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Z.ai vs Wafer
Wafer serves a tuned GLM 5.1 it says runs 2x faster than stock vLLM; Z.ai serves the newer GLM-5.3 on an $18 monthly plan. Speed and location versus price and recency.
By The Subconscious Team · Updated
Z.ai vs Wafer: key differences
GLM sits on both menus. Wafer lists GLM 5.1 Turbo among its hosted models and reports GLM 5.1 running 2x faster than a vLLM baseline on its agent-tuned stack, a self-reported comparison against stock software. Z.ai, the lab that makes GLM, serves the newer GLM-5.3 at $1.40 in and $4.40 out. Both sell flat-rate access for coding tools. Wafer Pass starts at $10 a week and covers every hosted model in Claude Code, Cline and OpenHands. The GLM Coding Plan starts at $18 a month on the Lite tier and runs Claude Code through an Anthropic-compatible endpoint.
The choice comes down to model generation, speed and location. Z.ai gets new GLM versions first and prices them low, but its servers sit mostly in China, adding 100 to 200ms from the US or Europe, and quota burns faster during Beijing peak hours. Wafer tunes for speed and runs on NVIDIA or AMD, but it is a very young company with a small catalog. Wafer also builds dedicated deployments around a customer's model and SLO, which could suit a team that fine-tunes MIT-licensed GLM weights and needs them fast.
What Z.ai and Wafer do
Z.ai
Z.AI is the international brand of Chinese lab Zhipu AI, maker of the GLM models. Its current flagship, GLM-5.3, shipped August 17, 2026 at $1.40 in and $4.40 out per million tokens, with cached input at $0.26. GLM-5.3-Flash costs $0.075 in and $0.25 out, and several older Flash models are priced at zero, a real free tier instead of trial credits. GLM-5, released in February 2026, is a 744B mixture-of-experts model under an MIT license, and at launch it ranked first among open-weight models on the Artificial Analysis index with a record-low hallucination score.
Example models: GLM-5.3, GLM-5.3-Flash
Full Z.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. 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 Z.ai or Wafer?
Z.ai vs Wafer at a glance
| Attribute | Z.ai | Wafer |
|---|---|---|
| Model access | Open weights (MIT) | Open weights |
| Flagship models | GLM-5.3, GLM-5.3-Flash | Qwen 3.5 397B Turbo, GLM 5.1 Turbo |
| Speed | ~80 tok/s on GLM-5.3 | 2–2.8x vs stock vLLM or SGLang |
| Price | $1.40 in, $4.40 out (GLM-5.3); free Flash tier | Wafer Pass from $10 a week |
| Customization | Open weights, no license limits | Agent-tuned dedicated deployments |
| Deployment | API, GLM Coding Plan | Serverless pass, dedicated |
| Long context | 1M (GLM-5.3) | Varies by model |
Frequently asked questions
What is the difference between Z.ai and Wafer?
Wafer serves a tuned GLM 5.1 it says runs 2x faster than stock vLLM; Z.ai serves the newer GLM-5.3 on an $18 monthly plan. Speed and location versus price and recency.
When should I choose Z.ai over Wafer?
The newest GLM-5.3 models first; An $18 monthly plan instead of a weekly pass; Zero-cost trials on older Flash models.
When should I choose Wafer over Z.ai?
Faster GLM inference on a tuned stack; Flat weekly access to every hosted model; Dedicated GLM deployments tuned to a latency SLO.
Is Z.ai or Wafer cheaper?
Z.ai: $1.40 in, $4.40 out (GLM-5.3); free Flash tier. Wafer: Wafer Pass from $10 a week. The cheaper choice depends on the model and workload.
Which has more context, Z.ai or Wafer?
Z.ai: 1M (GLM-5.3). 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.