{
  "aboutHtml": "<h3>Working with text material</h3><p>GPT-6.1 Terra Pro in Ailoot API accepts a text request and returns a text response. This listing can form part of document preparation, source-material analysis and iterative refinement through conversation. Provide the task, necessary information and desired response format in one request or across the conversation’s messages.</p><h3>Preparing a document</h3><p>Start with the goal: which document you need, who it is for and what action it should help someone take. Include key points, source excerpts or a draft. Then define the structure—for example, an introduction, main conclusions, supporting arguments and next steps. For editing, specify what should change: length, tone, terminology or the order of presentation. This defines a verifiable result rather than an open-ended instruction to “improve the text.”</p><h3>Analysis and comparison</h3><p>To analyze several sources, separate them by title and define the comparison criteria. You can request a short summary of each text, a combined list of questions or a point-by-point comparison of requirements. If precise source attribution matters, ask for the document title and relevant passage alongside each conclusion. A field list and a completed example can help produce a response suited to further manual processing.</p><h3>Connection and size</h3><p>In Ailoot API, this listing is configured with the Messages, Responses, Chat Completions and Gemini-compatible generateContent text interfaces. Use the message format supported by your client. Document contents and other source material are supplied as text; the result is text that can be saved, edited or passed to the next stage of work.</p><p>For a large task, distribute the available space between source material, instructions and the expected response. If you need a brief conclusion, specify its length directly; if completeness matters, list the mandatory sections and verification criteria.</p><h3>Request sequence</h3><ol><li>Describe the end task and include the source text.</li><li>Define the constraints and desired structure.</li><li>Compare the response with the source material.</li><li>Refine individual sections while preserving the overall goal and requirements.</li></ol>",
  "aboutText": "### Working with text material\n\nGPT-6.1 Terra Pro in Ailoot API accepts a text request and returns a text response. This listing can form part of document preparation, source-material analysis and iterative refinement through conversation. Provide the task, necessary information and desired response format in one request or across the conversation’s messages.\n\n### Preparing a document\n\nStart with the goal: which document you need, who it is for and what action it should help someone take. Include key points, source excerpts or a draft. Then define the structure—for example, an introduction, main conclusions, supporting arguments and next steps. For editing, specify what should change: length, tone, terminology or the order of presentation. This defines a verifiable result rather than an open-ended instruction to “improve the text.”\n\n### Analysis and comparison\n\nTo analyze several sources, separate them by title and define the comparison criteria. You can request a short summary of each text, a combined list of questions or a point-by-point comparison of requirements. If precise source attribution matters, ask for the document title and relevant passage alongside each conclusion. A field list and a completed example can help produce a response suited to further manual processing.\n\n### Connection and size\n\nIn Ailoot API, this listing is configured with the Messages, Responses, Chat Completions and Gemini-compatible generateContent text interfaces. Use the message format supported by your client. Document contents and other source material are supplied as text; the result is text that can be saved, edited or passed to the next stage of work.\n\nFor a large task, distribute the available space between source material, instructions and the expected response. If you need a brief conclusion, specify its length directly; if completeness matters, list the mandatory sections and verification criteria.\n\n### Request sequence\n\n1. Describe the end task and include the source text.\n2. Define the constraints and desired structure.\n3. Compare the response with the source material.\n4. Refine individual sections while preserving the overall goal and requirements.",
