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作成日: 2026年1月31日

使用モデル GPT-5.2 Thinking by Chat01

質問

我本地xubunt24.04已经安装opencode(https://github.com/anomalyco/opencode/),已经配置了claude sonnet和gpt5.2,请给出gemini3模型models中的options如何配置，部分配置内容如下
{
"$schema":"https://opencode.ai/config.json",
"provider":{
"Elysiz":{
"npm":"@ai-sdk/openai-compatible",
"name":"Elysiz",
"options":{
"baseURL":"https://elysia.h-e.top/v1",
"apiKey":"sk-SSEr9Vxk9rOA50xZudDoWmm6SOxuQikG"
},
"models":{
"claude-4.5-sonnet-real":{
"name":"claude-4.5-sonnet-real",
"attachment":true,
"reasoning":true,
"tool_call":true,
"temperature":true,
"modalities":{
"input":[
"text",
"image"
],
"output":[
"text"
]
},
"cost":{
"input":3,
"output":15,
"cache_read":0.3,
"cache_write":3.75
},
"limit":{
"context":200000,
"output":64000
},
"options":{
"thinking":{
"type":"enabled",
"budgetTokens":32000
}
}
},
"claude-4.5-sonnet":{
"name":"claude-4.5-sonnet",
"attachment":true,
"reasoning":true,
"tool_call":true,
"temperature":true,
"modalities":{
"input":[
"text",
"image"
],
"output":[
"text"
]
},
"cost":{
"input":3,
"output":15,
"cache_read":0.3,
"cache_write":3.75
},
"limit":{
"context":200000,
"output":64000
},
"options":{
"thinking":{
"type":"enabled",
"budgetTokens":32000
}
}
},
"gemini-3-pro-preview":{
"name":"gemini-3-pro-preview",
"thinking":true
},
"gpt-5.2":{
"name":"gpt-5.2",
"attachment":true,
"reasoning":true,
"tool_call":true,
"temperature":false,
"modalities":{
"input":[
"text",
"image"
],
"output":[
"text"
]
},
"cost":{
"input":1.75,
"output":14,
"cache_read":0.175
},
"limit":{
"context":400000,
"output":128000
},
"options":{
"store":false,
"reasoningEffort":"xhigh",
"textVerbosity":"medium",
"reasoningSummary":"auto",
"include":[
"reasoning.encrypted_content"
]
}
}
}
},
"BoHe":{
"npm":"@ai-sdk/openai-compatible",
"name":"BoHe",
"options":{
"baseURL":"https://x666.me/v1",
"apiKey":"sk-IQrzxa9pkDC7igKlVI83AHGDmIdfEe6"
},
"models":{
"gpt-5.2-high":{
"name":"gpt-5.2-high",
"attachment":true,
"reasoning":true,
"tool_call":true,
"temperature":false,
"release_date":"2025-12-11",
"modalities":{
"input":[
"text",
"image"
],
"output":[
"text"
]
},
"cost":{
"input":1.75,
"output":14,
"cache_read":0.175
},
"limit":{
"context":400000,
"output":128000
},
"options":{
"store":false,
"reasoningEffort":"xhigh",
"textVerbosity":"medium",
"reasoningSummary":"auto",
"include":[
"reasoning.encrypted_content"
]
}
},
"gemini-3-pro-preview-bs":{
"name":"gemini-3-pro-preview-bs"
},
"gpt-5.2":{
"name":"gpt-5.2",
"attachment":true,
"reasoning":true,
"tool_call":true,
"temperature":false,
"modalities":{
"input":[
"text",
"image"
],
"output":[
"text"
]
},
"cost":{
"input":1.75,
"output":14,
"cache_read":0.175
},
"limit":{
"context":400000,
"output":128000
},
"options":{
"store":false,
"reasoningEffort":"xhigh",
"textVerbosity":"medium",
"reasoningSummary":"auto",
"include":[
"reasoning.encrypted_content"
]
}
}
}
},
"B4U":{
"npm":"@ai-sdk/openai-compatible",
"name":"B4U",
"options":{
"baseURL":"https://b4u.qzz.io/v1",
"apiKey":"sk-T51gpwsP5bze6fd7lMpcbRzv0wKX0S"
},
"models":{
"claude-4.5-sonnet":{
"name":"claude-4.5-sonnet",
"attachment":true,
"reasoning":true,
"tool_call":true,
"temperature":true,
"modalities":{
"input":[
"text",
"image"
],
"output":[
"text"
]
},
"cost":{
"input":3,
"output":15,
"cache_read":0.3,
"cache_write":3.75
},
"limit":{
"context":200000,
"output":64000
},
"options":{
"thinking":{
"type":"enabled",
"budgetTokens":32000
}
}
},
"claude-4.5-sonnet-think":{
"name":"claude-4.5-sonnet-think",
"attachment":true,
"reasoning":true,
"tool_call":true,
"temperature":true,
"modalities":{
"input":[
"text",
"image"
],
"output":[
"text"
]
},
"cost":{
"input":3,
"output":15,
"cache_read":0.3,
"cache_write":3.75
},
"limit":{
"context":200000,
"output":64000
},
"options":{
"thinking":{
"type":"enabled",
"budgetTokens":32000
}
}
}
}
},
"QAQ":{
"npm":"@ai-sdk/openai-compatible",
"name":"QAQ",
"options":{
"baseURL":"https://ai.qaq.al",
"apiKey":"sk-df87dc1f3a78b272243b198e48b53fc3c0e"
},
"models":{
"gpt-5.2-codex":{
"name":"gpt-5.2-codex",
"attachment":true,
"reasoning":true,
"tool_call":true,
"temperature":false,
"modalities":{
"input":[
"text",
"image"
],
"output":[
"text"
]
},
"cost":{
"input":1.25,
"output":10,
"cache_read":0.125
},
"limit":{
"context":400000,
"output":128000
},
"options":{
"store":false,
"reasoningEffort":"high",
"textVerbosity":"medium",
"reasoningSummary":"auto",
"include":[
"reasoning.encrypted_content"
]
}
},
"gpt-5.2":{
"name":"gpt-5.2",
"attachment":true,
"reasoning":true,
"tool_call":true,
"temperature":false,
"release_date":"2025-12-11",
"modalities":{
"input":[
"text",
"image"
],
"output":[
"text"
]
},
"cost":{
"input":1.75,
"output":14,
"cache_read":0.175
},
"limit":{
"context":400000,
"output":128000
},
"options":{
"store":false,
"reasoningEffort":"xhigh",
"textVerbosity":"medium",
"reasoningSummary":"auto",
"include":[
"reasoning.encrypted_content"
]
}
}
}
}
}
}

