# Models

Available models on the Tensorix platform.

***

## Overview

Tensorix provides access to leading open-source and proprietary AI models through a unified API. All models are accessible via the same OpenAI-compatible endpoint.

{% hint style="info" %}
**Live Pricing & Full List**: Visit [tensorix.ai/models](https://tensorix.ai/models) for real-time pricing and the complete model catalog.
{% endhint %}

***

## Model Capabilities

Our Large Language Models (LLMs) support:

* **Text Generation** - Generate coherent, contextual content
* **Language Understanding** - Understand meaning and context
* **Code Generation** - Write, analyze, and debug code
* **Reasoning** - Complex problem solving and analysis
* **Function Calling** - Tool use and structured outputs
* **Vision** - Image understanding (select models)
* **Multilingual** - Support for multiple languages
* **Text-to-Speech** - Convert text to natural audio
* **Speech-to-Text** - Transcribe audio to text

***

## Available Models

### GLM (Z-AI) ⭐

| Model          | Context | Features             | Best For                                     |
| -------------- | ------- | -------------------- | -------------------------------------------- |
| `z-ai/glm-5.1` | 203K    | Functions, Reasoning | Coding, reasoning, Chinese/English bilingual |
| `z-ai/glm-4.6` | 203K    | Functions, Reasoning | General purpose, bilingual                   |

### MiniMax ⭐

| Model                  | Context | Features                     | Best For                   |
| ---------------------- | ------- | ---------------------------- | -------------------------- |
| `minimax/minimax-m2.5` | 197K    | Functions, Reasoning         | Reasoning, general purpose |
| `minimax/minimax-m2`   | 197K    | Coding, Functions, Reasoning | Coding, fast responses     |

### Moonshot AI

| Model                  | Context | Features          | Best For                                    |
| ---------------------- | ------- | ----------------- | ------------------------------------------- |
| `moonshotai/kimi-k2.5` | 262K    | Vision, Functions | Vision tasks, long context, general purpose |

### DeepSeek

| Model                         | Context | Features             | Best For                             |
| ----------------------------- | ------- | -------------------- | ------------------------------------ |
| `deepseek/deepseek-chat-v3.1` | 164K    | Functions, Reasoning | General chat, coding, fast reasoning |
| `deepseek/deepseek-v3.2`      | 164K    | Functions, Reasoning | General chat, fast responses         |
| `deepseek/deepseek-r1-0528`   | 164K    | Functions, Reasoning | Complex reasoning tasks              |

### Qwen

| Model                               | Context | Features          | Best For              |
| ----------------------------------- | ------- | ----------------- | --------------------- |
| `qwen/qwen3-235b-a22b-2507`         | 131K    | Functions         | Large-scale reasoning |
| `qwen/qwen3-coder-30b-a3b-instruct` | 262K    | Coding, Functions | Code generation       |

### Llama (Meta)

| Model                               | Context | Features  | Best For                               |
| ----------------------------------- | ------- | --------- | -------------------------------------- |
| `meta-llama/llama-3.3-70b-instruct` | 131K    | Functions | General purpose, instruction following |
| `meta-llama/llama-4-maverick`       | 1050K   | Functions | Long context, multimodal tasks         |

### OpenAI OSS

| Model                 | Context | Features             | Best For             |
| --------------------- | ------- | -------------------- | -------------------- |
| `openai/gpt-oss-120b` | 131K    | Functions, Reasoning | GPT-4 alternative    |
| `openai/gpt-oss-20b`  | 131K    | Functions, Reasoning | Fast, cost-effective |

### Audio Models 🎧

| Model                             | Type | Features                  | Best For                  |
| --------------------------------- | ---- | ------------------------- | ------------------------- |
| `chatterbox-turbo`                | TTS  | High-quality voices       | Text-to-speech generation |
| `Systran/faster-whisper-large-v3` | STT  | 98%+ accuracy, timestamps | Audio transcription       |

See [Audio API](/api-reference/audio.md) for detailed usage.

