---
title: "Qwen3.8 Max (0902) AI model: facts and benchmarks | Kendr"
canonical: "https://kendr.org/models/qwen-qwen3-8-max-0902"
date_modified: "2026-09-06"
profile_kind: "reference"
---

# Qwen3.8 Max (0902) model profile

Qwen3.8 Max (0902) is a Alibaba Qwen model profile with a 1,000,000-token context window. The dated catalog snapshot records text, image, video modalities and interfaces for prompt caching, reasoning controls, structured output, text generation, tool calling.

Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team. It is a 2.4-trillion-parameter mixture-of-experts model that accepts text, image, and video input and returns text, with a 1M-token context window and reasoning enabled by default. This snapshot is post-trained for coding and agentic work, including multi-step software projects, multi-tool orchestration, and long-horizon task execution. It also targets chart reasoning, document parsing, and multimodal understanding over long documents and extended video. Tool calling, structured outputs, and configurable reasoning effort are supported.

Qwen3.8 Max (0902) is a reference profile: Alibaba Qwen publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call.

Qwen3.8 Max (0902) is an independent knowledge profile. It does not claim that Kendr hosts the model, quote a Kendr customer price, promise API availability, or advertise a Kendr routing receipt.

Qwen3.8 Max (0902) accepts text, image, and video and returns text. The snapshot records prompt caching, reasoning controls, structured output, text generation, tool calling, video input, and vision as capabilities or interfaces.

The dated reference snapshot lists $2 input and $6 output per million tokens. Cached input is $0.25 per million tokens.

The 2026-09-06 snapshot includes 3 Artificial Analysis indexes. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable.

Qwen3.8 Max (0902) ranked #93 in the cited trailing-7-day third-party catalog usage dataset as of 2026-09-06. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share.

Profile data was reviewed for the 2026-09-06 snapshot. Claims retain their source dates, and unavailable fields are shown as unavailable instead of estimated.

## Profile facts

- **Profile type:** Model research profile
- **Provider or publisher:** Alibaba Qwen
- **Context window:** 1,000,000 tokens
- **Snapshot date:** 2026-09-06
- **Knowledge cutoff:** Not disclosed
- **Reference catalog ID:** qwen/qwen3.8-max-0902

## When to pick Qwen3.8 Max (0902)

Qwen3.8 Max (0902) is a reference profile: Alibaba Qwen publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call.

Each condition below is derived from this model's own values in the 2026-09-06 snapshot, compared only against models publishing the same field.

- Reach for it when answer quality matters more than unit cost. It scores 46.9 on the Artificial Analysis intelligence index, above three quarters of the 32 models carrying that field in the 2026-09-06 snapshot.
- Reach for it when the input includes images. The snapshot records image input, so screenshots, scans, and diagrams can be sent directly instead of described.
- Reach for it when the model has to call tools. Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose.
- Look elsewhere when you need to call it through Kendr today. This is a research reference profile with no Kendr alias. The facts and evidence here are published for comparison; the model is not routable on Kendr.
- Look elsewhere when the request is trivial and latency-sensitive. Reasoning is mandatory on this route and cannot be turned off, so short factual requests still pay reasoning tokens and reasoning latency.

## Context, modalities, and identity

Qwen3.8 Max (0902) accepts text, image, and video and returns text. The snapshot records prompt caching, reasoning controls, structured output, text generation, tool calling, video input, and vision as capabilities or interfaces.

- **Provider or publisher:** Alibaba Qwen
- **Context window:** 1,000,000 tokens
- **Maximum output:** 131,072 tokens
- **Input modalities:** text, image, and video
- **Output modalities:** text
- **Knowledge cutoff:** Not disclosed

## Model overview

Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team. It is a 2.4-trillion-parameter mixture-of-experts model that accepts text, image, and video input and returns text, with a 1M-token context window and reasoning enabled by default. This snapshot is post-trained for coding and agentic work, including multi-step software projects, multi-tool orchestration, and long-horizon task execution. It also targets chart reasoning, document parsing, and multimodal understanding over long documents and extended video. Tool calling, structured outputs, and configurable reasoning effort are supported.

- **Reference model ID:** qwen/qwen3.8-max-0902
- **Canonical version:** qwen/qwen3.8-max-20260902
- **Hugging Face ID:** Not separately documented

## Capabilities and supported controls

Capabilities and parameters are reported from the dated catalog and source records; their presence does not guarantee identical behavior across every provider route.