思考

Providing details for OpenAI-compatible gateway configuration

I’ll share a minimal yet useful response with relevant citations. I'll mention that OpenCode uses options like thinkingLevel and includeThoughts for Google Gemini and model selection format as providerID/modelID:variant. I'll clarify Gemini OpenAI compatibility and its limitations with medium settings. I'll also note providerOptions from the Vercel AI SDK docs.

Creating response and citing relevant sources

I'll begin by noting that the API key has been exposed, recommending immediate revocation: "你贴的 sk-... 已暴露". Then, I'll proceed with two options:

###方案 A: 使用 OpenCode 的 Google Gemini provider

  • Use thinkingLevel and includeThoughts.

I'll also make sure to mention the use of providerOptions in tools like @ai-sdk/openai-compatible.

Thought for 6m 13s

回答

先提醒一句：你把好几个 真实 API Key（sk-…） 直接贴在对话里了——这等同于“已泄露”。建议你立刻去对应平台 撤销/轮换这些 Key，然后把配置里的 Key 改成从环境变量读取（或用 opencode 的 auth 存储），不要再明文出现在配置/截图/聊天记录里。

结论：Gemini 3 的 options 主要就两种写法（看你走哪条接口）

A) 走 OpenCode 内置的 Google Gemini 适配（推荐）

OpenCode 对 Google Gemini 的“思考档位”控制用的是：

  • thinkingLevel: "low" / "high"
  • includeThoughts: true/false (DeepWiki)

