GLM-5.3
GLM-5.3 is Z.ai's flagship, announced on 18 August 2026, with open weights on Hugging Face from 25 August. It is a 753B-parameter mixture-of-experts with DeepSeek-style sparse attention and a 1M-token context, built on the GLM-5.2 base with further post-training aimed at coding. Reasoning is always on, with low, high and max effort levels.
Specifications
- Context window
- 1Mabout 786,000 words, or 1,570 pages
- Max output
- 128Ktokens per response
- Input price
- $1.40per 1M tokens
- Output price
- $4.40per 1M tokens
- Cached input
- $0.26per 1M tokens
- Weights
- OpenGLM-5.3 License
- Parameters
- 753BMoE
- Input types
- Text
- Output types
- Text
- Reasoning mode
- Yes
- Tool calling
- Yes
- Released
- Aug 18, 2026Current
Z.ai API price; cached-input storage is free for a limited time. Active parameters are not stated on the GLM-5.3 card (its config matches GLM-5, which Z.ai describes as 744B total / 40B active), so null. Announced 2026-08-18; weights on Hugging Face from 2026-08-25.
What it costs in practice
| Workload | Monthly cost at list price |
|---|---|
| Support chatbot30,000 conversations a month, 2,000 input and 400 output tokens each | $137 |
| Document summaries2,000 documents a month, 12,000 input and 800 output tokens each | $41 |
| Coding agent1,000 tasks a month, 60,000 input and 6,000 output tokens each | $110 |
Standard rates, no caching or batch discounts. Run your own numbers.
Strengths
- 1M-token context and 128K maximum output
- Coding-focused post-training
- Permissive license; only MaaS providers above $10B revenue need a security review
Trade-offs to weigh
- Reasoning cannot be disabled
- Text-only input; vision is in GLM-5.3-Flash
Where it fits
Z.ai (Zhipu AI) positions GLM-5.3 for:
Where you can use it
- Hugging Face
- Ollama
- API
- Together AI
- Fireworks
Run it yourself
Released under GLM-5.3 License. Approximate memory needed just to load the weights:
| Precision | Memory for weights |
|---|---|
| 16-bit (BF16/FP16) | 1,506 GB |
| 8-bit (FP8/INT8) | 753 GB |
| 4-bit (Q4_K_M, about 4.85 bits) | 457 GB |
Add memory for the KV cache (it grows with context length and concurrent users) and 1-2 GB of runtime overhead. Size it precisely in the VRAM calculator.
Alternatives to consider
| Model | Tier | Context | Input / output per 1M | |
|---|---|---|---|---|
| DeepSeek-V4-ProDeepSeek | Frontier | 1M | $1.32 / $3.96 | Compare |
| Qwen3.8-2.4T-A95BAlibaba (Qwen) | Frontier | 256K | $2 / $6 | Compare |
| Mistral Large 4Mistral AI | Frontier | 1M | $1.36 / $4.18 | Compare |
| Grok 4.7xAI | Frontier | 500K | $2 / $6 | Compare |
Frequently asked questions
How much does GLM-5.3 cost?
GLM-5.3 lists at $1.40 per million input tokens and $4.40 per million output tokens, with cached input at $0.26 (checked October 10, 2026). Z.ai API price; cached-input storage is free for a limited time. Active parameters are not stated on the GLM-5.3 card (its config matches GLM-5, which Z.ai describes as 744B total / 40B active), so null. Announced 2026-08-18; weights on Hugging Face from 2026-08-25. Confirm current rates on the provider's pricing page before you commit.
What is the context window of GLM-5.3?
GLM-5.3 accepts up to 1,048,576 tokens of context (about 786,000 words, or 1,570 pages), and it can write up to 128K tokens in a single response. Long prompts cost more and can be slower, so most apps send only what the task needs.
Is GLM-5.3 open source?
GLM-5.3 is an open-weight model released under the GLM-5.3 License license. You can download the weights from Hugging Face (zai-org/GLM-5.3) and run or fine-tune them yourself, within the license terms. Open weights isn't the same as fully open source: training data and code may not be published.
Can I run GLM-5.3 locally?
Yes, if you have enough memory. The weights alone need about 457 GB at 4-bit quantization and about 1,506 GB at 16-bit, plus room for the KV cache. Use the VRAM calculator on LLModel.com to check a specific GPU or Mac.
What is GLM-5.3 best for?
Z.ai (Zhipu AI) positions GLM-5.3 for coding, agents, long documents, reasoning. It accepts text as input, has a reasoning (thinking) mode and supports tool calling. Test it on a sample of your own tasks before you choose it for production.
Sources
- huggingface.co/zai-org/GLM-5.3
- docs.z.ai/guides/overview/pricing
- docs.z.ai/release-notes/new-released
- docs.z.ai/guides/llm/glm-5.3
- docs.z.ai/api-reference/llm/chat-completion
- huggingface.co/zai-org/GLM-5.3/raw/main/config.json
- huggingface.co/zai-org/GLM-5.3/raw/main/LICENSE
- huggingface.co/api/models/zai-org/GLM-5.3
- huggingface.co/zai-org/GLM-5
- huggingface.co/zai-org/GLM-5/raw/main/config.json
- docs.together.ai/docs/serverless-models
- docs.fireworks.ai/serverless/pricing
- ollama.com/library
Facts checked against these pages on October 10, 2026. Spot an error? Tell us.
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