qwen/qwen3.8-max

1M context · $1.2000 / M input tokens · $3.6000 / M output tokens

Qwen3.8 Max is the flagship Qwen3.8 route on OurToken for developers evaluating the most capable Qwen API option for chat, multimodal understanding, coding, reasoning, long-context work, and production assistant workloads.

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24H Status Monitor

Historical uptime data is collected over time. Current status reflects the latest health check.

Pricing

Pay-per-use

No upfront costs, pay only for what you use

60% of official price

Input$2.00 / M$1.2000 / M Tokens

Output$6.00 / M$3.6000 / M Tokens

Cached input$0.25 / M$0.1500 / M Tokens

Cache writes$2.50 / M$1.5000 / M Tokens

API Usage

API Access Guide

Base URLhttps://api.ourtoken.ai/v1

API Endpointchat/completions

Full URLhttps://api.ourtoken.ai/v1/chat/completions

Model IDqwen3.8-max

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Code examples

Use the OurToken API endpoint for this model. The examples below use direct HTTP requests and the recommended endpoint for the model family.

curl https://api.ourtoken.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "qwen3.8-max",
    "messages": [
      {
        "role": "user",
        "content": "Hello!"
      }
    ],
    "max_tokens": 256
  }'

Chat Completions API Reference

Create a chat response with the OpenAI Chat Completions-compatible endpoint. Use https://api.ourtoken.ai/v1 as the SDK Base URL and POST /chat/completions as the endpoint.

Authorization

Content-Type	application/json
Authorization	Bearer YOUR_API_KEY

Request Body

Field	Type	Required	Description
model	string	Required	Model ID to call.
messages	array<object>	Required	Conversation messages sent to the model.
max_tokens	integer	Optional	Maximum number of output tokens.
temperature	number	Optional	Sampling temperature.
top_p	number	Optional	Nucleus sampling parameter.
stream	boolean	Optional	Whether to return a streaming response.
stream_options	object	Optional	Additional options for streaming responses.
tools	array<object>	Optional	Tools available to the model.
tool_choice	string \| object	Optional	Controls how the model selects tools.
response_format	object	Optional	Controls structured output, such as JSON object responses.

Response Body

Field	Type	Required	Description
id	string	Required	Unique chat completion identifier.
object	"chat.completion"	Required	Object type returned by the Chat Completions API.
created	integer	Required	Unix timestamp when the response was created.
model	string	Required	Model that produced the response.
choices	array<object>	Required	Candidate responses returned by the model.
choices[].message.role	string	Required	Role of the returned chat message.
choices[].message.content	string	Optional	Text content in the returned chat message.
choices[].finish_reason	string	Optional	Reason generation stopped.
usage	object	Optional	Token usage information for the chat completion.
usage.prompt_tokens	integer	Optional	Input token count.
usage.completion_tokens	integer	Optional	Output token count.
usage.total_tokens	integer	Optional	Total token count.
usage.prompt_tokens_details	object	Optional	Breakdown of input token usage.
usage.prompt_tokens_details.cached_tokens	integer	Optional	Tokens served from cache.

Model Introduction

Qwen qwen3.8-max

Qwen3.8 Max is the flagship of the Qwen3.8 generation, combining frontier reasoning, coding capability, and native vision-language understanding with a 1M-token context window according to supplied launch material. Use qwen3.8-max api through OurToken when you want one endpoint for model testing, pricing review, API keys, usage logs, benchmark validation, and production integration.

Why It Looks Great

Flagship Qwen3.8 route for evaluation and production testing.
OpenAI-compatible chat completions setup through the OurToken endpoint.
Dedicated route page for model ID, code examples, and 60% of official price pricing review.
Useful for comparing benchmark claims against real prompts and logs.
Clean path from Qwen discovery into API implementation.

Key Features

Model ID: qwen3.8-max
Provider: Qwen
Input price: $1.2000 per 1M tokens on OurToken
Output price: $3.6000 per 1M tokens on OurToken
Cache read price: $0.1500 per 1M tokens on OurToken
Cache write price: $1.5000 per 1M tokens on OurToken
API endpoint: chat completions
Evaluation focus: reasoning, coding, multimodal understanding, and benchmark validation

Specifications

ProviderQwen

Model IDqwen3.8-max

Model TypeMultimodal Large Model (LLM + VLM)

OurToken Input Price$1.2000 / 1M tokens

OurToken Output Price$3.6000 / 1M tokens

OurToken Cache Read Price$0.1500 / 1M tokens

OurToken Cache Write Price$1.5000 / 1M tokens

Official Input Reference$2.00 / 1M tokens

Official Output Reference$6.00 / 1M tokens

Official Cache Read Reference$0.25 / 1M tokens

Official Cache Write Reference$2.50 / 1M tokens

Context Window1M tokens

API Endpointhttps://api.ourtoken.ai/v1/chat/completions

qwen3.8 max api Features for Developers

Use qwen3.8 max api access to review qwen3.8 max pricing at 60% of official price and test flagship benchmark claims.

