GLM 4 Plus 0111
by Z.ai (Zhipu AI)Chatunverified match
Compact GPT model for low-latency assistance and high-volume workloads
- Context
- 128K tokens
- Max output
- 4,096 tokens
- Released
- 2025-02-19
- Weights
- Closed
zhipuai/glm-4-plus-0111
Specifications
Full facts as recorded, incl. what is unknown.
- Released
- 2025-02-19
- Weights
- Closed
- Input
- Text
- Output
- Text
- Context window
- 128,000 max across endpoints
- Max output
- 4,096
- Providers
- 0 + 1 gateway, not counted as providers
- Epoch Capabilities Index
- not evaluated
- Direct price range
- $10.00 in at NanoGPT, via gateway, fees not verified
More details
- Last updated
- 2025-02-19
- Knowledge cutoff
Capabilities
Across all endpoints: supported if any endpoint supports it.
- Tool calling
- Parallel toolsunknown
- Structured output
- Reasoning
- Image input
- PDF input
- Audio input
- Audio outputunknown
- Video input
- Prompt cachingunknown
- Web searchunknown
- Computer useunknown
- System messagesunknown
- Assistant prefillunknown
- Temperatureunknown
- Streamingunknown
- Attachments
Endpoints
One row per provider and variant; gateways are listed separately.
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Cost calculator
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Similarly priced models
Blended rate per 1M tokens, each at its own cheapest provider (10M input : 2M output mix).
| Model | Blended/1M | In/1M | Out/1M | Context | vs GLM 4 Plus 0111 |
|---|---|---|---|---|---|
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| GPT-5.5OpenAI | $9.17 | $5.00 | $30 | 1.05M | −8% cheaper |
| GPT Chat LatestOpenAI | $9.17 | $5.00 | $30 | 400K | −8% cheaper |
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More from Z.ai (Zhipu AI)
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|---|---|---|---|
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| Apex Flash 1 Abliterated | 2026-10-05 | 1.05M | $0.15 via NanoGPT |
| GLM 5.3 Uncensored | 2026-09-26 | 1.05M | $1.25 via NanoGPT |
| GLM 5.3 Prime | 2026-09-23 | 1M | from $2.80 |
| GLM 5.3 Flash Cybersecurity | 2026-09-19 | 1.05M | $0.15 via NanoGPT |
| GLM 5.3 FlashX | 2026-09-18 | 1.05M | from $0.37 |
| GLM-5.3-Flash | 2026-08-26 | 1.05M | from $0.099 |
| GLM-5.3 | 2026-08-14 | 1.05M | from $0.75 |
Heads up: prices are indicative list rates scraped from provider pricing pages; verify with the provider before relying on them. Report incorrect data for this model