Custom model metadata cannot be resolved although model_catalog_json is successfully loaded 已成功加载 model_catalog_json，但仍无法解析自定义模型元数据

Open 💬 2 comments Opened Jul 11, 2026 by xiandeyi

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/<user>/.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。

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。

作为默认模型。

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:

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。

作为默认模型。

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:

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_

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