  "locale": "en",
  "methods": [
    {
      "html": "<section class=\"meth\" data-route=\"Ultra\"><header><b><span class=\"alias\">Ultra</span> Anthropic Messages</b><code>POST /v1/messages</code></header><dl class=\"method-capabilities\" data-model-capabilities><div><dt>Input types</dt><dd><code>text</code></dd></div><div><dt>Output types</dt><dd><code>text</code></dd></div><div><dt>Context</dt><dd>Not specified in the catalogue</dd></div><div><dt>Max. output</dt><dd>Not specified in the catalogue</dd></div></dl><dl><div><dt>Input</dt><dd>$0.002 <em>/ 1K</em></dd></div><div><dt>Output</dt><dd>$0.01 <em>/ 1K</em></dd></div><div><dt>Cache read</dt><dd>$0.0001 <em>/ 1K</em></dd></div><div><dt>Cache write</dt><dd>$0.0025 <em>/ 1K</em></dd></div><div><dt>Cache write, 5 min</dt><dd>$0.0025 <em>/ 1K tokens</em></dd></div><div><dt>Cache write, 1 hour</dt><dd>$0.0025 <em>/ 1K tokens</em></dd></div><div><dt>web_search_call</dt><dd>$0.02 <em>per call</em></dd></div></dl><h4>Prices by request length · Anthropic Messages</h4><div class=\"tw\" data-card-table=\"tiers\"><table><thead><tr><th>Request size, tokens</th><th class=\"num\">Input</th><th class=\"num\">Output</th><th class=\"num\">Cache read</th><th class=\"num\">Cache write</th><th class=\"num\">5 min cache</th><th class=\"num\">1 hour cache</th></tr></thead><tbody><tr><td data-cell-label=\"Request size, tokens\"><span class=\"card-cell-label\">Request size, tokens</span><span class=\"card-tier-interval\">(0; 272,000]</span></td><td data-cell-label=\"Input\" class=\"num\"><span class=\"card-cell-label\">Input</span>$0.002</td><td data-cell-label=\"Output\" class=\"num\"><span class=\"card-cell-label\">Output</span>$0.01</td><td data-cell-label=\"Cache read\" class=\"num\"><span class=\"card-cell-label\">Cache read</span>$0.0001</td><td data-cell-label=\"Cache write\" class=\"num\"><span class=\"card-cell-label\">Cache write</span>$0.0025</td><td data-cell-label=\"5 min cache\" class=\"num\"><span class=\"card-cell-label\">5 min cache</span>$0.0025</td><td data-cell-label=\"1 hour cache\" class=\"num\"><span class=\"card-cell-label\">1 hour cache</span>$0.0025</td></tr><tr><td data-cell-label=\"Request size, tokens\"><span class=\"card-cell-label\">Request size, tokens</span><span class=\"card-tier-interval\">(272,000; ∞)</span></td><td data-cell-label=\"Input\" class=\"num\"><span class=\"card-cell-label\">Input</span>$0.004</td><td data-cell-label=\"Output\" class=\"num\"><span class=\"card-cell-label\">Output</span>$0.015</td><td data-cell-label=\"Cache read\" class=\"num\"><span class=\"card-cell-label\">Cache read</span>$0.0002</td><td data-cell-label=\"Cache write\" class=\"num\"><span class=\"card-cell-label\">Cache write</span>$0.005</td><td data-cell-label=\"5 min cache\" class=\"num\"><span class=\"card-cell-label\">5 min cache</span>$0.005</td><td data-cell-label=\"1 hour cache\" class=\"num\"><span class=\"card-cell-label\">1 hour cache</span>$0.005</td></tr></tbody></table></div><p class=\"note-s\">Rates in USD per 1K tokens. If no rate is set, the base rate for this method is inherited; «—» means no base rate is set.</p></section>",
      "method_identity": {
        "effective_request_model_id": "openai/gpt-6.1-terra-pro",
        "fmt": "messages",
        "http": "POST",
        "path": "/v1/messages",
        "request_model_id": "openai/gpt-6.1-terra-pro",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|messages|/v1/messages|openai%2Fgpt-6.1-terra-pro",
      "ordinal": 0,
      "rawMethod": {
        "cache_read": 0.1,
        "cache_write": 2.5,
        "cache_write_1h": 2.5,
