How does Qwen3.8 Flash rank among AI models?
Qwen3.8 Flash holds ModelCap Index position #89 of 351 ranked language models as of 18 October 2026, with an Index score of 57.1 (interval 44.9–69.2); evidence: modeled · succession. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.
How much does Qwen3.8 Flash cost per 1M tokens?
Qwen3.8 Flash is listed at $0.15 per 1M input tokens and $0.47 per 1M output tokens as of 18 October 2026. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $0.535 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.
What is the context window of Qwen3.8 Flash?
Qwen3.8 Flash has a published context window of 1M tokens (1,000,000). The snapshot lists a 131,072 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.
Is Qwen3.8 Flash open-weight?
Restricted license (qwen-community-1.0). Downloadable weights use a model-specific or use-restricted license. Review the linked license before use, redistribution, or commercial deployment. The repository is Qwen/Qwen3.8-Flash-Next on Hugging Face.
Which API providers serve Qwen3.8 Flash?
One provider serves Qwen3.8 Flash through OpenRouter as of 18 October 2026: Alibaba. Each provider's price, context limit, quantization and measured uptime are in the providers table above.
Which benchmarks has Qwen3.8 Flash been evaluated on?
Qwen3.8 Flash has published results on 3 public boards tracked by ModelCap as of 18 October 2026: AA Intelligence Index 39.8 (#45 of 134), AA Terminal-Bench 2.1 86.1% (#13 of 128) and AA Humanity's Last Exam 38.0% (#56 of 267). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.