Qwen3.5 35B A3B is a multimodal Mixture-of-Experts (MoE) large language model designed for efficient long-context reasoning, multimodal understanding, and scalable deployment. The model contains 35B total parameters with ~3B active parameters, activating 8 routed experts plus 1 shared expert from 256 experts per token. It features a 40-layer hybrid architecture combining Gated DeltaNet and full attention layers, with 16 attention heads and a 2,048 hidden size. The model supports a 262K token context window, extendable to ~1M, and integrates a 27-layer vision encoder for unified multimodal processing.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (Qwen/Qwen3.5-35B-A3B). Released under Apache 2.0. Further reading: Blog
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2,048 GB
1,440 GB
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Benchmarks measured by Vultr on MI325X · vLLM. Throughput and latency vary with concurrency, input length and engine configuration, so treat these as a comparison baseline, not a service guarantee.