        "cache_write_5m": 2.5,
        "conditional_meter": null,
        "ctx": null,
        "family": "anthropic",
        "fast_multiplier": 1,
        "flex_multiplier": 1,
        "fmt": "messages",
        "http": "POST",
        "img_in": null,
        "img_out": null,
        "in": 2.0,
        "input": [
          "text"
        ],
        "label": "Anthropic Messages",
        "max_out": null,
        "max_tool_calls": null,
        "out": 10.0,
        "output": [
          "text"
        ],
        "path": "/v1/messages",
        "request_model_id": "openai/gpt-6.1-terra-pro",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [
          {
            "cache_read": 0.1,
            "cache_write": 2.5,
            "cache_write_1h": 2.5,
            "cache_write_5m": 2.5,
            "in": 2.0,
            "interval_boundary": "min_exclusive_max_inclusive",
            "label": "<=272K",
            "max": 272000,
            "min": 0,
            "null_rate_policy": "inherit_base_rate",
            "out": 10.0
          },
          {
            "cache_read": 0.2,
            "cache_write": 5.0,
            "cache_write_1h": 5.0,
            "cache_write_5m": 5.0,
            "in": 4.0,
            "interval_boundary": "min_exclusive_max_inclusive",
            "label": ">272K",
            "max": null,
            "min": 272000,
            "null_rate_policy": "inherit_base_rate",
            "out": 15.0
          }
        ],
        "tool_prices": {
          "web_search_call": 0.02
        },
        "unit": "token",
        "units": []
      }
    },
    {
      "html": "<section class=\"meth\" data-route=\"Ultra\"><header><b><span class=\"alias\">Ultra</span> OpenAI Responses</b><code>POST /v1/responses</code></header><dl class=\"method-capabilities\" data-model-capabilities><div><dt>Input types</dt><dd><code>text</code></dd></div><div><dt>Output types</dt><dd><code>text</code></dd></div><div><dt>Context</dt><dd>Not specified in the catalogue</dd></div><div><dt>Max. output</dt><dd>Not specified in the catalogue</dd></div></dl><dl><div><dt>Input</dt><dd>$0.002 <em>/ 1K</em></dd></div><div><dt>Output</dt><dd>$0.01 <em>/ 1K</em></dd></div><div><dt>Cache read</dt><dd>$0.0001 <em>/ 1K</em></dd></div><div><dt>Cache write</dt><dd>$0.0025 <em>/ 1K</em></dd></div><div><dt>Cache write, 5 min</dt><dd>$0.0025 <em>/ 1K tokens</em></dd></div><div><dt>Cache write, 1 hour</dt><dd>$0.0025 <em>/ 1K tokens</em></dd></div><div><dt>web_search_call</dt><dd>$0.02 <em>per call</em></dd></div></dl><h4>Prices by request length · OpenAI Responses</h4><div class=\"tw\" data-card-table=\"tiers\"><table><thead><tr><th>Request size, tokens</th><th class=\"num\">Input</th><th class=\"num\">Output</th><th class=\"num\">Cache read</th><th class=\"num\">Cache write</th><th class=\"num\">5 min cache</th><th class=\"num\">1 hour cache</th></tr></thead><tbody><tr><td data-cell-label=\"Request size, tokens\"><span class=\"card-cell-label\">Request size, tokens</span><span class=\"card-tier-interval\">(0; 272,000]</span></td><td data-cell-label=\"Input\" class=\"num\"><span class=\"card-cell-label\">Input</span>$0.002</td><td data-cell-label=\"Output\" class=\"num\"><span class=\"card-cell-label\">Output</span>$0.01</td><td data-cell-label=\"Cache read\" class=\"num\"><span class=\"card-cell-label\">Cache read</span>$0.0001</td><td data-cell-label=\"Cache write\" class=\"num\"><span class=\"card-cell-label\">Cache write</span>$0.0025</td><td data-cell-label=\"5 min cache\" class=\"num\"><span class=\"card-cell-label\">5 min cache</span>$0.0025</td><td data-cell-label=\"1 hour cache\" class=\"num\"><span class=\"card-cell-label\">1 hour cache</span>$0.0025</td></tr><tr><td data-cell-label=\"Request size, tokens\"><span class=\"card-cell-label\">Request size, tokens</span><span class=\"card-tier-interval\">(272,000; ∞)</span></td><td data-cell-label=\"Input\" class=\"num\"><span class=\"card-cell-label\">Input</span>$0.004</td><td data-cell-label=\"Output\" class=\"num\"><span