qwen/qwen3.8-max-0902 is a frontier-tier language model from OpenRouter. qwen/qwen3.8-max-0902 is a proprietary model available exclusively through OpenRouter's API. It is a reasoning model that uses extended chain-of-thought (CoT) processing before producing a final answer — significantly more capable on complex math, science, and multi-step logic tasks, but slower and more expensive per query than standard models. Qwen is Alibaba's open-weights model family, with strong multilingual performance (especially Chinese/English) and a wide parameter range from 0.5B to 72B.
qwen/qwen3.8-max-0902 is priced at $2/1M input tokens and $6/1M output tokens. Output tokens are 3× more expensive than input tokens — this ratio reflects the sequential nature of autoregressive generation, which requires a separate forward pass per output token versus parallel processing of all input tokens simultaneously. At a typical usage pattern of 1,000 input tokens and 500 output tokens per call, qwen/qwen3.8-max-0902 costs approximately $5.00 per 1,000 API calls. OpenRouter does not publish a prompt caching rate for this model, so repeated long contexts are billed at the standard $2/1M input rate.
Its 1.0M-token context window is among the largest available — sufficient for processing entire codebases, book-length documents, or hours of transcribed audio in a single API call.
qwen/qwen3.8-max-0902 is best suited to reasoning, coding, chat. Supported capabilities include function calling / tool use for agentic workflows, streaming token output for real-time UIs. Function calling support makes it suitable for building AI agents, structured data extraction pipelines, and any workflow requiring the model to invoke external APIs or return typed JSON. When evaluating this model for a specific workload, the most important factors are: context window (does your input fit?), output price (how long are your generations?), and latency (is this interactive or batch?). The pricing table above shows how qwen/qwen3.8-max-0902 compares to similar models across these dimensions.
qwen/qwen3.8-max-0902 sits in the frontier tier — the highest-capability models available, used when quality is the primary constraint and cost is secondary. Unlike open-weights alternatives, qwen/qwen3.8-max-0902 is only available via OpenRouter's API — there is no self-hosted option, which simplifies deployment but creates vendor dependency. When comparing qwen/qwen3.8-max-0902 to alternatives, use the similar models section on this page to find models at comparable price points with different capability tradeoffs. The intelligence score (88/100) reflects aggregate benchmark performance — a useful proxy for general capability, though real-world performance varies significantly by task type. Always test with your specific prompts and use case before committing to a model for production.
Composite quality score based on reasoning, coding, and instruction-following benchmarks.
Input price vs 135 frontier models tracked. Avg: $5.69/1M.
| Model ID | qwen/qwen3.8-max-0902 |
| Provider | OpenRouter |
| Model Family | Qwen3.8 |
| Tier | Frontier |
| Context Window | 1,000,000 tokens (1.0M) |
| Max Output Tokens | — |
| Input Price | $2 / 1M tokens |
| Output Price | $6 / 1M tokens |
| Cached Input Price | Not available |
| Throughput | — |
| Latency (P50) | — |
| Intelligence Score | 88/100 |
| LiveBench Score | — |
| Cost per Task (LiveBench) | — |
| Data Confidence | — |
| HLE Score | — |
| GPQA Diamond | — |
| SWE-bench Score | — |
| OSWorld Score | — |
| BrowseComp Score | — |
| Terminal-Bench Score | — |
| AutoBench Score | — |
| Parameters | — |
| Vision Support | No |
| Function Calling | Yes |
| Streaming | Yes |
| Reasoning Model | Yes |
| Open Weights | No |
| Data Source | Static (verified) |
| Last Updated | 2026-10-22 |
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Self-hosting qwen/qwen3.8-max-0902? These GPUs are well-matched for this model's compute and memory requirements.