What version of Codex CLI is running?
0.143.0
What subscription do you have?
Free
Which model were you using?
MiniMax-M2.7
What platform is your computer?
windows x64
What terminal emulator and version are you using (if applicable)?
powershell and cmd
Codex doctor report
What issue are you seeing?
Summary / 问题概述
English
When using a custom OpenAI-compatible provider (MiniMax) together with model_catalog_json, Codex successfully uses the custom model for inference, but still reports:
Model metadata for MiniMax-M2.7 not found.
Defaulting to fallback metadata; this can degrade performance and cause issues.
Meanwhile:
/status correctly reports the custom model.
API requests succeed.
Tokens are consumed normally.
The custom model does not appear in /model.
This suggests that runtime model selection and metadata lookup are using different code paths.
中文
当使用 OpenAI Compatible Provider（MiniMax）并配置 model_catalog_json 后，Codex 已经能够正常调用自定义模型进行推理，但启动时仍然提示：
Model metadata for MiniMax-M2.7 not found.
Defaulting to fallback metadata; this can degrade performance and cause issues.
与此同时：
/status 能正确显示当前模型；
API 请求完全正常；
MiniMax Token 正常消耗；
/model 中仍然没有该模型。
这表明模型调用成功，但模型元数据查询失败，两者似乎并未使用同一套模型目录。
Environment / 环境
English
OS: Windows 11
Codex CLI: v0.143.0
Provider: MiniMax (OpenAI Compatible)
API: Responses API
Configuration managed by CC Switch
Model: MiniMax-M2.7
中文
操作系统：Windows 11
Codex CLI：v0.143.0
Provider：MiniMax（OpenAI Compatible）
API：Responses API
使用 CC Switch 管理配置
模型：MiniMax-M2.7
Configuration / 配置
config.toml
model = "MiniMax-M2.7"
model_provider = "minimax"
model_context_window = 1000000
[model_providers.minimax]
name = "MiniMax"
base_url = "https://api.minimaxi.com/v1"
experimental_bearer_token = "***"
wire_api = "responses"
model_catalog_json = "C:/Users//.codex/model-catalogs/custom-catalog.json"
custom-catalog.json
{
"models": [
{
"slug": "MiniMax-M2.7",
"display_name": "MiniMax-M2.7",
"description": "MiniMax",
"default_reasoning_level": "high",
"supported_reasoning_levels": [
{
"effort": "none",
"description": "Think-Off"
},
{
"effort": "high",
"description": "Deep"
}
],
"shell_type": "shell_command",
"visibility": "list",
"supported_in_api": true,
"priority": 0,
"supports_reasoning_summaries": true,
"default_reasoning_summary": "none",
"supports_parallel_tool_calls": true,
"experimental_supported_tools": [],
"input_modalities": [
"text",
"image"
]
}
]
}
Reproduction / 复现步骤
English
Configure a custom OpenAI-compatible provider.
Configure model_catalog_json.
Set
model="MiniMax-M2.7"
Start Codex.
中文
配置 OpenAI Compatible Provider。
配置 model_catalog_json。
将
model="MiniMax-M2.7"
作为默认模型。
4. 启动 Codex。
Actual Behavior / 实际表现
English
Codex starts successfully.
/status shows:
Model: MiniMax-M2.7
Model provider: MiniMax
Requests are successfully sent to MiniMax.
Token usage increases normally.
However, every startup prints:
Model metadata for MiniMax-M2.7 not found.
Defaulting to fallback metadata.
In addition, /model only lists built-in OpenAI models.
中文
Codex 能正常启动。
/status 显示：
Model: MiniMax-M2.7
Model provider: MiniMax
说明 Codex 实际已经在使用 MiniMax。
API 请求成功。
MiniMax Token 正常消耗。
但每次启动都会提示：
Model metadata for MiniMax-M2.7 not found.
Defaulting to fallback metadata.
