# Venice vs Wafer > Wafer tunes inference stacks with agents to run open models faster on the same weights. Venice sells privacy and breadth, with no published speed data. Canonical: https://www.subconscious.dev/compare/venice-vs-wafer · By The Subconscious Team · Updated September 30, 2026 ## How they compare Wafer competes on speed from software. Its agents profile a workload, try batching, decoding, quantization, engine and kernel configs, and deploy the winner, then keep re-tuning on NVIDIA or AMD. Wafer reports its tuned Qwen 3.5 397B running 2.8x faster than stock SGLang, and GLM 5.1 and DeepSeek V4 Pro each 2x faster than a vLLM baseline, all self-reported. Wafer Pass is a flat-rate subscription from $10 a week that covers every hosted model and plugs into Claude Code, Cline and OpenHands. Venice publishes no speed figures and bills per token, from $0.06 in on GLM 4.7 Flash to $1.75 in on GLM 5.3, or through DIEM daily credits. Breadth and privacy favor Venice. It lists 370+ models across text, image, audio and video, proxies closed models, and runs open models under zero retention with TEE options. Wafer's hosted catalog is small and the company is very young. Wafer offers dedicated deployments built around a customer's model, traffic shape and SLO, which Venice does not. Venice lists 1M context on most current models; Wafer's context varies by model. A coding agent that wants big open models at interactive speed for a flat weekly fee fits Wafer. An app that needs private inference across many models and modalities fits Venice. ## What each one does ### Venice Venice is a privacy-focused AI platform founded in 2024 by Erik Voorhees, the crypto entrepreneur behind ShapeShift. It pairs a consumer chat app with a developer API that works as a drop-in replacement for OpenAI's chat endpoint and covers text, image, audio and video across 370+ models. Open models such as GLM 5.3, Kimi K3, DeepSeek V4 and Venice's own uncensored fine-tunes run under a private tier with contract-enforced zero data retention, and some add TEE inference or end-to-end encryption, where only an attested enclave can decrypt the prompt. Closed models from Anthropic, OpenAI and Google are proxied under an anonymized tier that hides user identity but leaves prompt content visible to the upstream provider. ### Wafer 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. Its agents profile a workload, generate candidate configs across batching, decoding, quantization, engines, kernels and hardware, measure each one and deploy the winner. ## Which is best, and when ### Choose Venice for - Broad catalog across four modalities - Zero-retention inference with TEE options - Uncensored models for creative apps ### Choose Wafer for - Flat-rate open models inside coding harnesses - Faster big open models on tuned stacks - Dedicated endpoints built to a latency SLO ## At a glance | Attribute | Venice | Wafer | |---|---|---| | Model access | Open weights, plus proxied closed models | Open weights | | Flagship models | GLM 5.3, Kimi K3, DeepSeek V4 Pro | Qwen 3.5 397B Turbo, GLM 5.1 Turbo | | Speed | - | 2–2.8x vs stock vLLM or SGLang | | Price | $0.06–$12 in, $0.28–$60 out per 1M; DIEM staking | Wafer Pass from $10 a week | | Customization | - | Agent-tuned dedicated deployments | | Deployment | Serverless API, consumer app | Serverless pass, dedicated | | Long context | 1M on most current models | Varies by model | ## FAQ ### What is the difference between Venice and Wafer? Wafer tunes inference stacks with agents to run open models faster on the same weights. Venice sells privacy and breadth, with no published speed data. ### When should I choose Venice over Wafer? Broad catalog across four modalities; Zero-retention inference with TEE options; Uncensored models for creative apps. ### When should I choose Wafer over Venice? Flat-rate open models inside coding harnesses; Faster big open models on tuned stacks; Dedicated endpoints built to a latency SLO. ### Is Venice or Wafer cheaper? Venice: $0.06–$12 in, $0.28–$60 out per 1M; DIEM staking. Wafer: Wafer Pass from $10 a week. The cheaper choice depends on the model and workload. ### Which has more context, Venice or Wafer? Venice: 1M on most current models. Wafer: Varies by model. ## Running long-horizon agents? If your agents run past 200K tokens, compare both against Subconscious: [Subconscious vs Venice](https://www.subconscious.dev/compare/subconscious-vs-venice.md), [Subconscious vs Wafer](https://www.subconscious.dev/compare/subconscious-vs-wafer.md). Full profiles: [Venice](https://www.subconscious.dev/providers/venice.md), [Wafer](https://www.subconscious.dev/providers/wafer.md).