你可以在 models.gemini-3-pro-preview.options 里这样写（示例）：

json
"gemini-3-pro-preview": {
  "name": "gemini-3-pro-preview",
  "attachment": true,
  "reasoning": true,
  "tool_call": true,
  "temperature": true,
  "modalities": { "input": ["text","image"], "output": ["text"] },

  "options": {
    "thinkingLevel": "high",
    "includeThoughts": false
  },

  "variants": {
    "low":  { "thinkingLevel": "low",  "includeThoughts": false },
    "high": { "thinkingLevel": "high", "includeThoughts": false }
  }
}

调用时你还可以用 providerID/modelID:variant 这种格式切档位，比如：
Elysiz/gemini-3-pro-preview:high（variant 语法就是这样设计的）(DeepWiki)

⚠️ 注意：只有当你的“Gemini 真的是按 Google Gemini 适配链路在跑”时，这组 thinkingLevel/includeThoughts 才会被正确翻译成 Gemini 的参数。

B) 走 OpenAI-Compatible（OpenAI 兼容）接口去打 Gemini（你现在用的 @ai-sdk/openai-compatible 更像这类）

如果你的后端是 Gemini OpenAI 兼容端点（例如 Google 官方 .../v1beta/openai/，或你的网关完整兼容这个语义），那么控制思考强度应该用 OpenAI 的 reasoning_effort 语义：

在 opencode 的 model options 里你可以按你现有风格（camelCase）先这样配：

json
"gemini-3-pro-preview": {
  "name": "gemini-3-pro-preview",
  "options": {
    "reasoningEffort": "high"
  },
  "variants": {
    "low":  { "reasoningEffort": "low" },
    "high": { "reasoningEffort": "high" }
  }
}

如果你还想要 Gemini 的 include_thoughts（把“thought summaries/签名”等也带出来）

Google 的 OpenAI 兼容文档给的方式是通过 extra_body 传：

json
"extra_body": {
  "google": {
    "thinking_config": {
      "thinking_level": "low",
      "include_thoughts": true
    }
  }
}

并且强调：reasoning_effort 和 thinking_level/thinking_budget 不能同时用（功能重叠会冲突）。(Google AI for Developers)

所以你在 opencode 里要么用 reasoningEffort，要么改用（等价的）extra_body.google.thinking_config；不要两套一起上。

兼容性提醒：extra_body 是否会被你的网关/后端接受，取决于它是不是按 Google 文档实现的 OpenAI-compat。最稳的通常是先只用 reasoningEffort=low/high。

你该怎么选

  • 如果你能用 OpenCode 的 Google/Gemini 原生适配：优先用 A（thinkingLevel/includeThoughts），最贴合 OpenCode 对 Gemini 的变体体系。(DeepWiki)
  • 如果你必须走 OpenAI-Compatible 网关：优先用 B（reasoningEffort=low/high）；需要 thoughts 再考虑 extra_body，且不要和 reasoningEffort 混用。(Google AI for Developers)

如果你告诉我：你这个 baseURL 背后到底是 Google 官方 v1beta/openai、还是某个多模型网关（例如把 Gemini 转成 OpenAI 协议的那种），我可以把上面那段 options 精确到“应该用 thinkingLevel 还是 reasoningEffort，字段名用 camelCase 还是 snake_case”。

質問

我使用的是“penAI-Compatible 网关”，请给个gemin3的model中options,如下我写的如何，有不对或改进的请指出，并列出完整示例
"gemini-3-pro-preview":{
"name":"gemini-3-pro-preview",
"options": {
"reasoningEffort": "high"
},
"variants": {
"low": { "reasoningEffort": "low" },
"high": { "reasoningEffort": "high" }
}
},

思考

Considering compatibility for reasoningEffort parameter

The AI SDK docs don’t mention "reasoningEffort" but reference "providerOptions" for setting provider-specific options. In OpenCode, options are passed for each provider. I could adjust for snake_case if needed, though OpenCode internally uses its own transformations. I need to confirm these provider-specific transformations.

Determining compatibility for reasoning_effort parameter

Based on OpenAI's docs, reasoning models use reasoning.effort, but OpenCode uses reasoningEffort. For Gemini with openai-compatible gateway, the API expects reasoning_effort. To avoid confusion, I'll directly pass reasoning_effort: "high" as an option, ensuring it appears correctly in the request body.

