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Qwen: Qwen3.8 Max (0902) (batch)

qwen/qwen3.8-max-0902:batch

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.

Modalities
In / out price
$1.15 / $3.45per 1M
Context
262K
Released
Sep 3, 2026

Providers

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Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Weighted average

Input
$0/M tokens
Output
$0/M tokens
Price history
No effective price data for this selection

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Not enough uptime data to display yet.

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.

Benchmarks

Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.

Benchmark score summary for Qwen: Qwen3.8 Max (0902) (batch) (Artificial Analysis and Vals AI)
SourceBenchmarkScore
Artificial AnalysisQwen3.8 Max (0902) Intelligence Index33.7
Artificial AnalysisQwen3.8 Max (0902) Coding Index76.2
Artificial AnalysisQwen3.8 Max (0902) Agentic Index56.0
Artificial AnalysisQwen3.8 Max (0902) GPQA Diamond92.8%
Artificial AnalysisQwen3.8 Max (0902) HLE43.1%
Artificial AnalysisQwen3.8 Max (0902) AA-LCR80.3%
Artificial AnalysisQwen3.8 Max (0902) τ-Bench Banking47.8%
Artificial AnalysisQwen3.8 Max (0902) GDPval-AA58.7%
Artificial AnalysisQwen3.8 Max (0902) CritPt17.7%
Artificial AnalysisQwen3.8 Max (0902) SciCode52.1%
Artificial AnalysisQwen3.8 Max (0902) Terminal-Bench 4.038.9%
Artificial AnalysisQwen3.8 Max (0902) Terminal-Bench 2.188.8%
Artificial AnalysisQwen3.8 Max (0902) AA-Omniscience Accuracy29.5%
Artificial AnalysisQwen3.8 Max (0902) AA-Omniscience Non-Hallucination Rate72.9%
Vals AIQwen 3.8 Max Access to Justice Benchmark76.4%
Vals AIQwen 3.8 Max Code Migration24.0%
Vals AIQwen 3.8 Max CorpFin v265.9%
Vals AIQwen 3.8 Max CyberBench v1.128.6%
Vals AIQwen 3.8 Max EMB v1.166.0%
Vals AIQwen 3.8 Max Finance Agent (v2)50.6%
Vals AIQwen 3.8 Max Financial Coaching Bench75.6%
Vals AIQwen 3.8 Max GPQA Diamond93.7%
Vals AIQwen 3.8 Max Harvey's Legal Agent Benchmark v110.4%
Vals AIQwen 3.8 Max Immigration70.1%
Vals AIQwen 3.8 Max IOI68.9%
Vals AIQwen 3.8 Max LiveCodeBench87.9%
Vals AIQwen 3.8 Max LegalBench83.6%
Vals AIQwen 3.8 Max Legal Research Bench47.6%
Vals AIQwen 3.8 Max MedCode40.7%
Vals AIQwen 3.8 Max MedScribe84.9%
Vals AIQwen 3.8 Max MMLU Pro88.6%
Vals AIQwen 3.8 Max MMMU Pro88.0%
Vals AIQwen 3.8 Max MortgageTax64.0%
Vals AIQwen 3.8 Max MysteryMechanism23.9%
Vals AIQwen 3.8 Max ProgramBench0.0%
Vals AIQwen 3.8 Max ProofBench v1.158.0%
Vals AIQwen 3.8 Max Public Benefits Bench v1.167.1%
Vals AIQwen 3.8 Max Vals RSI Index21.8%
Vals AIQwen 3.8 Max SAGE81.8%
Vals AIQwen 3.8 Max SkillsBench42.0%
Vals AIQwen 3.8 Max SWE-bench85.6%
Vals AIQwen 3.8 Max SWE-bench Multimodal42.5%
Vals AIQwen 3.8 Max Tax Agent Bench32.1%
Vals AIQwen 3.8 Max TaxEval v275.6%
Vals AIQwen 3.8 Max Terminal-Bench 4.034.3%
Vals AIQwen 3.8 Max Terminal-Bench-Science12.9%
Vals AIQwen 3.8 Max Vals Index48.3%
Vals AIQwen 3.8 Max Vals Multimodal Index65.4%
Vals AIQwen 3.8 Max Vibe Code Bench 1-10012.8%
Vals AIQwen 3.8 Max Vibe Code Bench v1.164.7%

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

Not enough data for apps using this model yet.

Activity

Token volume and request traffic to this model over time.

API

Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.

Not currently available through EU in-region routing. In-region routing docs

Frequently asked questions