另外，/model 中仅显示 OpenAI 官方模型，自定义模型不会出现。
Expected Behavior / 期望行为
English
Since:
the custom catalog is configured,
the model exists in the catalog,
/status already recognizes the custom model,
API requests succeed,
Codex should:
resolve metadata from model_catalog_json;
stop printing the warning;
include the custom model in /model.
中文
既然：
已配置 model_catalog_json；
自定义模型已存在于 Catalog；
/status 已能识别该模型；
API 请求已经正常；
那么希望 Codex：
能从 model_catalog_json 正确读取模型元数据；
不再输出 fallback metadata Warning；
/model 能显示该模型。
Investigation / 已完成排查
English
The following have been verified:
The provider configuration is correct.
The model is actually used for inference.
Tokens are billed by MiniMax.
model_catalog_json is configured correctly.
The custom catalog follows the documented schema.
Therefore this does not appear to be a provider configuration issue.
It appears that metadata lookup (get_model_info()) does not use the same runtime catalog that is used for model execution.
中文
已确认：
Provider 配置正确；
实际推理由 MiniMax 完成；
MiniMax Token 正常计费；
model_catalog_json 已配置；
自定义 Catalog 格式符合文档要求。
因此，这看起来不像 Provider 配置问题。
更像是：
模型执行路径已经能够识别自定义模型，而模型元数据查询 (get_model_info()) 并未使用同一份 Runtime Catalog。
Related Issues / 相关 Issue
This issue appears related to, but different from:
#24659
#19694
The difference is that the custom model is already active and being used successfully, but metadata lookup still falls back to built-in metadata.
This may indicate a regression in Codex CLI v0.143.0.
What steps can reproduce the bug?
Summary / 问题概述
English
When using a custom OpenAI-compatible provider (MiniMax) together with model_catalog_json, Codex successfully uses the custom model for inference, but still reports:
Model metadata for MiniMax-M2.7 not found.
Defaulting to fallback metadata; this can degrade performance and cause issues.
Meanwhile:
/status correctly reports the custom model.
API requests succeed.
Tokens are consumed normally.
The custom model does not appear in /model.
This suggests that runtime model selection and metadata lookup are using different code paths.
中文
当使用 OpenAI Compatible Provider（MiniMax）并配置 model_catalog_json 后，Codex 已经能够正常调用自定义模型进行推理，但启动时仍然提示：
Model metadata for MiniMax-M2.7 not found.
Defaulting to fallback metadata; this can degrade performance and cause issues.
与此同时：
/status 能正确显示当前模型；
API 请求完全正常；
MiniMax Token 正常消耗；
/model 中仍然没有该模型。
这表明模型调用成功，但模型元数据查询失败，两者似乎并未使用同一套模型目录。
Environment / 环境
English
OS: Windows 11
Codex CLI: v0.143.0
Provider: MiniMax (OpenAI Compatible)
API: Responses API
Configuration managed by CC Switch
Model: MiniMax-M2.7
中文
操作系统：Windows 11
Codex CLI：v0.143.0
Provider：MiniMax（OpenAI Compatible）
API：Responses API
使用 CC Switch 管理配置
模型：MiniMax-M2.7
Configuration / 配置
config.toml
model = "MiniMax-M2.7"
model_provider = "minimax"
model_context_window = 1000000
[model_providers.minimax]
name = "MiniMax"
base_url = "https://api.minimaxi.com/v1"
experimental_bearer_token = "***"
wire_api = "responses"
model_catalog_json = "C:/Users//.codex/model-catalogs/custom-catalog.json"
custom-catalog.json
{
"models": [
{
"slug": "MiniMax-M2.7",
"display_name": "MiniMax-M2.7",
"description": "MiniMax",
"default_reasoning_level": "high",
"supported_reasoning_levels": [
{
"effort": "none",
"description": "Think-Off"
},
{
"effort": "high",
"description": "Deep"
}
],
"shell_type": "shell_command",
"visibility": "list",
"supported_in_api": true,
"priority": 0,
"supports_reasoning_summaries": true,
"default_reasoning_summary": "none",
"supports_parallel_tool_calls": true,
"experimental_supported_tools": [],
"input_modalities": [
"text",
"image"
]
}
]
}
Reproduction / 复现步骤
English
Configure a custom OpenAI-compatible provider.