Choosing reasoning_effort options for Gemini gateway

I'm thinking it might be safer to provide both "reasoning_effort" and "reasoningEffort" in the options, but that could cause conflicts if the gateway rejects unknown parameters. To be safe, I’ll stick with "reasoning_effort" since it’s documented. I’ll also include "low", "high", and "minimal" variants, but avoid "medium" and "none" since they aren't supported.

Clarifying conflicting options and adding variants

If they want to include thoughts, they’ll need to use extra_body.google.thinking_config instead of reasoning_effort. I’ll suggest a new variant with thinking_level and include_thoughts. Since they want options for Gemini3, I’ll include low/high variants, and explain differences for OpenCode and OpenAI-compatible providers. I’ll also provide a complete example with attachment and other possible configurations.

Providing a complete config example with options

I’ll offer a complete model configuration with placeholders for limit and cost, but avoid providing uncertain values. For clarity, I will mention environmental variables like {env:MY_API_KEY} instead of actual API keys, and provide guidance on options vs variants. The snippet should use reasoning_effort for OpenAI compatibility, with examples for minimal and optional thought summaries. The focus will be on clean, complete configuration including necessary fields, with proper citations.

Providing configuration advice on gemini-3-pro

The user's model structure is mostly fine, but I recommend switching reasoningEffort to reasoning_effort to align with the OpenAI-compatible specification. I'll explain supported values as minimal, low, and high, with medium/none unsupported. I'll provide a complete model example with those variations and a full configuration snippet. Also, we'll suggest adding temperature as it changes model behavior. I'll adjust their typo from "penAI" to "OpenAI" too.

Thought for 2m 33s

回答

你这段结构（options + variants）写法本身没问题，唯一需要重点改的是：如果你后端真的是 Gemini 的 OpenAI-Compatible（chat/completions）接口语义，那控制思考强度的请求字段在协议里是 reasoning_effort（下划线），不是 reasoningEffort（驼峰）。Google 的 OpenAI 兼容文档示例用的也是 reasoning_effort，并且明确了 Gemini 3 不支持 medium、也不能关闭 thinking。 (Google AI for Developers)

所以建议你把配置改成下面这样（并顺手加一个 minimal 变体，兼容更多档位）：

你这段该怎么改（核心改动：改成 reasoning_effort）

json
"gemini-3-pro-preview": {
  "name": "gemini-3-pro-preview",
  "options": {
    "reasoning_effort": "high"
  },
  "variants": {
    "minimal": { "reasoning_effort": "minimal" },
    "low":     { "reasoning_effort": "low" },
    "high":    { "reasoning_effort": "high" }
  }
}

为什么这样改

  • Gemini OpenAI compatibility 的 thinking 映射表用的是 reasoning_effort，且 Gemini 3 Pro：medium 会报错；none 也不能用于 Gemini 3（不能关 thinking）。(Google AI for Developers)
  • OpenCode 的 variants 机制就是让你用 provider/model:variant 切档位，你的写法是对的。(OpenCode)

可选增强：如果你还想拿到 thought summaries（include_thoughts）

Google 文档说可以用 extra_body.google.thinking_config，但注意：它和 reasoning_effort 不能同时用（功能重叠会冲突）。(Google AI for Developers)

你可以额外做一个“带 thoughts”的 variant（不要再放 reasoning_effort）：

json
"variants": {
  "high": { "reasoning_effort": "high" },

  "high_thoughts": {
    "extra_body": {
      "google": {
        "thinking_config": {
          "thinking_level": "high",
          "include_thoughts": true
        }
      }
    }
  }
}

（thinking_level / include_thoughts 这一套就是 Google 在 OpenAI compat 下的扩展字段。）(Google AI for Developers)

完整示例（放到你的某个 OpenAI-Compatible provider 里）

下面我用你现有结构写一个“可直接抄”的完整 model entry；注意我把 apiKey 改成环境变量写法，避免明文泄露（OpenCode 文档也推荐这样配）。(open-code.ai)

jsonc
{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "Elysiz": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Elysiz",
      "options": {
        "baseURL": "https://elysia.h-e.top/v1",
        "apiKey": "{env:ELYSIZ_API_KEY}"
      },
      "models": {
        "gemini-3-pro-preview": {
          "name": "gemini-3-pro-preview",