class=\"card-cell-label\">Output</span>$0.015</td><td data-cell-label=\"Cache read\" class=\"num\"><span class=\"card-cell-label\">Cache read</span>$0.0002</td><td data-cell-label=\"Cache write\" class=\"num\"><span class=\"card-cell-label\">Cache write</span>$0.005</td><td data-cell-label=\"5 min cache\" class=\"num\"><span class=\"card-cell-label\">5 min cache</span>$0.005</td><td data-cell-label=\"1 hour cache\" class=\"num\"><span class=\"card-cell-label\">1 hour cache</span>$0.005</td></tr></tbody></table></div><p class=\"note-s\">Rates in USD per 1K tokens. If no rate is set, the base rate for this method is inherited; «—» means no base rate is set.</p></section>",
      "method_identity": {
        "effective_request_model_id": "openai/gpt-6.1-terra-pro",
        "fmt": "responses",
        "http": "POST",
        "path": "/v1/responses",
        "request_model_id": "openai/gpt-6.1-terra-pro",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|responses|/v1/responses|openai%2Fgpt-6.1-terra-pro",
      "ordinal": 1,
      "rawMethod": {
        "cache_read": 0.1,
        "cache_write": 2.5,
        "cache_write_1h": 2.5,
        "cache_write_5m": 2.5,
        "conditional_meter": null,
        "ctx": null,
        "family": "openai",
        "fast_multiplier": 1,
        "flex_multiplier": 1,
        "fmt": "responses",
        "http": "POST",
        "img_in": null,
        "img_out": null,
        "in": 2.0,
        "input": [
          "text"
        ],
        "label": "OpenAI Responses",
        "max_out": null,
        "max_tool_calls": null,
        "out": 10.0,
        "output": [
          "text"
        ],
        "path": "/v1/responses",
        "request_model_id": "openai/gpt-6.1-terra-pro",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [
          {
            "cache_read": 0.1,
            "cache_write": 2.5,
            "cache_write_1h": 2.5,
            "cache_write_5m": 2.5,
            "in": 2.0,
            "interval_boundary": "min_exclusive_max_inclusive",
            "label": "<=272K",
            "max": 272000,
            "min": 0,
            "null_rate_policy": "inherit_base_rate",
            "out": 10.0
          },
          {
            "cache_read": 0.2,
            "cache_write": 5.0,
            "cache_write_1h": 5.0,
            "cache_write_5m": 5.0,
            "in": 4.0,
            "interval_boundary": "min_exclusive_max_inclusive",
            "label": ">272K",
            "max": null,
            "min": 272000,
            "null_rate_policy": "inherit_base_rate",
            "out": 15.0
          }
        ],
        "tool_prices": {
          "web_search_call": 0.02
        },
        "unit": "token",
        "units": []
      }
    },
    {
      "html": "<section class=\"meth\" data-route=\"Ultra\"><header><b><span class=\"alias\">Ultra</span> OpenAI Chat</b><code>POST /v1/chat/completions</code></header><dl class=\"method-capabilities\" data-model-capabilities><div><dt>Input types</dt><dd><code>text</code></dd></div><div><dt>Output types</dt><dd><code>text</code></dd></div><div><dt>Context</dt><dd>Not specified in the catalogue</dd></div><div><dt>Max. output</dt><dd>Not specified in the catalogue</dd></div></dl><dl><div><dt>Input</dt><dd>$0.002 <em>/ 1K</em></dd></div><div><dt>Output</dt><dd>$0.01 <em>/ 1K</em></dd></div><div><dt>Cache read</dt><dd>$0.0001 <em>/ 1K</em></dd></div><div><dt>Cache write</dt><dd>$0.0025 <em>/ 1K</em></dd></div><div><dt>Cache write, 5 min</dt><dd>$0.0025 <em>/ 1K tokens</em></dd></div><div><dt>Cache write, 1 hour</dt><dd>$0.0025 <em>/ 1K tokens</em></dd></div><div><dt>web_search_call</dt><dd>$0.02 <em>per call</em></dd></div></dl><h4>Prices by request length · OpenAI Chat</h4><div class=\"tw\" data-card-table=\"tiers\"><table><thead><tr><th>Request size, tokens</th><th class=\"num\">Input</th><th class=\"num\">Output</th><th class=\"num\">Cache read</th><th class=\"num\">Cache write</th><th class=\"num\">5 min cache</th><th class=\"num\">1 hour cache</th></tr></thead><tbody><tr><td data-cell-label=\"Request