Configure model_catalog_json.
Set
model="MiniMax-M2.7"
Start Codex.
中文
配置 OpenAI Compatible Provider。
配置 model_catalog_json。
将
model="MiniMax-M2.7"
作为默认模型。
4. 启动 Codex。
Actual Behavior / 实际表现
English
Codex starts successfully.
/status shows:
Model: MiniMax-M2.7
Model provider: MiniMax
Requests are successfully sent to MiniMax.
Token usage increases normally.
However, every startup prints:
Model metadata for MiniMax-M2.7 not found.
Defaulting to fallback metadata.
In addition, /model only lists built-in OpenAI models.
中文
Codex 能正常启动。
/status 显示：
Model: MiniMax-M2.7
Model provider: MiniMax
说明 Codex 实际已经在使用 MiniMax。
API 请求成功。
MiniMax Token 正常消耗。
但每次启动都会提示：
Model metadata for MiniMax-M2.7 not found.
Defaulting to fallback metadata.
另外，/model 中仅显示 OpenAI 官方模型，自定义模型不会出现。
Expected Behavior / 期望行为
English
Since:
the custom catalog is configured,
the model exists in the catalog,
/status already recognizes the custom model,
API requests succeed,
Codex should:
resolve metadata from model_catalog_json;
stop printing the warning;
include the custom model in /model.
中文
既然：
已配置 model_catalog_json；
自定义模型已存在于 Catalog；
/status 已能识别该模型；
API 请求已经正常；
那么希望 Codex：
能从 model_catalog_json 正确读取模型元数据；
不再输出 fallback metadata Warning；
/model 能显示该模型。
Investigation / 已完成排查
English
The following have been verified:
The provider configuration is correct.
The model is actually used for inference.
Tokens are billed by MiniMax.
model_catalog_json is configured correctly.
The custom catalog follows the documented schema.
Therefore this does not appear to be a provider configuration issue.
It appears that metadata lookup (get_model_info()) does not use the same runtime catalog that is used for model execution.
中文
已确认：
Provider 配置正确；
实际推理由 MiniMax 完成；
MiniMax Token 正常计费；
model_catalog_json 已配置；
自定义 Catalog 格式符合文档要求。
因此，这看起来不像 Provider 配置问题。
更像是：
模型执行路径已经能够识别自定义模型，而模型元数据查询 (get_model_info()) 并未使用同一份 Runtime Catalog。
Related Issues / 相关 Issue
This issue appears related to, but different from:
#24659
#19694
The difference is that the custom model is already active and being used successfully, but metadata lookup still falls back to built-in metadata.
This may indicate a regression in Codex CLI v0.143.0.
What is the expected behavior?
Summary / 问题概述
English
When using a custom OpenAI-compatible provider (MiniMax) together with model_catalog_json, Codex successfully uses the custom model for inference, but still reports:
Model metadata for MiniMax-M2.7 not found.
Defaulting to fallback metadata; this can degrade performance and cause issues.
Meanwhile:
/status correctly reports the custom model.
API requests succeed.
Tokens are consumed normally.
The custom model does not appear in /model.
This suggests that runtime model selection and metadata lookup are using different code paths.
中文
当使用 OpenAI Compatible Provider（MiniMax）并配置 model_catalog_json 后，Codex 已经能够正常调用自定义模型进行推理，但启动时仍然提示：
Model metadata for MiniMax-M2.7 not found.
Defaulting to fallback metadata; this can degrade performance and cause issues.