          // 下面这些能力开关你可留可不留；不影响 reasoning_effort
          "attachment": true,
          "reasoning": true,
          "tool_call": true,
          "temperature": true,
          "modalities": { "input": ["text", "image"], "output": ["text"] },

          // 默认：high
          "options": {
            "reasoning_effort": "high"
          },

          // 切换：Elysiz/gemini-3-pro-preview:low 之类
          "variants": {
            "minimal": { "reasoning_effort": "minimal" },
            "low":     { "reasoning_effort": "low" },
            "high":    { "reasoning_effort": "high" },

            // 可选：要 thought summaries 就用这个（不要和 reasoning_effort 同时用）
            "high_thoughts": {
              "extra_body": {
                "google": {
                  "thinking_config": {
                    "thinking_level": "high",
                    "include_thoughts": true
                  }
                }
              }
            }
          }
        }
      }
    }
  }
}

最后一个实用提醒

你之前贴出来的那堆 sk-... 已经算“公开泄露”了：建议立刻去各网关/平台撤销并重建，然后只用 {env:...} 或 /connect 存到 OpenCode 的 auth 文件里（文档提到凭据会存到本地 auth.json）。(OpenCode)

如果你愿意，把你网关实际对外的 OpenAI 路径（是 /v1/chat/completions 还是别的）贴一行（不要带 key），我可以再帮你确认：OpenCode 这边到底是“原样透传字段”还是会做 camelCase→snake_case 映射，从而决定到底用 reasoning_effort 还是两者都要兼容。

質問

我的确使用的是OpenAI-Compatible方式接入中转站的gemini,我怎么才能知道中转站有没有按照google约定的，你提到“Google 的 OpenAI 兼容文档示例用的也是 reasoning_effort，并且明确了 Gemini 3 不支持 medium、也不能关闭 thinking”，请问是否默认就是hign,如下配置是不也可行
"gemini-3-pro-preview-bs":{
"name":"gemini-3-pro-preview-bs",
"options": {
"reasoningEffort": "high"
},
"variants": {
"low": { "reasoningEffort": "low" },
"high": { "reasoningEffort": "high" }
}
},

我要知道的是只要开启了thinking模式，不要降智就行，我要这样
的配置

思考

Clarifying configuration for openai-compatible and Google settings

User uses an openai-compatible gateway, meaning parameters pass as-is, including reasoningEffort without conversion to reasoning_effort. If using Google docs as reference, you'd need to use reasoning_effort instead for compatibility. However, there’s a chance the proxy might convert it, so testing or provider confirmation is necessary. For Gemini 3, thinking is always on, but reasoning_effort controls the level.

Clarifying configuration details for proxy and reasoning effort

To ensure specified behavior, setting reasoningEffort high is ideal if you want "不要降智" (no degradation). Gemini 3 Pro doesn't support medium or disabling thinking. If not explicitly set, the model defaults. For the config, using reasoning_effort is recommended due to OpenCode’s raw parameter pass-through, as Google requires that specific case.

Testing gateway compatibility & providing configuration example

To check if the gateway follows Google’s rules, test with:

  1. reasoning_effort: "medium"—error expected, success means it’s not Google-compatible.
  2. reasoning_effort: "none"—should error, if accepted, it's not raw Google.
  3. Test with "extra_body.google.thinking_config.include_thoughts": true, checking for thought signatures.

I'll also provide a configuration example: base options empty, with google_high and proxy_high variants, ensuring no overlap.

Setting options for consistent high reasoning effort

To simplify, use reasoning_effort: "high" in base options, ensuring the user always sets high without worrying about the format (snake or camel). If the gateway can’t parse it, they'll get an error and can adjust to camel. If unsure, use a "google_high" variant to ensure the configuration stays enforced.

