Qwen3 Reranker 8BPricing
- Input Tokens: $0.110 /M tokens
- Output Tokens: $0.110 /M tokens
Input Modalities
- Text
- Vision
Providers
Performance for qwen3-reranker-8b
Uptime is the percentage of requests that succeeded over the past 72 hours. AIHubMix continuously monitors every provider and automatically retries with the next-best provider when one returns an error or responds too slowly; Latency is total round-trip time (lower is better); Throughput is how fast the model writes (tokens per second, higher is better).
Frequently asked questions
More models from Qwen
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Qwen 3.8 Max(qwen3.8-max) is Alibaba Cloud’s flagship native vision-language model, built on a 2.4-trillion-parameter Mixture-of-Experts (MoE) architecture and supporting context windows of up to 1 million tokens. It is well suited for complex multimodal understanding, advanced reasoning, software development, agentic workflows, and long-context processing. At a similar price to Qwen3.7-Max, Qwen3.8-Max delivers significant improvements in reasoning, coding, and agent capabilities, with overall performance comparable to today’s leading models.
- Input: $ 0.338 /M
- Output: $ 1.014 /M
- Web Search: $0.000548/request
Qwen 3.8 Max Preview(Qwen3.8-Max-Preview) is the latest-generation foundation model in the Qwen family, packing 2.4T parameters and still evolving. Compared with the previous flagship Qwen 3.7 Max, it delivers major gains in core capabilities like Coding and Cowork (professional productivity), with world-leading performance on complex, long-horizon tasks such as full-stack development, data analysis, and Office workflows. Launch offer: Credits are consumed at just 20% of the standard rate, effectively 5× your usage. Limited time only.
qwen-audio-3.0-tts-flash is a high-performance speech synthesis large model optimized for real-time interactive scenarios. Compared with the previous version, the model supports more low-resource languages and Chinese dialects, improves the authenticity of dialect pronunciation, and enhances free-style instruction following and fine-grained label control, enabling more flexible control of expression such as emotion, tone, character, speaking rate, and volume. At the same time, the model exhibits stronger robustness under complex acoustic conditions like noise and reverberation, improving sound quality, clarity, and overall expressiveness. The Flash version focuses on optimizing the real-time synthesis experience, keeping first-packet latency under 200 ms, making it suitable for low-latency interactive scenarios such as voice assistants, real-time dialogue, and intelligent customer service.
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