与此同时：
/status 能正确显示当前模型；
API 请求完全正常；
MiniMax Token 正常消耗；
/model 中仍然没有该模型。
这表明模型调用成功，但模型元数据查询失败，两者似乎并未使用同一套模型目录。
Environment / 环境
English
OS: Windows 11
Codex CLI: v0.143.0
Provider: MiniMax (OpenAI Compatible)
API: Responses API
Configuration managed by CC Switch
Model: MiniMax-M2.7
中文
操作系统：Windows 11
Codex CLI：v0.143.0
Provider：MiniMax（OpenAI Compatible）
API：Responses API
使用 CC Switch 管理配置
模型：MiniMax-M2.7
Configuration / 配置
config.toml
model = "MiniMax-M2.7"
model_provider = "minimax"
model_context_window = 1000000
[model_providers.minimax]
name = "MiniMax"
base_url = "https://api.minimaxi.com/v1"
experimental_bearer_token = "***"
wire_api = "responses"
model_catalog_json = "C:/Users//.codex/model-catalogs/custom-catalog.json"
custom-catalog.json
{
"models": [
{
"slug": "MiniMax-M2.7",
"display_name": "MiniMax-M2.7",
"description": "MiniMax",
"default_reasoning_level": "high",
"supported_reasoning_levels": [
{
"effort": "none",
"description": "Think-Off"
},
{
"effort": "high",
"description": "Deep"
}
],
"shell_type": "shell_command",
"visibility": "list",
"supported_in_api": true,
"priority": 0,
"supports_reasoning_summaries": true,
"default_reasoning_summary": "none",
"supports_parallel_tool_calls": true,
"experimental_supported_tools": [],
"input_modalities": [
"text",
"image"
]
}
]
}
Reproduction / 复现步骤
English
Configure a custom OpenAI-compatible provider.
Configure model_catalog_json.
Set
model="MiniMax-M2.7"
Start Codex.
中文
配置 OpenAI Compatible Provider。
配置 model_catalog_json。
将
model="MiniMax-M2.7"
作为默认模型。
4. 启动 Codex。
Actual Behavior / 实际表现
English
Codex starts successfully.
/status shows:
Model: MiniMax-M2.7
Model provider: MiniMax
Requests are successfully sent to MiniMax.
Token usage increases normally.
However, every startup prints:
Model metadata for MiniMax-M2.7 not found.
Defaulting to fallback metadata.
In addition, /model only lists built-in OpenAI models.
中文
Codex 能正常启动。
/status 显示：
Model: MiniMax-M2.7
Model provider: MiniMax
说明 Codex 实际已经在使用 MiniMax。
API 请求成功。
MiniMax Token 正常消耗。
但每次启动都会提示：
Model metadata for MiniMax-M2.7 not found.
Defaulting to fallback metadata.
另外，/model 中仅显示 OpenAI 官方模型，自定义模型不会出现。
Expected Behavior / 期望行为
English
Since:
the custom catalog is configured,
the model exists in the catalog,
/status already recognizes the custom model,
API requests succeed,
Codex should:
resolve metadata from model_catalog_json;
stop printing the warning;
include the custom model in /model.
中文
既然：
已配置 model_catalog_json；
自定义模型已存在于 Catalog；
/status 已能识别该模型；
API 请求已经正常；
那么希望 Codex：
能从 model_catalog_json 正确读取模型元数据；
不再输出 fallback metadata Warning；
/model 能显示该模型。
Investigation / 已完成排查
English
The following have been verified:
The provider configuration is correct.
The model is actually used for inference.
Tokens are billed by MiniMax.
model_catalog_json is configured correctly.
The custom catalog follows the documented schema.
Therefore this does not appear to be a provider configuration issue.
It appears that metadata lookup (get_model_info()) does not use the same runtime catalog that is used for model execution.
中文
已确认：
Provider 配置正确；
实际推理由 MiniMax 完成；
MiniMax Token 正常计费；
model_catalog_json 已配置；
自定义 Catalog 格式符合文档要求。
因此，这看起来不像 Provider 配置问题。
更像是：
模型执行路径已经能够识别自定义模型，而模型元数据查询 (get_model_info()) 并未使用同一份 Runtime Catalog。
Related Issues / 相关 Issue
This issue appears related to, but different from:
#24659
#19694
The difference is that the custom model is already active and being used successfully, but metadata lookup still falls back to built-in metadata.
This may indicate a regression in Codex CLI v0.143.0.
