LiteLLMModels

Qwen3.8 Max API Pricing

As of October 10, 2026, Qwen3.8 Max costs $2.00 per 1M input tokens and $6.00 per 1M output tokens on Alibaba Cloud Model Studio, with cache reads at $0.25 per 1M tokens. Across 8 providers on LiteLLM, the input price ranges from $1.65 to $2.00. It has a 991,808-token context window and returns up to 131,072 tokens per response.

By AlibabaModel ID dashscope/qwen3.8-maxPrices updated Checked
Input
$2.00 / 1M tokens
Output
$6.00 / 1M tokens
Cache read
$0.25 / 1M tokens
Context window
991,808 tokens
Max output
131,072 tokens
Providers
8
Added to LiteLLM
August 7, 2026

Qwen3.8 Max pricing by provider

9 listings across 8 providers. Token prices are in US dollars per 1M tokens. The highlighted row is the price quoted above.

ProviderModel name in LiteLLMInputOutputCache readCache writeContext
Alibaba Cloud Model Studiodashscope/qwen3.8-max$2.00$6.00$0.25–992K
AIHubMixaihubmix/qwen3.8-max$1.69$5.07$0.169$2.1131M
DeepInfradeepinfra/Qwen/Qwen3.8-Max$1.65$4.951$0.206–256K
Fireworks AIfireworks_ai/accounts/fireworks/models/qwen3p8-max$2.00$6.00$0.25–256K
Fireworks AIfireworks_ai/qwen3p8-max$2.00$6.00$0.25–256K
Novita AInovita/qwen/qwen3.8-max$2.00$6.00$0.25–1M
Qianwen AI Platformqwen_ai_platform/qwen3.8-max$2.00$6.00$0.25–992K
QwenCloudqwencloud/qwen3.8-max$2.00$6.00$0.25–992K
SCX.aiscx-ai/Qwen3.8-Max$1.65$4.99$0.21–1M

What Qwen3.8 Max costs in practice

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

Alibaba Cloud Model Studio$7.00
DeepInfra$5.776
SCX.ai$5.795
AIHubMix$5.915

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

Alibaba Cloud Model Studio$21.20
DeepInfra$17.49
SCX.ai$17.50
AIHubMix$17.91

Qwen3.8 Max features

Use Qwen3.8 Max with LiteLLM

Call Qwen3.8 Max 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="dashscope/qwen3.8-max",
    messages=[{"role": "user", "content": "Hello!"}],
)
Proxy config.yaml
model_list:
  - model_name: qwen3.8-max
    litellm_params:
      model: dashscope/qwen3.8-max
      # credentials: see the provider's LiteLLM docs page
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": "qwen3.8-max",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Qwen3.8 Max FAQ

How much does Qwen3.8 Max cost?

Qwen3.8 Max costs $2.00 per 1M input tokens and $6.00 per 1M output tokens on Alibaba Cloud Model Studio, with cache reads at $0.25 per 1M tokens. Across 8 providers on LiteLLM, the input price ranges from $1.65 to $2.00.

What is the context window of Qwen3.8 Max?

Qwen3.8 Max has a 991,808-token context window and returns up to 131,072 tokens per response.

Which providers offer Qwen3.8 Max?

Qwen3.8 Max is available from 8 providers through LiteLLM: Alibaba Cloud Model Studio, AIHubMix, DeepInfra, Fireworks AI, Novita AI, Qianwen AI Platform, QwenCloud and SCX.ai. The lowest price is on DeepInfra.

How do I call Qwen3.8 Max with an OpenAI-compatible API?

Use the LiteLLM Python SDK with model="dashscope/qwen3.8-max", 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 Max support?

Qwen3.8 Max supports function calling, structured output, image input, reasoning, prompt caching and web search.

When did LiteLLM add Qwen3.8 Max?

Qwen3.8 Max was added to LiteLLM's model price file on August 7, 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: Alibaba Cloud Model Studio, AIHubMix, DeepInfra, Fireworks AI, Qianwen AI Platform, SCX.ai.

Provider pages: Alibaba Cloud Model Studio, AIHubMix, DeepInfra, Fireworks AI, Novita AI, Qianwen AI Platform, QwenCloud, SCX.ai.