Wafer

What is Wafer?

Wafer is an enterprise inference platform that provides access to the world's fastest open-source LLMs through serverless and dedicated endpoints. Unlike traditional per-token pricing models, Wafer optimizes GPU kernels for AI inference using autonomous performance engineers, delivering 1.5-3x faster speeds than competing providers. The platform offers three core models: GLM-5.1 for coding and reasoning, Kimi-K2.6 with a 262K context window, and Qwen 3.5 397B-A17B as a flagship mixture-of-experts model. Wafer Pass provides flat-rate API subscription access starting at $10/week, integrating seamlessly with Claude Code, Cline, Kilo Code, and other agentic harnesses.

Key Features

• Fastest Open-Source LLMs

  Serverless inference for top open models optimized with autonomous performance engineers, delivering 25% faster speeds than competitors on benchmarks for models like Qwen 3.5 397B-A17B.

• Pay-As-You-Go Pricing

  Transparent per-token pricing with Input, Output, and Cache rates (Cache typically 10× cheaper), plus automatic cache hits for repeated prompt prefixes without any configuration.

• Dedicated Endpoints

  Mission-critical AI workloads get isolated traffic from shared inference pools with zero data retention, SLA-backed uptime, and custom-tuned deployments in under 24 hours.

• OpenAI-Compatible API

  Serverless endpoints follow the OpenAI Chat Completions schema, so existing clients like OpenAI SDK, LangChain, LiteLLM, Claude Code, and Cline work by swapping base URL and API key.

• Three Core Models

  GLM-5.1 (strong coding/reasoning), Kimi-K2.6 (sparse MoE, 262K context), and Qwen 3.5 397B-A17B (397B total/17B active MoE) with more models rolling out.

Use Cases

• Agentic Coding : Developers use Wafer Pass with Claude Code, OpenClaw, Cline, Kilo Code, Roo Code, OpenHands, or Conductor for rapid development at flat-rate pricing.
• Voice Agents & Copilots : Low-latency responses tailored for voice agents, intelligent copilots, and interactive AI products requiring real-time performance.
• Enterprise Production Workloads : Dedicated endpoints provide predictable uptime and stable performance for production systems with compliance-bound workloads requiring zero data retention.
• Batch Coding Agents : High-throughput scaling for coding agents, batch workloads, and parallel generations without bottlenecks.
• Document-Heavy RAG : Cache savings are largest on long system prompts, multi-turn conversations, and document-heavy RAG where most of the prompt repeats across requests.

FAQs