Additional information
No response
What version of Codex CLI is running?
0.143.0
What subscription do you have?
Free
Which model were you using?
MiniMax-M2.7
What platform is your computer?
windows x64
What terminal emulator and version are you using (if applicable)?
powershell and cmd
Codex doctor report
What issue are you seeing?
Summary / 问题概述
English
When using a custom OpenAI-compatible provider (MiniMax) together with model_catalog_json, Codex successfully uses the custom model for inference, but still reports:
Model metadata for
MiniMax-M2.7not found.Defaulting to fallback metadata; this can degrade performance and cause issues.
Meanwhile:
/status correctly reports the custom model.
API requests succeed.
Tokens are consumed normally.
The custom model does not appear in /model.
This suggests that runtime model selection and metadata lookup are using different code paths.
中文
当使用 OpenAI Compatible Provider（MiniMax）并配置 model_catalog_json 后，Codex 已经能够正常调用自定义模型进行推理，但启动时仍然提示：
Model metadata for
MiniMax-M2.7not found.Defaulting to fallback metadata; this can degrade performance and cause issues.
与此同时：
/status 能正确显示当前模型；
API 请求完全正常；
MiniMax Token 正常消耗；
/model 中仍然没有该模型。
这表明模型调用成功，但模型元数据查询失败，两者似乎并未使用同一套模型目录。
Environment / 环境
English
OS: Windows 11
Codex CLI: v0.143.0
Provider: MiniMax (OpenAI Compatible)
API: Responses API
Configuration managed by CC Switch
Model: MiniMax-M2.7
中文
操作系统：Windows 11
Codex CLI：v0.143.0
Provider：MiniMax（OpenAI Compatible）
API：Responses API
使用 CC Switch 管理配置
模型：MiniMax-M2.7
Configuration / 配置
config.toml
model = "MiniMax-M2.7"
model_provider = "minimax"
model_context_window = 1000000
[model_providers.minimax]
name = "MiniMax"
base_url = "https://api.minimaxi.com/v1"
experimental_bearer_token = "***"
wire_api = "responses"
model_catalog_json = "C:/Users//.codex/model-catalogs/custom-catalog.json"
custom-catalog.json
{
"models": [
{
"slug": "MiniMax-M2.7",
"display_name": "MiniMax-M2.7",
"description": "MiniMax",
"default_reasoning_level": "high",
"supported_reasoning_levels": [
{
"effort": "none",
"description": "Think-Off"
},
{
"effort": "high",
"description": "Deep"
}
],
"shell_type": "shell_command",
"visibility": "list",
"supported_in_api": true,
"priority": 0,
"supports_reasoning_summaries": true,
"default_reasoning_summary": "none",
"supports_parallel_tool_calls": true,
"experimental_supported_tools": [],
"input_modalities": [
"text",
"image"
]
}
]
}
Reproduction / 复现步骤
English
Configure a custom OpenAI-compatible provider.
Configure model_catalog_json.
Set
model="MiniMax-M2.7"
Start Codex.
中文
配置 OpenAI Compatible Provider。
配置 model_catalog_json。
将
model="MiniMax-M2.7"
作为默认模型。
4. 启动 Codex。
Actual Behavior / 实际表现
English
Codex starts successfully.
/status shows:
Model: MiniMax-M2.7
Model provider: MiniMax
Requests are successfully sent to MiniMax.
Token usage increases normally.
However, every startup prints:
Model metadata for
MiniMax-M2.7not found.Defaulting to fallback metadata.
In addition, /model only lists built-in OpenAI models.
中文
Codex 能正常启动。
/status 显示：
Model: MiniMax-M2.7
Model provider: MiniMax
说明 Codex 实际已经在使用 MiniMax。
API 请求成功。
MiniMax Token 正常消耗。
但每次启动都会提示：
Model metadata for
MiniMax-M2.7not found.Defaulting to fallback metadata.