***

## Model Recommendations

| Use Case              | Recommended Models                                                   |
| --------------------- | -------------------------------------------------------------------- |
| **General Chat**      | `deepseek/deepseek-chat-v3.1`, `meta-llama/llama-3.3-70b-instruct`   |
| **Complex Reasoning** | `deepseek/deepseek-r1-0528`, `z-ai/glm-5.1`                          |
| **Coding**            | `z-ai/glm-5.1`, `minimax/minimax-m2`                                 |
| **Vision Tasks**      | `moonshotai/kimi-k2.5`, `meta-llama/llama-4-maverick`                |
| **Long Context**      | `moonshotai/kimi-k2.5` (262K), `meta-llama/llama-4-maverick` (1050K) |
| **Multilingual**      | `z-ai/glm-5.1` (Chinese/English)                                     |
| **Text-to-Speech**    | `chatterbox-turbo`                                                   |
| **Speech-to-Text**    | `Systran/faster-whisper-large-v3`                                    |

***

## List Models API

Retrieve the list of available models programmatically:

```bash
curl https://api.tensorix.ai/v1/models \
  -H "Authorization: Bearer $TENSORIX_API_KEY"
```

### Response

```json
{
  "object": "list",
  "data": [
    {
      "id": "deepseek/deepseek-chat-v3.1",
      "object": "model",
      "created": 1706745600,
      "owned_by": "deepseek"
    },
    {
      "id": "z-ai/glm-5.1",
      "object": "model",
      "created": 1706745600,
      "owned_by": "z-ai"
    }
  ]
}
```

***

## Using Models

Specify the model ID in your API request:

```python
from openai import OpenAI

client = OpenAI(
    api_key="your-tensorix-api-key",
    base_url="https://api.tensorix.ai/v1"
)

# Use DeepSeek for fast reasoning
response = client.chat.completions.create(
    model="deepseek/deepseek-chat-v3.1",
    messages=[{"role": "user", "content": "Explain quantum computing"}]
)

# Use GLM for coding
response = client.chat.completions.create(
    model="z-ai/glm-5.1",
    messages=[{"role": "user", "content": "Write a Python function to sort a list"}]
)

# Use Llama for long context
response = client.chat.completions.create(
    model="meta-llama/llama-4-maverick",
    messages=[{"role": "user", "content": "Summarize this document..."}]
)
```

***

## Pricing

Model pricing is based on token usage (input + output tokens).

{% hint style="success" %}
**View Current Pricing**: [tensorix.ai/models](https://tensorix.ai/models)

Pricing is displayed per 1M tokens for each model.
{% endhint %}

### How Pricing Works

```
Cost = (Input Tokens × Input Price) + (Output Tokens × Output Price)
```

* **Input tokens**: Text you send to the model
* **Output tokens**: Text the model generates

### Tips to Optimize Costs

1. **Choose the right model** - Use smaller models for simple tasks
2. **Set max\_tokens** - Limit output length when appropriate
3. **Use caching** - Cache responses for repeated queries
4. **Monitor usage** - Check your [dashboard](https://app.tensorix.ai/dashboard) regularly

***

## Feature Support

| Feature              | Supported Models                      |
| -------------------- | ------------------------------------- |
| **Function Calling** | DeepSeek, GLM, Qwen, GPT-OSS, MiniMax |
| **Reasoning**        | DeepSeek, GPT-OSS                     |
| **Vision**           | Llama 4 Maverick                      |
| **Streaming**        | All models                            |
| **JSON Mode**        | All models                            |
| **Text-to-Speech**   | chatterbox-turbo                      |
| **Speech-to-Text**   | Systran/faster-whisper-large-v3       |

***

## See Also

* [Chat Completions](https://github.com/Tensorix-ai/tensorix-docs/blob/main/api-reference/chat-completions/README.md) - API endpoint documentation
* [Quantisation](https://github.com/Tensorix-ai/tensorix-docs/blob/main/api-reference/quantisation/README.md) - How models are quantised and how to check the level for any specific model
* [Audio API](https://github.com/Tensorix-ai/tensorix-docs/blob/main/audio/README.md) - TTS and STT documentation
* [API Examples](https://github.com/Tensorix-ai/tensorix-docs/blob/main/api-examples/README.md) - Code examples
* [Pricing](https://tensorix.ai/models) - Live pricing


---

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