> ## 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.

# Mercury 2.5 API

> Mercury 2.5 API on Venice: 260K context, $0.05 input and $0.19 output per 1M tokens. Anonymized access without your identity. Pricing, specs and code examples.

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":"mercury-2-5","name":"Mercury 2.5","modality":"text","task":"chat","provider":"inception","description":"Mercury 2.5 is a diffusion-based reasoning model from Inception with fast parallel token generation, tunable reasoning, tool calling, and structured output support.","primary":"mercury-2-5","variants":["mercury-2-5"],"created":1788825600,"updated":1788825600,"privacy":["anonymized"]},"models":[{"id":"mercury-2-5","name":"Mercury 2.5","type":"text","modality":"text","task":"chat","variant":"standard","provider":"inception","created":1788825600,"description":"Mercury 2.5 is a diffusion-based reasoning model from Inception with fast parallel token generation, tunable reasoning, tool calling, and structured output support.","source":"https://www.inceptionlabs.ai/models","privacy":"anonymized","text":{"context":260000,"maxOutput":65536,"reasoning":{"supported":true,"effort":["none","low","medium","high"],"defaultEffort":"high"},"caps":{"tools":true,"structured":true,"webSearch":true}},"pricing":{"input":0.05,"output":0.1875,"cacheRead":0.005,"blended":0.084375},"headline":{"value":0.084375,"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":"mercury-2-5"}],"related":{"similar":[{"slug":"qwen-2-5-7b","name":"Qwen 2.5 7B","provider":"alibaba","modality":"text","privacy":["e2ee"],"created":1773792000,"headline":{"value":0.07,"unit":"per 1M tokens","basis":"blended"},"variants":1},{"slug":"qwen-3-5-9b","name":"Qwen 3.5 9B","provider":"alibaba","modality":"text","privacy":["private"],"created":1772668800,"headline":{"value":0.1125,"unit":"per 1M tokens","basis":"blended"},"variants":1},{"slug":"nvidia-nemotron-3-nano-30b","name":"NVIDIA Nemotron 3 Nano 30B","provider":"nvidia","modality":"text","privacy":["private"],"created":1769472000,"headline":{"value":0.13125,"unit":"per 1M tokens","basis":"blended"},"variants":1},{"slug":"mistral-small-3-2-24b-instruct","name":"Mistral Small 3.2 24B Instruct","provider":"mistral","modality":"text","privacy":["private"],"created":1768435200,"headline":{"value":0.132813,"unit":"per 1M tokens","basis":"blended"},"variants":1}],"versions":[{"slug":"mercury-2","name":"Mercury 2","provider":"inception","modality":"text","privacy":["anonymized"],"created":1771545600,"headline":{"value":0.46875,"unit":"per 1M tokens","basis":"blended"},"variants":1}]},"providers":{"inception":{"slug":"inception","name":"Inception","logo":"/images/icons/models/inception.svg"},"alibaba":{"slug":"alibaba","name":"Alibaba Qwen","logo":"/images/icons/models/qwen.svg"},"nvidia":{"slug":"nvidia","name":"NVIDIA","logo":"/images/icons/models/nvidia.svg"},"mistral":{"slug":"mistral","name":"Mistral AI","logo":"/images/icons/models/mistral.svg"}},"faq":[{"q":"How much does the Mercury 2.5 API cost?","a":"$0.05 per 1M input tokens and $0.19 per 1M output tokens, with cached input at $0.005 per 1M. Prices are in USD and can be paid in DIEM at parity."},{"q":"What is the Mercury 2.5 model ID?","a":"Use `mercury-2-5` as the `model` parameter."},{"q":"Is the Mercury 2.5 API private?","a":"Mercury 2.5 is anonymized: Venice forwards requests to the provider without your identity, but the provider may retain prompt data, so use a private model for sensitive work."},{"q":"What is the context window of Mercury 2.5?","a":"260K tokens of context, with up to 64K output tokens per response."},{"q":"What does Mercury 2.5 support?","a":"Mercury 2.5 supports function calling, structured outputs, reasoning, web search and prompt caching. Reasoning effort is adjustable with `reasoning_effort`: none, low, medium and high (default high)."},{"q":"Which endpoint does the Mercury 2.5 API use?","a":"Call `POST /chat/completions`. `/responses` (Alpha) is also supported."}]}} />

<div className="vx-static">
  <Accordion title="Plain-text specification">
    # Mercury 2.5 API

    Mercury 2.5 is a large language model by Inception, available on the Venice API as `mercury-2-5`. Requests are anonymized, so the provider never sees your identity.

    Mercury 2.5 is a diffusion-based reasoning model from Inception with fast parallel token generation, tunable reasoning, tool calling, and structured output support.

    ## Mercury 2.5 API pricing

    | Model ID | Variant | Privacy | Price |
    | - | - | - | - |
    | `mercury-2-5` | Standard | Anonymized | $0.05 input / $0.19 output per 1M tokens |

    ## Mercury 2.5 specifications

    | Spec | Value |
    | - | - |
    | Provider | Inception |
    | Released | Sep 8, 2026 |
    | Privacy | Anonymized |
    | Context window | 260K tokens |
    | Max output | 64K tokens |
    | Reasoning effort | none, low, medium, high |

    ## How to use the Mercury 2.5 API

    Send requests to `POST https://api.venice.ai/api/v1/chat/completions` with `"model": "mercury-2-5"` 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": "mercury-2-5",
        "messages": [{ "role": "user", "content": "Explain TEE attestation in two sentences." }],
        "reasoning_effort": "high"
      }'
    ```

    ## Mercury 2.5 API FAQ

    ### How much does the Mercury 2.5 API cost?

    $0.05 per 1M input tokens and $0.19 per 1M output tokens, with cached input at \$0.005 per 1M. Prices are in USD and can be paid in DIEM at parity.

    ### What is the Mercury 2.5 model ID?

    Use `mercury-2-5` as the `model` parameter.

    ### Is the Mercury 2.5 API private?

    Mercury 2.5 is anonymized: Venice forwards requests to the provider without your identity, but the provider may retain prompt data, so use a private model for sensitive work.

    ### What is the context window of Mercury 2.5?

    260K tokens of context, with up to 64K output tokens per response.

    ### What does Mercury 2.5 support?

    Mercury 2.5 supports function calling, structured outputs, reasoning, web search and prompt caching. Reasoning effort is adjustable with `reasoning_effort`: none, low, medium and high (default high).

    ### Which endpoint does the Mercury 2.5 API use?

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

    ## Related models

    * [Mercury 2 API](/models/mercury-2): $0.31 input / $0.94 output per 1M tokens
    * [Qwen 2.5 7B API](/models/qwen-2-5-7b): $0.05 input / $0.13 output per 1M tokens
    * [Qwen 3.5 9B API](/models/qwen-3-5-9b): $0.10 input / $0.15 output per 1M tokens
    * [NVIDIA Nemotron 3 Nano 30B API](/models/nvidia-nemotron-3-nano-30b): $0.07 input / $0.30 output per 1M tokens
    * [Mistral Small 3.2 24B Instruct API](/models/mistral-small-3-2-24b-instruct): $0.09 input / $0.25 output per 1M tokens
  </Accordion>
</div>


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