- **Supported parameters:** frequency_penalty, include_reasoning, logprobs, max_tokens, presence_penalty, reasoning, reasoning_effort, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_p

- prompt caching
- reasoning controls
- structured output
- text generation
- tool calling
- video input
- vision

## Dated pricing snapshot

The dated reference snapshot lists $2 input and $6 output per million tokens. Cached input is $0.25 per million tokens.

These are dated third-party reference prices, not Kendr prices or an availability offer. Routes, tiers, caching, region, and provider policy can change the landed price.

- **Price date:** 2026-09-06
- **Input:** $2 per 1M tokens
- **Cached input:** $0.25 per 1M tokens
- **Output:** $6 per 1M tokens

## Provider routes, performance, and uptime

The snapshot retains 1 provider endpoint. Provider prices, context limits, p50 performance, and uptime can differ by route and are not Kendr guarantees.

- **Active provider endpoints:** 1
- **Best p50 latency:** 1.99 s
- **Best p50 throughput:** 40 tok/s
- **Availability with routing:** 99.71% over the sampled window
- **Availability without routing:** 99.61% over the sampled window
- **Performance date:** 2026-09-06

| Provider | Quantization | Input / 1M | Output / 1M | Cache read / 1M | Context | p50 latency | p50 throughput | Uptime (1d) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Alibaba Cloud Int. | unknown | $2 / 1M | $6 / 1M | $0.25 / 1M | 1,000,000 tokens | 1.99 s | 40 tok/s | 100.00% |

## Benchmark evidence and limitations

The 2026-09-06 snapshot includes 3 Artificial Analysis indexes. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable.

Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.

- **Intelligence Index:** 46.9
- **Coding Index:** 71.8
- **Agentic Index:** 49.9

## Popularity and market context

Qwen3.8 Max (0902) ranked #93 in the cited trailing-7-day third-party catalog usage dataset as of 2026-09-06. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share.

- **Third-party catalog rank:** #93
- **Global market share:** Not inferred
- **Observation date:** 2026-09-06

## Frequently asked questions

### When should I use Qwen3.8 Max (0902)?

Qwen3.8 Max (0902) is a reference profile: Alibaba Qwen publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call. Reach for it when answer quality matters more than unit cost: It scores 46.9 on the Artificial Analysis intelligence index, above three quarters of the 32 models carrying that field in the 2026-09-06 snapshot. Reach for it when the input includes images: The snapshot records image input, so screenshots, scans, and diagrams can be sent directly instead of described. Reach for it when the model has to call tools: Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose. Look elsewhere when you need to call it through Kendr today: This is a research reference profile with no Kendr alias. The facts and evidence here are published for comparison; the model is not routable on Kendr. Look elsewhere when the request is trivial and latency-sensitive: Reasoning is mandatory on this route and cannot be turned off, so short factual requests still pay reasoning tokens and reasoning latency.

### What is Qwen3.8 Max (0902)?

Qwen3.8 Max (0902) is a Alibaba Qwen model profile with a 1,000,000-token context window. The dated catalog snapshot records text, image, video modalities and interfaces for prompt caching, reasoning controls, structured output, text generation, tool calling.

### What context window does Qwen3.8 Max (0902) have?

The dated profile lists 1,000,000 tokens of context and up to 131,072 output tokens. Provider routes, variants, and runtime configuration can impose lower effective limits.

### What benchmark evidence is available for Qwen3.8 Max (0902)?

The 2026-09-06 snapshot includes 3 Artificial Analysis indexes. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable. Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.

### Is Qwen3.8 Max (0902) available through Kendr?

This is an independent knowledge profile, not a Kendr-hosted availability claim. Check Kendr's live public model API for currently enabled Kendr aliases.

### Does the popularity rank represent Qwen3.8 Max (0902)'s global market share?

Qwen3.8 Max (0902) ranked #93 in the cited trailing-7-day third-party catalog usage dataset as of 2026-09-06. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share. No global market-share percentage is inferred when the source does not publish one.

## Sources and evidence dates

- [Qwen3.8 Max (0902) third-party catalog record](https://openrouter.ai/qwen/qwen3.8-max-0902) — catalog, checked 2026-09-06
- [Third-party model catalog methodology](https://openrouter.ai/docs/guides/overview/models) — methodology, checked 2026-09-06
- [Alibaba Qwen official model documentation](https://help.aliyun.com/en/model-studio/model-pricing) — primary, checked 2026-09-06
- [Artificial Analysis capability indices methodology](https://artificialanalysis.ai/methodology/capability-indices) — benchmark, checked 2026-09-06

Live Kendr operational availability is published separately at https://api.kendr.org/api/public/models.