size, tokens\"><span class=\"card-cell-label\">Request size, tokens</span><span class=\"card-tier-interval\">(0; 272,000]</span></td><td data-cell-label=\"Input\" class=\"num\"><span class=\"card-cell-label\">Input</span>$0.002</td><td data-cell-label=\"Output\" class=\"num\"><span class=\"card-cell-label\">Output</span>$0.01</td><td data-cell-label=\"Cache read\" class=\"num\"><span class=\"card-cell-label\">Cache read</span>$0.0001</td><td data-cell-label=\"Cache write\" class=\"num\"><span class=\"card-cell-label\">Cache write</span>$0.0025</td><td data-cell-label=\"5 min cache\" class=\"num\"><span class=\"card-cell-label\">5 min cache</span>$0.0025</td><td data-cell-label=\"1 hour cache\" class=\"num\"><span class=\"card-cell-label\">1 hour cache</span>$0.0025</td></tr><tr><td data-cell-label=\"Request size, tokens\"><span class=\"card-cell-label\">Request size, tokens</span><span class=\"card-tier-interval\">(272,000; ∞)</span></td><td data-cell-label=\"Input\" class=\"num\"><span class=\"card-cell-label\">Input</span>$0.004</td><td data-cell-label=\"Output\" class=\"num\"><span class=\"card-cell-label\">Output</span>$0.015</td><td data-cell-label=\"Cache read\" class=\"num\"><span class=\"card-cell-label\">Cache read</span>$0.0002</td><td data-cell-label=\"Cache write\" class=\"num\"><span class=\"card-cell-label\">Cache write</span>$0.005</td><td data-cell-label=\"5 min cache\" class=\"num\"><span class=\"card-cell-label\">5 min cache</span>$0.005</td><td data-cell-label=\"1 hour cache\" class=\"num\"><span class=\"card-cell-label\">1 hour cache</span>$0.005</td></tr></tbody></table></div><p class=\"note-s\">Rates in USD per 1K tokens. If no rate is set, the base rate for this method is inherited; «—» means no base rate is set.</p></section>",
      "method_identity": {
        "effective_request_model_id": "openai/gpt-6.1-terra-pro",
        "fmt": "chat",
        "http": "POST",
        "path": "/v1/chat/completions",
        "request_model_id": "openai/gpt-6.1-terra-pro",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|chat|/v1/chat/completions|openai%2Fgpt-6.1-terra-pro",
      "ordinal": 2,
      "rawMethod": {
        "cache_read": 0.1,
        "cache_write": 2.5,
        "cache_write_1h": 2.5,
        "cache_write_5m": 2.5,
        "conditional_meter": null,
        "ctx": null,
        "family": "openai",
        "fast_multiplier": 1,
        "flex_multiplier": 1,
        "fmt": "chat",
        "http": "POST",
        "img_in": null,
        "img_out": null,
        "in": 2.0,
        "input": [
          "text"
        ],
        "label": "OpenAI Chat",
        "max_out": null,
        "max_tool_calls": null,
        "out": 10.0,
        "output": [
          "text"
        ],
        "path": "/v1/chat/completions",
        "request_model_id": "openai/gpt-6.1-terra-pro",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [
          {
            "cache_read": 0.1,
            "cache_write": 2.5,
            "cache_write_1h": 2.5,
            "cache_write_5m": 2.5,
            "in": 2.0,
            "interval_boundary": "min_exclusive_max_inclusive",
            "label": "<=272K",
            "max": 272000,
            "min": 0,
            "null_rate_policy": "inherit_base_rate",
            "out": 10.0
          },
          {
            "cache_read": 0.2,
            "cache_write": 5.0,
            "cache_write_1h": 5.0,
            "cache_write_5m": 5.0,
            "in": 4.0,
            "interval_boundary": "min_exclusive_max_inclusive",
            "label": ">272K",
            "max": null,
            "min": 272000,
            "null_rate_policy": "inherit_base_rate",
            "out": 15.0
          }
        ],
        "tool_prices": {
          "web_search_call": 0.02
        },
        "unit": "token",
        "units": []
      }
    },
    {
