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Z.ai vs Novita AI
Z.ai sells GLM at low first-party prices plus a flat coding plan; Novita sells 200+ open models across modalities on one cheap bill. Depth in one family versus breadth.
By The Subconscious Team · Updated
Z.ai vs Novita AI: key differences
Both compete on price, in different shapes. Z.ai is a model maker selling its own GLM family: GLM-5.3 at $1.40 in and $4.40 out, GLM-5.3-Flash at $0.075 in and $0.25 out, free older Flash models, and a GLM Coding Plan from $18 a month. Novita is a host with 200+ open models across LLMs, image, video, speech, voice cloning and embeddings, with LLM prices from $0.02 per million and batch at 50% off. Both speak OpenAI and Anthropic formats. Because GLM weights are open, it is worth checking Novita's catalog for the GLM version you need.
Location and support separate them. Z.ai's servers sit mostly in China, adding 100 to 200ms from the US or Europe. Novita is a San Francisco company with a GPU cloud, dedicated endpoints for any Hugging Face model with hot-swappable LoRA, and a per-second Agent Sandbox. Its weak spots are looser serverless SLAs, middling uptime ratings, Discord-based support and no public SOC 2 or HIPAA. Z.ai's are data concerns and quota that burns faster during Beijing peak hours. For GLM coding on a plan, Z.ai fits. For many model types on one bill, Novita does.
What Z.ai and Novita AI 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 profileNovita AI
Novita AI is a San Francisco inference cloud founded in late 2023 by Frank Lewis and Junyu Huang, and it competes on price and breadth. Its serverless API covers 200+ open models across LLMs, image, video, speech, voice cloning and embeddings, with LLM prices starting at $0.02 per million tokens. The API speaks both OpenAI and Anthropic formats. It became an official Hugging Face Inference Partner in April 2026 and was the day-zero launch partner for Google's Gemma 4.
Example models: DeepSeek V4 Pro, Gemma 4
Full Novita AI profileShould you choose Z.ai or Novita AI?
Z.ai vs Novita AI at a glance
| Attribute | Z.ai | Novita AI |
|---|---|---|
| Model access | Open weights (MIT) | Open weights |
| Flagship models | GLM-5.3, GLM-5.3-Flash | DeepSeek V4 Pro, Gemma 4 |
| Speed | ~80 tok/s on GLM-5.3 | ~36 tok/s on DeepSeek V4 Pro |
| Price | $1.40 in, $4.40 out (GLM-5.3); free Flash tier | From $0.02 per 1M; batch 50% off |
| Customization | Open weights, no license limits | Hot-swappable LoRA adapters |
| Deployment | API, GLM Coding Plan | Serverless, GPU cloud, dedicated |
| Long context | 1M (GLM-5.3) | Full 1M on DeepSeek V4 Pro |
Frequently asked questions
What is the difference between Z.ai and Novita AI?
Z.ai sells GLM at low first-party prices plus a flat coding plan; Novita sells 200+ open models across modalities on one cheap bill. Depth in one family versus breadth.
When should I choose Z.ai over Novita AI?
Flat-rate GLM coding in Claude Code; First-party access to new GLM releases; Free Flash-tier text calls.
When should I choose Novita AI over Z.ai?
Many model types, including image and video, on one bill; Dedicated endpoints for private Hugging Face models; Agent sandboxes next to model APIs.
Is Z.ai or Novita AI cheaper?
Z.ai: $1.40 in, $4.40 out (GLM-5.3); free Flash tier. Novita AI: From $0.02 per 1M; batch 50% off. The cheaper choice depends on the model and workload.
Which has more context, Z.ai or Novita AI?
Z.ai: 1M (GLM-5.3). Novita AI: Full 1M on DeepSeek V4 Pro.
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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.