Thought for 4m 25s

回答

你现在的目标其实就两点：

  1. 不要靠默认值（不一定是 high）
  2. 保证发到中转站的字段名，确实会被它识别并传到 Gemini

1) Gemini 3 的 thinking 默认是 high 吗？

不是。 Google 的 OpenAI 兼容文档写得很明确：如果你不传 reasoning_effort，Gemini 会用“该模型的默认 level / budget”。默认到底是啥取决于模型/服务端配置，不保证是 high。并且 Gemini 3 Pro 不支持 medium，也不能关闭 thinking。 (Google AI for Developers)

所以：想“不要降智”，就显式设置 high。

2) 你写的 reasoningEffort（驼峰）是否可行？

这要看你的中转站有没有做字段映射。

关键点：OpenCode 用的 @ai-sdk/openai-compatible 会“原样”发送参数，不会自动 camelCase→snake_case。OpenCode 官方 PR 里专门提到了这一点（例如 budgetTokens 不会自动变成 budget_tokens）。(GitHub)

而 Google 的 OpenAI 兼容接口示例使用的是 reasoning_effort（下划线）。(Google AI for Developers)

因此：

  • 如果中转站严格按 Google 的 OpenAI 兼容实现：你写 reasoningEffort 很可能无效（被忽略）或直接报 unknown field。
  • 如果中转站做了兼容映射：reasoningEffort 也可能“碰巧可用”。

3) 怎么快速判断中转站有没有按 Google 约定实现？

用“黑盒探测”最靠谱（不需要看中转站代码）：

测试 A：reasoning_effort = "medium" 应该报错（Gemini 3 Pro 不支持）

Google 文档：Gemini 3 Pro 的 medium 是 ERROR。(Google AI for Developers)

bash
curl "$BASE_URL/v1/chat/completions" \
  -H "Authorization: Bearer $KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model":"gemini-3-pro-preview",
    "reasoning_effort":"medium",
    "messages":[{"role":"user","content":"1+1=?"}]
  }'
  • 如果它按文档报错 → 基本确认它在按 Google 语义走（或至少做了等价校验）。
  • 如果它不报错 → 说明它没按 Google 这条约定实现（可能忽略字段、或把 medium 当 low/high）。

测试 B：对比 low vs high 的 token/时延/质量差异

同样 prompt 分别发 reasoning_effort:"low" 与 "high"；通常 high 会更慢、token 更多、推理更“稳”。（这不是 100% 量化，但能辅助判断。）(Google AI for Developers)

4) 你要的“只要开 thinking、不要降智”的推荐配置（完整示例）

我建议你直接用 snake_case 的 reasoning_effort，并且再给一个 驼峰 fallback variant，这样不需要你纠结中转站到底吃哪个字段——用哪个 variant 能跑就用哪个。

注意：不要在同一个请求里同时带 reasoning_effort 和 reasoningEffort，有些实现会直接报 unknown/ambiguous。

json
"gemini-3-pro-preview-bs": {
  "name": "gemini-3-pro-preview-bs",

  "attachment": true,
  "reasoning": true,
  "tool_call": true,
  "temperature": true,
  "modalities": { "input": ["text", "image"], "output": ["text"] },

  "variants": {
    "high": { "reasoning_effort": "high" },
    "low":  { "reasoning_effort": "low" },

    "high_camel": { "reasoningEffort": "high" },
    "low_camel":  { "reasoningEffort": "low" }
  }
}

使用时你就指定 variant（OpenCode 的 variants 机制就是这么用的）：(OpenCode)

  • BoHe/gemini-3-pro-preview-bs:high （优先，符合 Google 文档字段）
  • 如果不行就试：BoHe/gemini-3-pro-preview-bs:high_camel

额外一个小建议（避免“降智/怪行为”）

Google Gemini 3 的文档建议：Gemini 3 尽量保持 temperature 默认值（≈1.0），把 temperature 调到 <1 可能出现循环/性能下降。你现在 temperature:true 代表允许调，但如果你追求稳定，“不手动乱调”就行。(Google AI for Developers)

如果你把中转站的 OpenAI endpoint 路径（比如到底是 /v1/chat/completions 还是别的）和它对未知字段的典型报错样例（去掉 key）贴一段，我还能帮你判断：应该把默认 variant 固定到 high 还是 high_camel 更稳。

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