Z.AI
GLM-4.7-Flash
Budget GLM lane for fast coding help, routing, and everyday automation
Model facts
- Context window
- 2K tokens
- Maximum output
- 131K tokens
- Cheapest paid input
- $0.06 per 1M tokens
- Cheapest paid output
- $0.4 per 1M tokens
- Open weights
- yes
- Providers
- 27
Capabilities and modalities
reasoning, tool calling, structured output, attachments, temperature control, open weights, text.
Local hardware estimate
At 4K context: Q4_K_M 20.1 GiB, Q8_0 34.6 GiB, F16 61.9 GiB working memory.
- Parameters
- 31.2 billion
- Architecture
- glm4moelite
- Model license
- mit
Planning estimate adapted from the MIT-licensed whichllm estimator using metadata from Hugging Face; not a vendor minimum requirement.
Artificial Analysis benchmarks
Compare this model on the full LLM benchmark leaderboard.
| Configuration | AAI | Coding | Math | Output tokens/s |
|---|---|---|---|---|
| Reasoning | 23.3 | not measured | not measured | not measured |
| Non-reasoning | 15.6 | not measured | not measured | not measured |
Observed price history
- 2026-08-24: $0.06 input / $0.4 output per 1M tokens
API providers
- EmpirioLabs AI — model id glm-4-7-flash; free input / free output per 1M tokens; provider documentation
- Hugging Face — model id zai-org/GLM-4.7-Flash; free input / free output per 1M tokens; provider documentation
- Kenari (Free) — model id glm-4-7-flash:free; free input / free output per 1M tokens; provider documentation
- Pendra — model id glm-4.7-flash; free input / free output per 1M tokens; provider documentation
- Z.AI — model id glm-4.7-flash; free input / free output per 1M tokens; provider documentation
- ZenMux — model id z-ai/glm-4.7-flash-free; free input / free output per 1M tokens; provider documentation
- Zhipu AI — model id glm-4.7-flash; free input / free output per 1M tokens; provider documentation
- OpenRouter — model id z-ai/glm-4.7-flash; $0.06 input / $0.4 output per 1M tokens; provider documentation
- Deep Infra — model id zai-org/GLM-4.7-Flash; $0.06 input / $0.4 output per 1M tokens; provider documentation
- DevPass (LLM Gateway) — model id glm-4.7-flash; $0.06 input / $0.4 output per 1M tokens; provider documentation
- Eden AI — model id deepinfra/zai-org/GLM-4.7-Flash; $0.06 input / $0.4 output per 1M tokens; provider documentation
- Kilo Gateway — model id z-ai/glm-4.7-flash; $0.06 input / $0.4 output per 1M tokens; provider documentation
- LLM Gateway — model id embercloud/glm-4.7-flash; $0.06 input / $0.4 output per 1M tokens; provider documentation
- Venice AI — model id zai-org-glm-4.7-flash; $0.06 input / $0.4 output per 1M tokens; provider documentation
- Cloudflare Workers AI — model id @cf/zai-org/glm-4.7-flash; $0.06 input / $0.4 output per 1M tokens; provider documentation
- Eden AI — model id cloudflare/@cf/zai-org/glm-4.7-flash; $0.06 input / $0.4 output per 1M tokens; provider documentation
- Amazon Bedrock — model id zai.glm-4.7-flash; $0.07 input / $0.4 output per 1M tokens; provider documentation
- Eden AI — model id amazon/zai.glm-4.7-flash; $0.07 input / $0.4 output per 1M tokens; provider documentation
- Eden AI (US) — model id amazon/zai.glm-4.7-flash@us; $0.07 input / $0.4 output per 1M tokens; provider documentation
- Jiekou.AI — model id zai-org/glm-4.7-flash; $0.07 input / $0.4 output per 1M tokens; provider documentation
- Merge Gateway — model id zai/glm-4.7-flash; $0.07 input / $0.4 output per 1M tokens; provider documentation
- NanoGPT — model id z-ai/glm-4.7-flash; $0.07 input / $0.4 output per 1M tokens; provider documentation
- NovitaAI — model id zai-org/glm-4.7-flash; $0.07 input / $0.4 output per 1M tokens; provider documentation
- Vercel AI Gateway — model id zai/glm-4.7-flash; $0.07 input / $0.4 output per 1M tokens; provider documentation
- Cortecs — model id glm-4.7-flash; $0.08 input / $0.478 output per 1M tokens; provider documentation
- Synthetic — model id hf:zai-org/GLM-4.7-Flash; $0.1 input / $0.5 output per 1M tokens; provider documentation
- Poe — model id novita/glm-4.7-flash; not published input / not published output per 1M tokens; provider documentation