GLM-4.7-Flash
GLM-4.7-Flash is Z.ai's lightweight option in the 30B class (MIT licence, January 2026): a mixture-of-experts model with about 30B parameters and 3B active per token. It targets agentic coding, task planning and tool use where cost and latency matter more than peak quality, and keeps its reasoning across turns in multi-step tasks. The card reports 59.2 on SWE-bench Verified. It is fulfilled through global providers under our European contract, and requests go only to backends that do not retain prompts or completions.
model id: glm-4.7-flash
from openai import OpenAI client = OpenAI( api_key="hb-...", base_url="https://api.heabsy.com/v1",) r = client.chat.completions.create( model="glm-4.7-flash", messages=[{"role": "user", "content": "Hello"}],)print(r.choices[0].message.content)
curl https://api.heabsy.com/v1/chat/completions \ -H "Authorization: Bearer $HEABSY_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "glm-4.7-flash", "messages": [{"role": "user", "content": "Hello"}] }'
import OpenAI from "openai"; const client = new OpenAI({ apiKey: process.env.HEABSY_API_KEY, baseURL: "https://api.heabsy.com/v1",}); const r = await client.chat.completions.create({ model: "glm-4.7-flash", messages: [{ role: "user", content: "Hello" }],});console.log(r.choices[0].message.content);
Price list, updated 12 September 2026. No minimum spend, no subscription.
About the model
- Developer
- Z.ai
- Released
- January 2026
- Licence
- MIT
- Architecture
- mixture of experts · 30B parameters, 3B active per token
- Input
- text
- Reasoning
- reasoning model
- Languages named by the developer
- English, Chinese
Source: the developer's model card, as of 17 September 2026.
Licence: what it means for your company
MIT. A permissive open-source licence: you may use, modify and sell products built on the model, including commercially; when you redistribute the weights, the licence and copyright notices go with them.
A summary of the licence, not legal advice.
Benchmarks reported by the developer
- SWE-bench Verified
- 59.2
- τ²-Bench
- 79.5
Figures from the developer's model card, not our measurement. Source: huggingface.co/zai-org/GLM-4.7-Flash
Technical details
- Context window
- 195K tokens
- Max output
- 65,536 tokens
- Throughput limit
- 200K tok/min
- Tokenizer
- Other
- Streaming
- yes
- Open weights
- z-ai/glm-4.7-flash
- max_tokens
- 1 … 65536
- temperature
- 0 … 2
- top_p
- 0 … 1
- frequency_penalty
- -2 … 2
- presence_penalty
- -2 … 2
- stop
- array
- seed
- integer
This model is fulfilled through global providers under our European contract: one DPA with an EU company, one invoice for every model in the catalog, no US counterparty on your paperwork. Compute may run outside the EEA — if you need strict EEA-only processing, use our own-hardware model.
Questions about this model
›Where is GLM-4.7-Flash computed?
Outside the EEA, through a global provider under our European contract. You get one DPA with an EU company and one invoice, but the compute itself does not run in the EEA — we state that instead of hiding it.
›Does GLM-4.7-Flash store prompts and completions?
No. This model runs with zero data retention: request content is not written to durable storage and nothing is used for training.
›How large is the GLM-4.7-Flash context window?
195K tokens, with up to 65,536 tokens of output.
›What does GLM-4.7-Flash cost?
$0.09 per million input tokens and $0.62 per million output tokens. No minimum spend and no subscription; the same price list covers the API and the invoice.
›Is there a throughput limit on GLM-4.7-Flash?
Yes, 200K tokens per minute. Higher limits are a question of volume, not of principle.
›Which languages does GLM-4.7-Flash support?
The developer names English, Chinese. Languages not on that list may still work, but they are not claimed — test on your own material first.
›Under which licence is GLM-4.7-Flash released?
MIT. A permissive open-source licence: you may use, modify and sell products built on the model, including commercially; when you redistribute the weights, the licence and copyright notices go with them.
›Can reasoning be switched off in GLM-4.7-Flash?
GLM-4.7-Flash is built as a reasoning model; the developer's card does not document a way to switch reasoning off.
Compare with similar models
| Model | Developer | Parameters | Context | Licence | Input / 1M |
|---|---|---|---|---|---|
| GLM-4.7-Flash | Z.ai | 30B / 3B | 195K | MIT | $0.09 |
| GLM-5.3-Flash (NVFP4) | Z.ai | 320B / 18B | 1M | MIT | $0.04 |
| Nemotron 3.5 Lightning | NVIDIA | 30B / 3B | 256K | OpenMDW-1.1 | $0.12 |
| Gemma 4 31B | Google DeepMind | 30.7B | 256K | Apache-2.0 | $0.14 |
30 more models behind the same key and the same invoice.
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