> ## Documentation Index
> Fetch the complete documentation index at: https://veniceai-feat-models-redesign.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# GLM 5 API

> GLM 5 API on Venice: 198K context, $1.00 input and $3.20 output per 1M tokens. Private, with zero data retention. Supports reasoning and function calling.

export const HubMount = ({view, children, ...props}) => {
  const [hub, setHub] = useState(null);
  const [failed, setFailed] = useState(false);
  useEffect(() => {
    let alive = true;
    const w = window;
    if (!w.__veniceModelHub) {
      const urls = w.location.hostname === 'localhost' ? ['http://localhost:3333/data/model-hub.bundle.json', '/data/model-hub.bundle.json'] : ['/data/model-hub.bundle.json'];
      const load = i => fetch(urls[i], {
        cache: 'no-cache'
      }).then(res => {
        if (!res.ok) throw new Error(`bundle ${res.status}`);
        return res.json();
      }).catch(err => i + 1 < urls.length ? load(i + 1) : Promise.reject(err));
      const Frag = <></>.type;
      const h = (type, props, ...kids) => {
        const T = type;
        const {key, ...rest} = props || ({});
        if (!kids.length) return <T key={key} {...rest} />;
        if (kids.length === 1) return <T key={key} {...rest}>{kids[0]}</T>;
        return <T key={key} {...rest}>{kids.map((kid, i) => <Frag key={i}>{kid}</Frag>)}</T>;
      };
      w.__veniceModelHub = load(0).then(bundle => new Function(`return (${bundle.code})`)()({
        h,
        Fragment: Frag,
        useState,
        useEffect,
        useRef,
        useMemo,
        useCallback
      }));
    }
    w.__veniceModelHub.then(instance => {
      if (alive) setHub(instance);
    }).catch(() => {
      w.__veniceModelHub = null;
      if (alive) setFailed(true);
    });
    return () => {
      alive = false;
    };
  }, []);
  const View = hub ? hub[view] : null;
  if (View) return <View {...props}>{children}</View>;
  if (failed) {
    return <div className="vx-mount is-failed">
        <p className="vx-mount-note">The interactive model catalog could not load. The full data is below.</p>
        {children}
      </div>;
  }
  return <div className="vx-mount" aria-busy="true">
      <div className="vx-mount-skeleton" aria-hidden="true"><span /><span /><span /></div>
      <div className="vx-mount-source">{children}</div>
    </div>;
};

<HubMount view="ModelPage" data={{"family":{"slug":"glm-5","name":"GLM 5","modality":"text","task":"chat","provider":"zai","description":"GLM-5 is the next-generation large language model developed by Zhiyuan AI, featuring significantly enhanced reasoning capabilities, improved instruction following, and support for multiple languages. Supports large context windows for processing extensive text and detailed analysis.","primary":"zai-org-glm-5","variants":["zai-org-glm-5"],"created":1770768000,"updated":1770768000,"privacy":["private"],"openWeights":true},"models":[{"id":"zai-org-glm-5","name":"GLM 5","type":"text","modality":"text","task":"chat","variant":"standard","provider":"zai","created":1770768000,"description":"GLM-5 is the next-generation large language model developed by Zhiyuan AI, featuring significantly enhanced reasoning capabilities, improved instruction following, and support for multiple languages. Supports large context windows for processing extensive text and detailed analysis.","source":"https://huggingface.co/zai-org/GLM-5","privacy":"private","openWeights":true,"text":{"context":198000,"maxOutput":32000,"quantization":"fp8","reasoning":{"supported":true,"effort":["none","low","medium","high"],"defaultEffort":"low"},"caps":{"tools":true,"structured":true,"webSearch":true,"code":true}},"pricing":{"input":1,"output":3.2,"cacheRead":0.2,"blended":1.55},"headline":{"value":1.55,"unit":"per 1M tokens","basis":"blended"},"endpoints":[{"id":"chat","method":"POST","path":"/chat/completions","name":"Chat Completions","status":"stable","recommended":true},{"id":"responses","method":"POST","path":"/responses","name":"Responses","status":"alpha"}],"family":"glm-5"}],"related":{"similar":[{"slug":"qwen-3-5-397b","name":"Qwen 3.5 397B","provider":"alibaba","modality":"text","privacy":["anonymized"],"created":1771200000,"headline":{"value":1.6875,"unit":"per 1M tokens","basis":"blended"},"variants":1},{"slug":"gemini-3-flash-preview","name":"Gemini 3 Flash Preview","provider":"google","modality":"text","privacy":["anonymized"],"created":1766102400,"headline":{"value":1.4625,"unit":"per 1M tokens","basis":"blended"},"variants":1},{"slug":"kimi-k2-6","name":"Kimi K2.6","provider":"moonshot","modality":"text","privacy":["private","e2ee"],"created":1776643200,"headline":{"value":1.4375,"unit":"per 1M tokens","basis":"blended"},"variants":2},{"slug":"qwen-3-6-plus-uncensored","name":"Qwen 3.6 Plus Uncensored","provider":"alibaba","modality":"text","privacy":["anonymized"],"created":1775433600,"headline":{"value":1.40625,"unit":"per 1M tokens","basis":"blended"},"variants":1}],"versions":[{"slug":"glm-5-3","name":"GLM 5.3","provider":"zai","modality":"text","privacy":["private","e2ee"],"created":1787011200,"headline":{"value":2.6875,"unit":"per 1M tokens","basis":"blended"},"variants":2},{"slug":"glm-5-2","name":"GLM 5.2","provider":"zai","modality":"text","privacy":["private","e2ee"],"created":1781568000,"headline":{"value":2.15,"unit":"per 1M tokens","basis":"blended"},"variants":2},{"slug":"glm-5-1","name":"GLM 5.1","provider":"zai","modality":"text","privacy":["private"],"created":1775520000,"headline":{"value":2.365,"unit":"per 1M tokens","basis":"blended"},"variants":1},{"slug":"glm-4-7","name":"GLM 4.7","provider":"zai","modality":"text","privacy":["private"],"created":1766534400,"headline":{"value":1.075,"unit":"per 1M tokens","basis":"blended"},"variants":1},{"slug":"glm-4-6","name":"GLM 4.6","provider":"zai","modality":"text","privacy":["private"],"created":1711929600,"headline":{"value":0.76,"unit":"per 1M tokens","basis":"blended"},"variants":1}]},"providers":{"zai":{"slug":"zai","name":"Z.ai","logo":"/images/icons/models/Zhipu.svg"},"alibaba":{"slug":"alibaba","name":"Alibaba Qwen","logo":"/images/icons/models/qwen.svg"},"google":{"slug":"google","name":"Google","logo":"/images/icons/models/google.svg"},"moonshot":{"slug":"moonshot","name":"Moonshot AI","logo":"/images/icons/models/kimi.svg"}},"faq":[{"q":"How much does the GLM 5 API cost?","a":"$1.00 per 1M input tokens and $3.20 per 1M output tokens, with cached input at $0.20 per 1M. Prices are in USD and can be paid in DIEM at parity."},{"q":"What is the GLM 5 model ID?","a":"Use `zai-org-glm-5` as the `model` parameter."},{"q":"Is the GLM 5 API private?","a":"GLM 5 is private: requests run on infrastructure Venice controls with zero data retention, and prompts and outputs are never stored or used for training."},{"q":"What is the context window of GLM 5?","a":"198K tokens of context, with up to 32K output tokens per response."},{"q":"What does GLM 5 support?","a":"GLM 5 supports function calling, structured outputs, reasoning, web search and prompt caching. Reasoning effort is adjustable with `reasoning_effort`: none, low, medium and high (default low)."},{"q":"Which endpoint does the GLM 5 API use?","a":"Call `POST /chat/completions`. `/responses` (Alpha) is also supported."}]}} />

