Qwen3.5 4B via DeepInfra: Latency, Throughput & Cost
Blog post from Deepinfra
Qwen3.5 4B, a part of Alibaba Cloud’s Qwen3.5 Small Model Series, is an innovative 4-billion parameter model featuring native multimodal capabilities and a compact architecture that integrates Gated Delta Networks with sparse Mixture-of-Experts to enhance throughput and minimize latency. Released in March 2026, the model supports 201 languages and offers a 262,144-token context window extendable via YaRN. It is designed for efficient processing of text, image, and video inputs, resulting in improved spatial reasoning and OCR accuracy. DeepInfra, the exclusive provider for deploying Qwen3.5 4B, offers a competitive blended price of $0.06 per million tokens and excels in speed, latency, and cost metrics, making it suitable for latency-sensitive and throughput-intensive applications. The deployment features a 0.45-second Time to First Token (TTFT), 250 tokens per second output speed, and supports function calling, positioning it as an optimal choice for real-time AI applications and complex agentic workflows.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| LLM | 2 | 5,932 | 1,046 | 223 | -2% |
| Real-time | 2 | 6,296 | 1,346 | 246 | -2% |
| AI Agents | 1 | 4,430 | 1,100 | 236 | -3% |
| AI Model Fine-tuning | 1 | 420 | 130 | 55 | -54% |
| RAG | 1 | 941 | 216 | 85 | -48% |
| Vector Search | 1 | 1,739 | 413 | 146 | -27% |
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