API Access

Call qwen3.8 max api through the OurToken unified endpoint with the qwen3.8-max model ID. This gives developers a direct route for testing Qwen3.8 flagship prompts while keeping API keys, request examples, and usage review in one place.

Pricing Review

Review qwen3.8 max pricing before scaling traffic. OurToken lists $1.2000 input, $3.6000 output, $0.1500 cache read, and $1.5000 cache write per 1M tokens, with official references of $2.00, $6.00, $0.25, and $2.50.

Multimodal Understanding

Evaluate Qwen3.8 Max on image and document understanding, STEM diagrams, and hour-scale video comprehension alongside text reasoning, reflecting the native vision-language capability of the Qwen3.8 generation.

Built-in Tools

Test built-in tools such as web search, code interpreter, and image search directly through the Qwen3.8 Max route, which reduces the need to wire separate tool integrations for agent-style prompts.

Long-Context Tasks

Use the 1M-token context window for repository-scale analysis, long documents, and long-horizon agent sessions, with flexible thinking control available per request.

Benchmark Testing

Build your own qwen3.8 max benchmark suite with real coding, reasoning, retrieval, and assistant prompts. Compare outputs against acceptance criteria, not only public leaderboard claims or one-off provider examples.

How to Use qwen3.8 max api on OurToken

Create an API key, use qwen3.8-max, compare 60% of official price pricing, run tests, and monitor usage.

Create Key

Create an OurToken API key from the dashboard and store it in a secure server-side environment variable. This gives your backend a stable way to test qwen3.8 max api without exposing credentials in browser code.

Copy Model

Use qwen3.8-max as the model value in your request body. Keeping the exact model ID in configuration helps developers avoid casing mistakes while comparing Qwen routes across local tests, staging traffic, and production deployments.

Call Endpoint

Send chat completions requests to the OurToken unified endpoint with your qwen3.8-max model ID. Existing OpenAI-compatible client patterns can usually be reused after changing the base URL, API key, and model value.

Review Pricing

Before scaling usage, review qwen3.8 max pricing: $1.2000 input, $3.6000 output, $0.1500 cache read, and $1.5000 cache write per 1M tokens. Compare those rows with expected prompt size, output length, and request volume.

Test Benchmark

Use real coding, reasoning, multimodal, and assistant prompts to build your own qwen3.8 max benchmark suite. Validate thinking depth, tool behavior, latency, and cost instead of relying only on public leaderboards.

Monitor Cost

After testing, review request count, token usage, failures, latency, and spend in OurToken history. This helps decide whether qwen3.8 max api should become a default route or remain an evaluation option.

qwen3.8 max api FAQ

Answers about qwen3.8 max pricing, qwen3.8-max model selection, benchmark testing, model ID, and provider comparison.

What is qwen3.8 max api?

qwen3.8 max api is the OurToken route page for calling the qwen3.8-max model through a unified API workflow. Developers can copy the model ID, create an API key, run chat completions requests, review current pricing at 60% of official price, and compare real outputs before choosing it for production traffic.

How should I check qwen3.8 max pricing?

qwen3.8 max pricing on OurToken is $1.2000 per 1M input tokens and $3.6000 per 1M output tokens. Cache read is $0.1500 per 1M tokens, and cache write is $1.5000 per 1M tokens. Official references are $2.00 input, $6.00 output, $0.25 cache read, and $2.50 cache write.

Which model ID should I use for Qwen3.8 Max?

Use qwen3.8-max as the model value when calling this route through OurToken. Keep it in configuration rather than hard-coding it across many files, because that makes it easier to compare qwen3.8 max api with Qwen3.8 Flash or other provider routes later.

What context window does Qwen3.8 Max support?

According to supplied launch material, Qwen3.8 Max natively supports a 1M-token context window with flexible thinking control, reasoning effort tuning, and built-in tools such as web search and code interpreter.

Can Qwen3.8 Max understand images and videos?

Qwen3.8 Max is a native vision-language model as part of the Qwen3.8 generation, supporting image and video understanding from STEM diagrams and documents to hour-scale videos, on top of text reasoning and coding.

How should I interpret a qwen3.8 max benchmark?

A qwen3.8 max benchmark can help decide what to test, but it should not replace your own evaluation. Run representative prompts for coding, multilingual chat, reasoning, tool use, and latency, then compare quality, stability, token usage, and cost against your product requirements.