另外，/model 中仅显示 OpenAI 官方模型，自定义模型不会出现。
Expected Behavior / 期望行为
English
Since:
the custom catalog is configured,
the model exists in the catalog,
/status already recognizes the custom model,
API requests succeed,
Codex should:
resolve metadata from model_catalog_json;
stop printing the warning;
include the custom model in /model.
中文
既然：
已配置 model_catalog_json；
自定义模型已存在于 Catalog；
/status 已能识别该模型；
API 请求已经正常；
那么希望 Codex：
能从 model_catalog_json 正确读取模型元数据；
不再输出 fallback metadata Warning；
/model 能显示该模型。
Investigation / 已完成排查
English
The following have been verified:
The provider configuration is correct.
The model is actually used for inference.
Tokens are billed by MiniMax.
model_catalog_json is configured correctly.
The custom catalog follows the documented schema.
Therefore this does not appear to be a provider configuration issue.
It appears that metadata lookup (get_model_info()) does not use the same runtime catalog that is used for model execution.
中文
已确认：
Provider 配置正确；
实际推理由 MiniMax 完成；
MiniMax Token 正常计费；
model_catalog_json 已配置；
自定义 Catalog 格式符合文档要求。
因此，这看起来不像 Provider 配置问题。
更像是：
模型执行路径已经能够识别自定义模型，而模型元数据查询 (get_model_info()) 并未使用同一份 Runtime Catalog。
Related Issues / 相关 Issue
This issue appears related to, but different from:
#24659
#19694
The difference is that the custom model is already active and being used successfully, but metadata lookup still falls back to built-in metadata.
This may indicate a regression in Codex CLI v0.143.0.
What steps can reproduce the bug?
Summary / 问题概述
English
When using a custom OpenAI-compatible provider (MiniMax) together with model_catalog_json, Codex successfully uses the custom model for inference, but still reports:
Model metadata for
MiniMax-M2.7not found.Defaulting to fallback metadata; this can degrade performance and cause issues.
Meanwhile:
/status correctly reports the custom model.
API requests succeed.
Tokens are consumed normally.
The custom model does not appear in /model.
This suggests that runtime model selection and metadata lookup are using different code paths.
中文
当使用 OpenAI Compatible Provider（MiniMax）并配置 model_catalog_json 后，Codex 已经能够正常调用自定义模型进行推理，但启动时仍然提示：
Model metadata for
MiniMax-M2.7not found.Defaulting to fallback metadata; this can degrade performance and cause issues.
与此同时：
/status 能正确显示当前模型；
API 请求完全正常；
MiniMax Token 正常消耗；
/model 中仍然没有该模型。
这表明模型调用成功，但模型元数据查询失败，两者似乎并未使用同一套模型目录。
Environment / 环境
English
OS: Windows 11
Codex CLI: v0.143.0
Provider: MiniMax (OpenAI Compatible)
API: Responses API
Configuration managed by CC Switch
Model: MiniMax-M2.7
中文
操作系统：Windows 11
Codex CLI：v0.143.0
Provider：MiniMax（OpenAI Compatible）
API：Responses API
使用 CC Switch 管理配置
模型：MiniMax-M2.7
Configuration / 配置
config.toml
model = "MiniMax-M2.7"
model_provider = "minimax"
model_context_window = 1000000
[model_providers.minimax]
name = "MiniMax"
base_url = "https://api.minimaxi.com/v1"
experimental_bearer_token = "***"
wire_api = "responses"
model_catalog_json = "C:/Users//.codex/model-catalogs/custom-catalog.json"
custom-catalog.json
{
"models": [
{
"slug": "MiniMax-M2.7",
"display_name": "MiniMax-M2.7",
"description": "MiniMax",
"default_reasoning_level": "high",
"supported_reasoning_levels": [
{
"effort": "none",
"description": "Think-Off"
},
{
"effort": "high",
"description": "Deep"
}
],
"shell_type": "shell_command",
"visibility": "list",
"supported_in_api": true,
"priority": 0,
"supports_reasoning_summaries": true,
"default_reasoning_summary": "none",
"supports_parallel_tool_calls": true,
"experimental_supported_tools": [],
"input_modalities": [
"text",
"image"
]
}
]
}
Reproduction / 复现步骤
English
Configure a custom OpenAI-compatible provider.
