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Novita AI vs Wafer
Novita competes on price and catalog breadth. Wafer competes on speed from agent-tuned stacks. Cheap and wide against fast and narrow.
By The Subconscious Team · Updated
Novita AI vs Wafer: key differences
Novita and Wafer both host open models, with different promises. Novita's is breadth and price: 200+ models across modalities, LLMs from $0.02 per million and batch at half off. Wafer's is speed on the same weights. Its AI agents tune batching, decoding, quantization and kernels per workload, and Wafer reports its Qwen 3.5 397B running 2.8x faster than stock SGLang, with GLM 5.1 and DeepSeek V4 Pro each 2x faster than vLLM. Those are Wafer's own numbers against stock baselines, and Wafer is very young with a small hosted catalog.
Pricing models differ. Novita bills per token or per GPU hour. Wafer Serverless bills per token from prepaid credits and plugs into Claude Code, Cline and OpenHands. For dedicated work, Wafer builds deployments around a customer's SLO and keeps re-tuning them on NVIDIA or AMD, while Novita offers dedicated endpoints for any Hugging Face model with LoRA hot swapping at a 99.5% SLA. Heavy agentic coding users may prefer Wafer's tuned speed; everything else fits Novita's catalog.
What Novita AI and Wafer do
Novita AI
Novita AI is a San Francisco inference cloud founded in late 2023 by Frank Lewis and Junyu Huang, and it competes on price and breadth. Its serverless API covers 200+ open models across LLMs, image, video, speech, voice cloning and embeddings, with LLM prices starting at $0.02 per million tokens. The API speaks both OpenAI and Anthropic formats. It became an official Hugging Face Inference Partner in April 2026 and was the day-zero launch partner for Google's Gemma 4.
Example models: DeepSeek V4 Pro, Gemma 4
Full Novita AI profileWafer
Wafer builds AI agents that act as GPU performance engineers, then sells inference on the stacks those agents tune. The company came out of Y Combinator's Summer 2025 batch as a "Cursor for CUDA" that turned slow PyTorch into custom kernels. Founders Emilio Andere and Steven Arellano are based in San Francisco. Wafer raised a $4M seed led by Fifty Years in April 2026 and a $40M Series A co-led by Marathon and Chemistry in September 2026 at a $220M post-money valuation, with AMD Ventures and Wing joining. Its agents profile a workload, generate candidate configs across batching, decoding, quantization, engines, kernels and hardware, measure each one and deploy the winner.
Example models: GLM-5.3, DeepSeek V4.1 Flash
Full Wafer profileShould you choose Novita AI or Wafer?
Novita AI vs Wafer at a glance
| Attribute | Novita AI | Wafer |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | DeepSeek V4 Pro, Gemma 4 | GLM-5.3, DeepSeek V4.1 Flash |
| Speed | ~36 tok/s on DeepSeek V4 Pro | ~168 tok/s on GLM-5.3; 2–2.8x vs stock vLLM or SGLang (vendor) |
| Price | From $0.02 per 1M; batch 50% off | Per token, prepaid credits |
| Customization | Hot-swappable LoRA adapters | Agent-tuned dedicated deployments |
| Deployment | Serverless, GPU cloud, dedicated | Serverless, dedicated |
| Long context | Full 1M on DeepSeek V4 Pro | Up to 1M (GLM-5.3, DeepSeek V4.1 Flash) |
Frequently asked questions
What is the difference between Novita AI and Wafer?
Novita competes on price and catalog breadth. Wafer competes on speed from agent-tuned stacks. Cheap and wide against fast and narrow.
When should I choose Novita AI over Wafer?
Wide model choice across text, image and speech; Pay-per-token billing with batch discounts; Hugging Face models with hot-swappable LoRAs.
When should I choose Wafer over Novita AI?
Fast open models in agent harnesses; Interactive speed on large open models; Dedicated endpoints tuned to a latency SLO.
Is Novita AI or Wafer cheaper?
Novita AI: From $0.02 per 1M; batch 50% off. Wafer: Per token, prepaid credits. The cheaper choice depends on the model and workload.
Which has more context, Novita AI or Wafer?
Novita AI: Full 1M on DeepSeek V4 Pro. Wafer: Up to 1M (GLM-5.3, DeepSeek V4.1 Flash).
Related comparisons
Running long-horizon agents?
If your agents run past 200K tokens, compare both against Subconscious. Our inference stack treats a long-horizon trace as the primary workload, so speed, cost, and accuracy hold up deep into the trace.