# Model Providers

> Select models by capabilities, access scope, and pricing, and find the relevant configuration entrance.

Source: https://doc.fastgpt.io/en/guide/workspace/models

Open **Account → Model provider** (available in Commercial Edition and FastGPT Cloud; Community Edition manages models under the Admin console) to inspect the active model catalog, filter by provider and model category, and check tiered token pricing. When `feConfigs.enable_team_model` is enabled, the page exposes five team model management tabs; otherwise, it displays the **Available models** catalog.

![Model routing and catalog invocation flow](https://cdn.jsdelivr.net/gh/labring/fastgpt-img@main/diagrams/model-routing.en.light.svg)

## Choose for the task

* Use language models for conversations and summaries. Verify tool calling, vision, and reasoning against model labels and configuration.
* Use embedding models for knowledge indexing. Retrieval reranking requires a configured reranker.
* Confirm member access and quota before selecting a model in an application, then run a small sample.

| Model Category               | Where It Is Used                                                                                        | Key Attributes to Verify                                                                                                                                                                                    |
| ---------------------------- | ------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Language Model (LLM)**     | Chat Agent, Agent V2, Workflow AI Chat / Question Classification / Content Extraction / Query Extension | Max context window, max output tokens, Function Calling support, vision/audio badges, reasoning support, and tiered input/output rates per million tokens (M Tokens)                                        |
| **Embedding Model**          | Vector index building and semantic search in datasets                                                   | Vector dimensions, chunk token limit, and unit price per million tokens (after creation, you can switch the **Index Model** in the dataset's right-side info panel to rebuild vector indexes automatically) |
| **Rerank Model**             | Second-stage relevance reranking during knowledge retrieval                                             | Context window and unit price per million tokens                                                                                                                                                            |
| **Speech Model (STT / TTS)** | Microphone speech-to-text and assistant voice synthesis                                                 | Supported languages, voice presets, and unit price (per 1M characters for TTS, per 60 seconds for STT)                                                                                                      |

Display names, model instance identifiers, and provider model names serve different purposes. Use the exact identifier required by an API or configuration contract. Pricing and provider support follow the current environment. System models deduct AI points according to the listed rates, while team-configured models are free of platform points.

![Select an available team model and configure parameters in an application](https://cdn.jsdelivr.net/gh/labring/fastgpt-img@main/optimized/current/ai-model-selector.png.webp)

## Team and platform configuration

Members granted the **Install Models** permission under **Account → Team management → Permissions** (see [Members, Departments, Groups, and Permissions](/en/guide/workspace/team/team_roles_permissions)) can configure team models when `feConfigs.enable_team_model` is enabled. System models are managed by the self-hosted `root` system administrator account (which displays the **Admin** entry at the bottom of the left navigation bar; FastGPT Cloud does not expose this entry to tenants) under **Admin → System Resources → System Models** (**Admin → System Models** in Community Edition). See [model configuration](/en/self-host/config/model/intro) for self-hosted administration.

* **Available Model Catalog**: Displayed in all environments; filter by provider (such as Qwen, DeepSeek, OpenAI, GLM, MiniMax) and model type, and hover over pricing cells to inspect tiered input/output rates.
* **Team Model Administration (when `feConfigs.enable_team_model` is enabled under Account → Model provider)**: Exposes **Available models**, **Model configuration**, **Model provider**, **Call log**, and **Monitoring** tabs.
* **Platform System Model Administration (under Admin → System Resources → System Models)**: Exposes **Model configuration**, **Model provider**, **Call log**, **Monitoring**, and **Model probes** tabs for global presets, routing weights, and connectivity probes.

If a listed model fails during execution, inspect the selected instance, member permissions, channel credentials, provider status, and quota. Test configuration updates before verifying dependent applications.

## Bulk Replace Invalid Team Model References

When a model is retired or its identifier changes, a **Team Owner** can click **Replace unavailable models** in the filter bar of **Account → Model provider** to repair unavailable static model references across team assets:

1. **Select Replacement Models**: Choose the target **Language Model (LLM)**, **Text-to-Speech Model (TTS)**, and **Rerank Model** in the modal.
2. **Scan and Replacement Scope**: Upon confirmation, the system scans the current team's **Datasets**, **Apps**, and **all historical App versions** (including custom model selector fields), replacing unavailable static model references with the selected targets and updating valid resource snapshots. Empty values, dynamic variable references, and Embedding models are skipped (changing an Embedding model requires an index rebuild in the knowledge base settings).
3. **Inspect Counts and Retry**: After execution, the modal reports **Records scanned**, **References replaced**, **References skipped**, **Conflicts**, and **Failed records** per resource type (`Dataset`, `App`, `App version`) along with failure samples. If concurrent edits or interruptions occur, click **Run again** with the same mapping to process remaining unavailable references.