Configure model_catalog_json.
Set
model="MiniMax-M2.7"
Start Codex.
中文
配置 OpenAI Compatible Provider。
配置 model_catalog_json。
将
model="MiniMax-M2.7"
作为默认模型。
4. 启动 Codex。
Actual Behavior / 实际表现
English
Codex starts successfully.
/status shows:
Model: MiniMax-M2.7
Model provider: MiniMax
Requests are successfully sent to MiniMax.
Token usage increases normally.
However, every startup prints:
Model metadata for
MiniMax-M2.7not found.Defaulting to fallback metadata.
In addition, /model only lists built-in OpenAI models.
中文
Codex 能正常启动。
/status 显示：
Model: MiniMax-M2.7
Model provider: MiniMax
说明 Codex 实际已经在使用 MiniMax。
API 请求成功。
MiniMax Token 正常消耗。
但每次启动都会提示：
Model metadata for
MiniMax-M2.7not found.Defaulting to fallback metadata.
另外，/model 中仅显示 OpenAI 官方模型，自定义模型不会出现。
Expected Behavior / 期望行为
English
Since:
the custom catalog is configured,
the model exists in the catalog,
/status already recognizes the custom model,
API requests succeed,
Codex should:
resolve metadata from model_catalog_json;
stop printing the warning;
include the custom model in /model.
中文
既然：
已配置 model_catalog_json；
自定义模型已存在于 Catalog；
/status 已能识别该模型；
API 请求已经正常；
那么希望 Codex：
能从 model_catalog_json 正确读取模型元数据；
不再输出 fallback metadata Warning；
/model 能显示该模型。
Investigation / 已完成排查
English
The following have been verified:
The provider configuration is correct.
The model is actually used for inference.
Tokens are billed by MiniMax.
model_catalog_json is configured correctly.
The custom catalog follows the documented schema.
Therefore this does not appear to be a provider configuration issue.
It appears that metadata lookup (get_model_info()) does not use the same runtime catalog that is used for model execution.
中文
已确认：
Provider 配置正确；
实际推理由 MiniMax 完成；
MiniMax Token 正常计费；
model_catalog_json 已配置；
自定义 Catalog 格式符合文档要求。
因此，这看起来不像 Provider 配置问题。
更像是：
模型执行路径已经能够识别自定义模型，而模型元数据查询 (get_model_info()) 并未使用同一份 Runtime Catalog。
Related Issues / 相关 Issue
This issue appears related to, but different from:
#24659
#19694
The difference is that the custom model is already active and being used successfully, but metadata lookup still falls back to built-in metadata.
This may indicate a regression in Codex CLI v0.143.0.
What is the expected behavior?
Summary / 问题概述
English
When using a custom OpenAI-compatible provider (MiniMax) together with model_catalog_json, Codex successfully uses the custom model for inference, but still reports:
Model metadata for
MiniMax-M2.7not found.Defaulting to fallback metadata; this can degrade performance and cause issues.
Meanwhile:
/status correctly reports the custom model.
API requests succeed.
Tokens are consumed normally.
The custom model does not appear in /model.
This suggests that runtime model selection and metadata lookup are using different code paths.
中文
当使用 OpenAI Compatible Provider（MiniMax）并配置 model_catalog_json 后，Codex 已经能够正常调用自定义模型进行推理，但启动时仍然提示：
Model metadata for
MiniMax-M2.7not found.Defaulting to fallback metadata; this can degrade performance and cause issues.
