> Discover all available pages from the documentation index: https://mastra.zisheng.pro/zh-HK/llms.txt

# ![Weights & Biases 標誌](https://models.dev/logos/wandb.svg)Weights & Biases

透過 Mastra 的模型路由器存取 27 個 Weights & Biases 模型。系統會自動使用 `WANDB_API_KEY` 環境變數進行驗證。

詳情請參閱[Weights & Biases 文件](https://docs.wandb.ai)。

```bash
WANDB_API_KEY=your-api-key
```

```typescript
import { Agent } from '@mastra/core/agent'

const agent = new Agent({
  id: 'my-agent',
  name: 'My Agent',
  instructions: 'You are a helpful assistant',
  model: 'wandb/JetBrains/Mellum2-12B-A2.5B-Instruct',
})

// Generate a response
const response = await agent.generate('Hello!')

// Stream a response
const stream = await agent.stream('Tell me a story')
for await (const chunk of stream) {
  console.log(chunk)
}
```

> **資訊:** Mastra 使用與 OpenAI 相容的 `/chat/completions` 端點。部分 Provider 專屬功能可能無法使用，詳情請參閱[Weights & Biases 文件](https://docs.wandb.ai)。

## 模型

| Model                                                | Context | Tools | Reasoning | Image | Audio | Video | Input $/1M | Output $/1M |
| ---------------------------------------------------- | ------- | ----- | --------- | ----- | ----- | ----- | ---------- | ----------- |
| `wandb/deepseek-ai/DeepSeek-V3.1`                    | 161K    |       |           |       |       |       | $0.55      | $2          |
| `wandb/deepseek-ai/DeepSeek-V4-Flash`                | 1.0M    |       |           |       |       |       | $0.14      | $0.28       |
| `wandb/deepseek-ai/DeepSeek-V4-Flash-0731`           | 262K    |       |           |       |       |       | $0.13      | $0.28       |
| `wandb/deepseek-ai/DeepSeek-V4-Pro`                  | 1.0M    |       |           |       |       |       | $1         | $3          |
| `wandb/google/gemma-4-31B-it`                        | 262K    |       |           |       |       |       | $0.10      | $0.34       |
| `wandb/ibm-granite/granite-4.1-8b`                   | 131K    |       |           |       |       |       | $0.05      | $0.10       |
| `wandb/JetBrains/Mellum2-12B-A2.5B-Instruct`         | 131K    |       |           |       |       |       | $0.05      | $0.10       |
| `wandb/meta-llama/Llama-3.1-70B-Instruct`            | 128K    |       |           |       |       |       | $0.80      | $0.80       |
| `wandb/meta-llama/Llama-3.1-8B-Instruct`             | 128K    |       |           |       |       |       | $0.22      | $0.22       |
| `wandb/meta-llama/Llama-3.3-70B-Instruct`            | 128K    |       |           |       |       |       | $0.71      | $0.71       |
| `wandb/MiniMaxAI/MiniMax-M2.5`                       | 197K    |       |           |       |       |       | $0.30      | $1          |
| `wandb/MiniMaxAI/MiniMax-M3`                         | 262K    |       |           |       |       |       | $0.23      | $0.96       |
| `wandb/moonshotai/Kimi-K2.6`                         | 262K    |       |           |       |       |       | $0.65      | $3          |
| `wandb/moonshotai/Kimi-K2.7-Code`                    | 262K    |       |           |       |       |       | $0.71      | $4          |
| `wandb/moonshotai/Kimi-K3`                           | 1.0M    |       |           |       |       |       | $3         | $15         |
| `wandb/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-FP8` | 262K    |       |           |       |       |       | $0.20      | $0.80       |
| `wandb/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B`     | 262K    |       |           |       |       |       | $0.75      | $3          |
| `wandb/openai/gpt-oss-120b`                          | 131K    |       |           |       |       |       | $0.03      | $0.17       |
| `wandb/openai/gpt-oss-20b`                           | 131K    |       |           |       |       |       | $0.03      | $0.13       |
| `wandb/OpenPipe/Qwen3-14B-Instruct`                  | 33K     |       |           |       |       |       | $0.05      | $0.22       |
| `wandb/Qwen/Qwen3-30B-A3B-Instruct-2507`             | 262K    |       |           |       |       |       | $0.10      | $0.30       |
| `wandb/Qwen/Qwen3-Coder-480B-A35B-Instruct`          | 262K    |       |           |       |       |       | $1         | $2          |
| `wandb/Qwen/Qwen3.5-35B-A3B`                         | 262K    |       |           |       |       |       | $0.25      | $1          |
| `wandb/Qwen/Qwen3.6-27B`                             | 262K    |       |           |       |       |       | $0.60      | $4          |
| `wandb/Qwen/Qwen3.6-35B-A3B`                         | 262K    |       |           |       |       |       | $0.25      | $1          |
| `wandb/zai-org/GLM-5.1`                              | 203K    |       |           |       |       |       | $1         | $4          |
| `wandb/zai-org/GLM-5.2`                              | 262K    |       |           |       |       |       | $0.76      | $2          |

## 進階設定

### 自訂標頭

```typescript
const agent = new Agent({
  id: 'custom-agent',
  name: 'custom-agent',
  model: {
    url: 'https://api.inference.wandb.ai/v1',
    id: 'wandb/JetBrains/Mellum2-12B-A2.5B-Instruct',
    apiKey: process.env.WANDB_API_KEY,
    headers: {
      'X-Custom-Header': 'value',
    },
  },
})
```

### 動態選擇模型

```typescript
const agent = new Agent({
  id: 'dynamic-agent',
  name: 'Dynamic Agent',
  model: ({ requestContext }) => {
    const useAdvanced = requestContext.task === 'complex'
    return useAdvanced ? 'wandb/zai-org/GLM-5.2' : 'wandb/JetBrains/Mellum2-12B-A2.5B-Instruct'
  },
})
```