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OpenAI vs Wafer
OpenAI's closed GPT API against Wafer, a young host that tunes open models with agents. Wafer offers flat-rate coding access; OpenAI offers frontier models and scale.
By The Subconscious Team · Updated
OpenAI vs Wafer: key differences
Wafer and OpenAI sell very different things to coding teams. OpenAI charges per token for GPT-6 Astra and the GPT-5.6 family, with a 1.05M window and Fast mode at double the price for up to 2.5x speed. Wafer sells open models on inference stacks its own agents tune, and its serverless Wafer Pass is a flat-rate subscription from $10 a week that covers every hosted model and drops into Claude Code, Cline and OpenHands. Wafer reports its tuned Qwen 3.5 397B running 2.8x faster than stock SGLang, a self-reported figure against a stock baseline.
For dedicated work, Wafer builds a deployment around a customer's model, traffic shape and SLO, then keeps re-tuning on NVIDIA or AMD as conditions change. That suits teams with a strict latency target and no kernel engineers. OpenAI's listing has no equivalent service for customer models, but it has a far larger ecosystem and closed frontier models, while Wafer is a very young company with a small catalog. A developer who wants cheap, fast open models in an agent harness can try Wafer Pass. A business product that needs frontier quality stays on OpenAI.
What OpenAI and Wafer do
OpenAI
OpenAI runs the most widely adopted closed-model API. Its September 2026 lineup has GPT-6 Astra at the top for computer use, coding and long agentic runs, priced at $10 in and $50 out per million tokens. Below it sits the GPT-5.6 family: Sol for hard professional work, Terra as the balanced default, and Luna for high-volume jobs at $0.20 in and $1.20 out. All of them carry a 1.05M token context window with up to 128K output.
Example models: GPT-6 Astra, GPT-5.6 Terra
Full OpenAI 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. 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: Qwen 3.5 397B Turbo, GLM 5.1 Turbo
Full Wafer profileShould you choose OpenAI or Wafer?
OpenAI
Choose OpenAI for
- GPT-6 Astra for the hardest coding and computer-use work
- Products that need a mature vendor and large ecosystem
- Usage-based billing across many tiers
Wafer
Choose Wafer for
- Flat-rate open-model access inside agent harnesses
- Dedicated endpoints with a strict latency SLO
- Teams hedging GPU supply across NVIDIA and AMD
OpenAI vs Wafer at a glance
| Attribute | OpenAI | Wafer |
|---|---|---|
| Model access | Closed, plus open gpt-oss | Open weights |
| Flagship models | GPT-6 Astra, GPT-5.6 Sol, Terra, Luna | Qwen 3.5 397B Turbo, GLM 5.1 Turbo |
| Speed | Fast mode: up to 2.5x at 2x price | 2–2.8x vs stock vLLM or SGLang |
| Price | $0.20–$10 in, $1.20–$50 out per 1M | Wafer Pass from $10 a week |
| Customization | N/A | Agent-tuned dedicated deployments |
| Deployment | API, Azure OpenAI, Bedrock | Serverless pass, dedicated |
| Long context | 1.05M; 2x input past 272K | Varies by model |
Frequently asked questions
What is the difference between OpenAI and Wafer?
OpenAI's closed GPT API against Wafer, a young host that tunes open models with agents. Wafer offers flat-rate coding access; OpenAI offers frontier models and scale.
When should I choose OpenAI over Wafer?
GPT-6 Astra for the hardest coding and computer-use work; Products that need a mature vendor and large ecosystem; Usage-based billing across many tiers.
When should I choose Wafer over OpenAI?
Flat-rate open-model access inside agent harnesses; Dedicated endpoints with a strict latency SLO; Teams hedging GPU supply across NVIDIA and AMD.
Is OpenAI or Wafer cheaper?
OpenAI: $0.20–$10 in, $1.20–$50 out per 1M. Wafer: Wafer Pass from $10 a week. The cheaper choice depends on the model and workload.
Which has more context, OpenAI or Wafer?
OpenAI: 1.05M; 2x input past 272K. Wafer: Varies by model.
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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.