与此同时：
/status 能正确显示当前模型；
API 请求完全正常；
MiniMax Token 正常消耗；
/model 中仍然没有该模型。
这表明模型调用成功，但模型元数据查询失败，两者似乎并未使用同一套模型目录。
Environment / 环境
English
OS: Windows 11
Codex CLI: v0.143.0
Provider: MiniMax (OpenAI Compatible)
API: Responses API
Configuration managed by CC Switch
Model: MiniMax-M2.7
中文
操作系统：Windows 11
Codex CLI：v0.143.0
Provider：MiniMax（OpenAI Compatible）
API：Responses API
使用 CC Switch 管理配置
模型：MiniMax-M2.7
Configuration / 配置
config.toml
model = "MiniMax-M2.7"
model_provider = "minimax"
model_context_window = 1000000
[model_providers.minimax]
name = "MiniMax"
base_url = "https://api.minimaxi.com/v1"
experimental_bearer_token = "***"
wire_api = "responses"
model_catalog_json = "C:/Users//.codex/model-catalogs/custom-catalog.json"
custom-catalog.json
{
"models": [
{
"slug": "MiniMax-M2.7",
"display_name": "MiniMax-M2.7",
"description": "MiniMax",
"default_reasoning_level": "high",
"supported_reasoning_levels": [
{
"effort": "none",
"description": "Think-Off"
},
{
"effort": "high",
"description": "Deep"
}
],
"shell_type": "shell_command",
"visibility": "list",
"supported_in_api": true,
"priority": 0,
"supports_reasoning_summaries": true,
"default_reasoning_summary": "none",
"supports_parallel_tool_calls": true,
"experimental_supported_tools": [],
"input_modalities": [
"text",
"image"
]
}
]
}
Reproduction / 复现步骤
English
Configure a custom OpenAI-compatible provider.
Configure model_catalog_json.
Set
model="MiniMax-M2.7"
Start Codex.
中文
配置 OpenAI Compatible Provider。
配置 model_catalog_json。
将
model="MiniMax-M2.7"
作为默认模型。
4. 启动 Codex。
Actual Behavior / 实际表现
English
Codex starts successfully.
/status shows:
Model: MiniMax-M2.7
Model provider: MiniMax
Requests are successfully sent to MiniMax.
Token usage increases normally.
However, every startup prints:
Model metadata for
MiniMax-M2.7not found.Defaulting to fallback metadata.
In addition, /model only lists built-in OpenAI models.
中文
Codex 能正常启动。
/status 显示：
Model: MiniMax-M2.7
Model provider: MiniMax
说明 Codex 实际已经在使用 MiniMax。
API 请求成功。
MiniMax Token 正常消耗。
但每次启动都会提示：
Model metadata for
MiniMax-M2.7not found.Defaulting to fallback metadata.
另外，/model 中仅显示 OpenAI 官方模型，自定义模型不会出现。
Expected Behavior / 期望行为
English
Since:
the custom catalog is configured,
the model exists in the catalog,
/status already recognizes the custom model,
API requests succeed,
Codex should:
resolve metadata from model_catalog_json;
stop printing the warning;
include the custom model in /model.
中文
既然：
已配置 model_catalog_json；
自定义模型已存在于 Catalog；
/status 已能识别该模型；
API 请求已经正常；
那么希望 Codex：
能从 model_catalog_json 正确读取模型元数据；
不再输出 fallback metadata Warning；
/model 能显示该模型。
Investigation / 已完成排查
English
The following have been verified:
The provider configuration is correct.
The model is actually used for inference.
Tokens are billed by MiniMax.
model_catalog_json is configured correctly.
The custom catalog follows the documented schema.
Therefore this does not appear to be a provider configuration issue.
It appears that metadata lookup (get_model_info()) does not use the same runtime catalog that is used for model execution.
中文
已确认：
Provider 配置正确；
实际推理由 MiniMax 完成；
MiniMax Token 正常计费；
model_catalog_json 已配置；
自定义 Catalog 格式符合文档要求。
因此，这看起来不像 Provider 配置问题。
更像是：
模型执行路径已经能够识别自定义模型，而模型元数据查询 (get_model_info()) 并未使用同一份 Runtime Catalog。
Related Issues / 相关 Issue
This issue appears related to, but different from:
#24659
#19694
The difference is that the custom model is already active and being used successfully, but metadata lookup still falls back to built-in metadata.
This may indicate a regression in Codex CLI v0.143.0.
Additional information
No response