# Qwen3.8 2.4t A95B API Pricing

As of October 10, 2026, Qwen3.8 2.4t A95B costs $2.00 per 1M input tokens and $6.00 per 1M output tokens from AIHubMix, the lowest of 3 providers, with cache reads at $0.50 per 1M tokens. It has a 1,000,000-token context window and returns up to 131,072 tokens per response.

- Page: https://models.litellm.ai/models/qwen3.8-2.4t-a95b
- Lab: Alibaba
- LiteLLM model name: `aihubmix/qwen3.8-2.4t-a95b`
- Context window: 1,000,000 tokens
- Max output: 131,072 tokens
- Added to LiteLLM: August 25, 2026
- Prices updated: October 10, 2026

## Pricing by provider

Token prices in USD per 1M tokens.

| Provider | Model name | Input | Output | Cache read | Per image | Per second | Context |
|---|---|---|---|---|---|---|---|
| AIHubMix | `aihubmix/qwen3.8-2.4t-a95b` | $2.00 | $6.00 | $0.50 | – | – | 1M |
| DeepInfra | `deepinfra/Qwen/Qwen3.8-2.4T-A95B` | $2.00 | $6.00 | $0.20 | – | – | 256K |
| Together AI | `together_ai/Qwen/Qwen3.8-2.4T-A95B` | $2.00 | $6.00 | $0.25 | – | – | 1M |

## Cost examples

1,000 requests with 2,000 input and 500 output tokens each:

- AIHubMix: $7.00
- DeepInfra: $7.00
- Together AI: $7.00

100 long-document requests with 100,000 input and 2,000 output tokens each:

- AIHubMix: $21.20
- DeepInfra: $21.20
- Together AI: $21.20

## Features

Supported: Function calling, Structured output, Reasoning, Prompt caching, Web search.

## Use it with LiteLLM

```python
from litellm import completion

response = completion(
    model="aihubmix/qwen3.8-2.4t-a95b",
    messages=[{"role": "user", "content": "Hello!"}],
)
```

## FAQ

### How much does Qwen3.8 2.4t A95B cost?

Qwen3.8 2.4t A95B costs $2.00 per 1M input tokens and $6.00 per 1M output tokens from AIHubMix, the lowest of 3 providers, with cache reads at $0.50 per 1M tokens.

### What is the context window of Qwen3.8 2.4t A95B?

Qwen3.8 2.4t A95B has a 1,000,000-token context window and returns up to 131,072 tokens per response.

### Which providers offer Qwen3.8 2.4t A95B?

Qwen3.8 2.4t A95B is available from 3 providers through LiteLLM: AIHubMix, DeepInfra and Together AI.

### How do I call Qwen3.8 2.4t A95B with an OpenAI-compatible API?

Use the LiteLLM Python SDK with model="aihubmix/qwen3.8-2.4t-a95b", or add the model to the LiteLLM proxy's config.yaml and send requests to /v1/chat/completions from any OpenAI client. LiteLLM tracks the cost of every request at the prices on this page.

### What features does Qwen3.8 2.4t A95B support?

Qwen3.8 2.4t A95B supports function calling, structured output, reasoning, prompt caching and web search.

### When did LiteLLM add Qwen3.8 2.4t A95B?

Qwen3.8 2.4t A95B was added to LiteLLM's model price file on August 25, 2026.

Source: LiteLLM model price file, https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json