Wafer provides serverless and dedicated inference for high-performance open-source LLMs.
Product memo
Enterprises needing fast, open-source LLM inference turn to Wafer for serverless and dedicated endpoints. It delivers low-latency, high-throughput inference for critical AI applications. This focus on performance and open-source models appeals to companies with sensitive workloads that avoid generic public APIs.
For who
Enterprises needing fast, open-source LLM inference
Solves what
Provides serverless and dedicated inference for high-performance open-source LLMs.
- Serverless LLM inference
- Dedicated enterprise endpoints
- Optimized inference performance
In their own words
The fastest open source LLMs for enterprise
Serverless and dedicated inference for the world’s fastest open-source LLMs
Commercial cues
Model
usage based
Free tier
No
Trial
No
Pricing Strategy
- • Usage-based pricing scales costs directly with token consumption.
- • Lower cache pricing rewards repeated prompts, cutting operational spend.
Operator context
Founded
Dec 2025
Platform
API
Audience
Developers
Public footprint
+1 more footprint links
Tech stack
Builder Strategy
- Strategy Type
- Niche Specialist
- Stage
- Vc Growth
- Effort
- Small Team
About wafer Expand
Wafer provides specialized LLM inference for enterprises, focusing on high-performance open-source models. It offers both serverless and dedicated inference endpoints, ensuring low latency and high throughput for critical AI applications.
This targets companies that require specific performance and control over their AI workloads, often for sensitive data or mission-critical tasks where generic API providers fall short. By supporting specific open-source LLMs like GLM-5.1, Kimi-K2.6, and Qwen 3.5, Wafer carves out a niche for organizations committed to open-source flexibility without sacrificing enterprise-grade speed and reliability.