LiteLLMModels

Qwen3 Max Thinking API Pricing

As of October 10, 2026, Qwen3 Max Thinking costs $1.20 per 1M input tokens and $6.00 per 1M output tokens on DeepInfra, with cache reads at $0.24 per 1M tokens. It has a 256,000-token context window.

By AlibabaModel ID deepinfra/Qwen/Qwen3-Max-ThinkingPrices updated Checked
Input
$1.20 / 1M tokens
Output
$6.00 / 1M tokens
Cache read
$0.24 / 1M tokens
Context window
256,000 tokens
Providers
1
Added to LiteLLM
August 27, 2026

Qwen3 Max Thinking pricing by provider

1 listing across 1 provider. Token prices are in US dollars per 1M tokens. The highlighted row is the price quoted above.

ProviderModel name in LiteLLMInputOutputCache readContext
DeepInfradeepinfra/Qwen/Qwen3-Max-Thinking$1.20$6.00$0.24256K

What Qwen3 Max Thinking costs in practice

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

DeepInfra$5.40

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

DeepInfra$13.20

Qwen3 Max Thinking features

Use Qwen3 Max Thinking with LiteLLM

Call Qwen3 Max Thinking through the LiteLLM Python SDK, or put it behind the LiteLLM proxy and send OpenAI-format requests to /v1/chat/completions. LiteLLM tracks the cost of every request at these prices.

Python SDK
from litellm import completion

response = completion(
    model="deepinfra/Qwen/Qwen3-Max-Thinking",
    messages=[{"role": "user", "content": "Hello!"}],
)
Proxy config.yaml
model_list:
  - model_name: qwen3-max-thinking
    litellm_params:
      model: deepinfra/Qwen/Qwen3-Max-Thinking
      api_key: os.environ/DEEPINFRA_API_KEY
Call the proxy
curl http://0.0.0.0:4000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-1234" \
  -d '{
    "model": "qwen3-max-thinking",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Qwen3 Max Thinking FAQ

How much does Qwen3 Max Thinking cost?

Qwen3 Max Thinking costs $1.20 per 1M input tokens and $6.00 per 1M output tokens on DeepInfra, with cache reads at $0.24 per 1M tokens.

What is the context window of Qwen3 Max Thinking?

Qwen3 Max Thinking has a 256,000-token context window.

Which providers offer Qwen3 Max Thinking?

Qwen3 Max Thinking is available from DeepInfra through LiteLLM, using the model name deepinfra/Qwen/Qwen3-Max-Thinking.

How do I call Qwen3 Max Thinking with an OpenAI-compatible API?

Use the LiteLLM Python SDK with model="deepinfra/Qwen/Qwen3-Max-Thinking", 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 Max Thinking support?

Qwen3 Max Thinking supports function calling, structured output and prompt caching. It does not support image input.

When did LiteLLM add Qwen3 Max Thinking?

Qwen3 Max Thinking was added to LiteLLM's model price file on August 27, 2026.

Sources

Prices come from LiteLLM's open-source model_prices_and_context_window.json, which LiteLLM uses to calculate the cost of every request. Provider pricing pages:

LiteLLM docs: DeepInfra.

Provider pages: DeepInfra.