      "html": "<section class=\"meth\" data-route=\"Ultra\"><header><b><span class=\"alias\">Ultra</span> Gemini generateContent</b><code>POST /v1beta/models/openai/gpt-6.1-terra-pro:generateContent</code></header><dl class=\"method-capabilities\" data-model-capabilities><div><dt>Input types</dt><dd><code>text</code></dd></div><div><dt>Output types</dt><dd><code>text</code></dd></div><div><dt>Context</dt><dd>Not specified in the catalogue</dd></div><div><dt>Max. output</dt><dd>Not specified in the catalogue</dd></div></dl><dl><div><dt>Input</dt><dd>$0.002 <em>/ 1K</em></dd></div><div><dt>Output</dt><dd>$0.01 <em>/ 1K</em></dd></div><div><dt>Cache read</dt><dd>$0.0001 <em>/ 1K</em></dd></div><div><dt>Cache write</dt><dd>$0.0025 <em>/ 1K</em></dd></div><div><dt>Cache write, 5 min</dt><dd>$0.0025 <em>/ 1K tokens</em></dd></div><div><dt>Cache write, 1 hour</dt><dd>$0.0025 <em>/ 1K tokens</em></dd></div><div><dt>web_search_call</dt><dd>$0.02 <em>per call</em></dd></div></dl><h4>Prices by request length · Gemini generateContent</h4><div class=\"tw\" data-card-table=\"tiers\"><table><thead><tr><th>Request size, tokens</th><th class=\"num\">Input</th><th class=\"num\">Output</th><th class=\"num\">Cache read</th><th class=\"num\">Cache write</th><th class=\"num\">5 min cache</th><th class=\"num\">1 hour cache</th></tr></thead><tbody><tr><td data-cell-label=\"Request size, tokens\"><span class=\"card-cell-label\">Request size, tokens</span><span class=\"card-tier-interval\">(0; 272,000]</span></td><td data-cell-label=\"Input\" class=\"num\"><span class=\"card-cell-label\">Input</span>$0.002</td><td data-cell-label=\"Output\" class=\"num\"><span class=\"card-cell-label\">Output</span>$0.01</td><td data-cell-label=\"Cache read\" class=\"num\"><span class=\"card-cell-label\">Cache read</span>$0.0001</td><td data-cell-label=\"Cache write\" class=\"num\"><span class=\"card-cell-label\">Cache write</span>$0.0025</td><td data-cell-label=\"5 min cache\" class=\"num\"><span class=\"card-cell-label\">5 min cache</span>$0.0025</td><td data-cell-label=\"1 hour cache\" class=\"num\"><span class=\"card-cell-label\">1 hour cache</span>$0.0025</td></tr><tr><td data-cell-label=\"Request size, tokens\"><span class=\"card-cell-label\">Request size, tokens</span><span class=\"card-tier-interval\">(272,000; ∞)</span></td><td data-cell-label=\"Input\" class=\"num\"><span class=\"card-cell-label\">Input</span>$0.004</td><td data-cell-label=\"Output\" class=\"num\"><span class=\"card-cell-label\">Output</span>$0.015</td><td data-cell-label=\"Cache read\" class=\"num\"><span class=\"card-cell-label\">Cache read</span>$0.0002</td><td data-cell-label=\"Cache write\" class=\"num\"><span class=\"card-cell-label\">Cache write</span>$0.005</td><td data-cell-label=\"5 min cache\" class=\"num\"><span class=\"card-cell-label\">5 min cache</span>$0.005</td><td data-cell-label=\"1 hour cache\" class=\"num\"><span class=\"card-cell-label\">1 hour cache</span>$0.005</td></tr></tbody></table></div><p class=\"note-s\">Rates in USD per 1K tokens. If no rate is set, the base rate for this method is inherited; «—» means no base rate is set.</p></section>",
      "method_identity": {
        "effective_request_model_id": "openai/gpt-6.1-terra-pro",
        "fmt": "gemini",
        "http": "POST",
        "path": "/v1beta/models/openai/gpt-6.1-terra-pro:generateContent",
        "request_model_id": "openai/gpt-6.1-terra-pro",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|gemini|/v1beta/models/openai/gpt-6.1-terra-pro:generateContent|openai%2Fgpt-6.1-terra-pro",
      "ordinal": 3,
      "rawMethod": {
        "cache_read": 0.1,
        "cache_write": 2.5,
        "cache_write_1h": 2.5,
        "cache_write_5m": 2.5,
        "conditional_meter": null,
        "ctx": null,
        "family": "gemini",
        "fast_multiplier": 1,
        "flex_multiplier": 1,
        "fmt": "gemini",
        "http": "POST",
        "img_in": null,
        "img_out": null,
        "in": 2.0,
        "input": [
          "text"
        ],
        "label": "Gemini generateContent",
        "max_out": null,
        "max_tool_calls": null,
        "out": 10.0,
        "output": [
          "text"
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