing OpenAI client libraries

Qwen, DeepSeek, GLM, Kimi, MiniMax, Llama, Gemma and Nemotron families served serverlessly with per-token billing

Cache-read pricing published separately from standard input pricing on most chat models

Per-second serverless GPU jobs, on-demand instances, and bare-metal clusters with H100 and H200 hardware

Dedicated deployments for workloads that need reserved capacity rather than shared serverless throughput

Isolated runtimes for agent workloads that call models and execute tools, billed per second

Pay-as-you-go API access to hosted open-source models including GLM, Kimi, Qwen, and DeepSeek with no infrastructure management

Custom-tuned inference deployments with performance guarantees, provisioned in under 24 hours

Agents profile inference bottlenecks and tune across serving engines (vLLM, SGLang, TensorRT-LLM), custom kernels (CUDA, HIP, Triton, NKI), quantization (FP8/FP4), and decode strategies

Workloads run on NVIDIA B200/B300, AMD MI350X/MI355X, and AWS Trainium depending on the model and traffic shape

OpenAI-compatible endpoint at pass.wafer.ai/v1 and Anthropic-compatible endpoint at pass.wafer.ai/v1/messages, both using Bearer token authentication

Cached input tokens are billed at reduced rates on supported models