<div className="vx-static">
  <Accordion title="Plain-text specification">
    # GLM 5 API

    GLM 5 is a large language model by Z.ai, available on the Venice API as `zai-org-glm-5`. It runs privately, with zero data retention.

    GLM-5 is the next-generation large language model developed by Zhiyuan AI, featuring significantly enhanced reasoning capabilities, improved instruction following, and support for multiple languages. Supports large context windows for processing extensive text and detailed analysis.

    ## GLM 5 API pricing

    | Model ID | Variant | Privacy | Price |
    | - | - | - | - |
    | `zai-org-glm-5` | Standard | Private | $1.00 input / $3.20 output per 1M tokens |

    ## GLM 5 specifications

    | Spec | Value |
    | - | - |
    | Provider | Z.ai |
    | Released | Feb 11, 2026 |
    | Privacy | Private |
    | Open weights | Yes |
    | Context window | 198K tokens |
    | Max output | 32K tokens |
    | Reasoning effort | none, low, medium, high |
    | Served precision | FP8 |

    ## How to use the GLM 5 API

    Send requests to `POST https://api.venice.ai/api/v1/chat/completions` with `"model": "zai-org-glm-5"` and your API key.

    ```bash theme={null}
    curl https://api.venice.ai/api/v1/chat/completions \
      -H "Authorization: Bearer $VENICE_API_KEY" \
      -H "Content-Type: application/json" \
      -d '{
        "model": "zai-org-glm-5",
        "messages": [{ "role": "user", "content": "Explain TEE attestation in two sentences." }],
        "reasoning_effort": "low"
      }'
    ```

    ## GLM 5 API FAQ

    ### How much does the GLM 5 API cost?

    $1.00 per 1M input tokens and $3.20 per 1M output tokens, with cached input at \$0.20 per 1M. Prices are in USD and can be paid in DIEM at parity.

    ### What is the GLM 5 model ID?

    Use `zai-org-glm-5` as the `model` parameter.

    ### Is the GLM 5 API private?

    GLM 5 is private: requests run on infrastructure Venice controls with zero data retention, and prompts and outputs are never stored or used for training.

    ### What is the context window of GLM 5?

    198K tokens of context, with up to 32K output tokens per response.

    ### What does GLM 5 support?

    GLM 5 supports function calling, structured outputs, reasoning, web search and prompt caching. Reasoning effort is adjustable with `reasoning_effort`: none, low, medium and high (default low).

    ### Which endpoint does the GLM 5 API use?

    Call `POST /chat/completions`. `/responses` (Alpha) is also supported.

    ## Related models

    * [GLM 5.3 API](/models/glm-5-3): $1.75 input / $5.50 output per 1M tokens
    * [GLM 5.2 API](/models/glm-5-2): $1.40 input / $4.40 output per 1M tokens
    * [GLM 5.1 API](/models/glm-5-1): $1.54 input / $4.84 output per 1M tokens
    * [GLM 4.7 API](/models/glm-4-7): $0.55 input / $2.65 output per 1M tokens
    * [GLM 4.6 API](/models/glm-4-6): $0.43 input / $1.75 output per 1M tokens
    * [Qwen 3.5 397B API](/models/qwen-3-5-397b): $0.75 input / $4.50 output per 1M tokens
    * [Gemini 3 Flash Preview API](/models/gemini-3-flash-preview): $0.70 input / $3.75 output per 1M tokens
    * [Kimi K2.6 API](/models/kimi-k2-6): $0.75 input / $3.50 output per 1M tokens
    * [Qwen 3.6 Plus Uncensored API](/models/qwen-3-6-plus-uncensored): $0.63 input / $3.75 output per 1M tokens
  </Accordion>
</div>


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