Qwen3.5-397B-A17B

397B total parameters with 17B activated per token. It is a sparse Mixture-of-Experts model: each MoE layer holds 512 experts but routes each token through only 10 routed plus 1 shared expert, so you get large-model quality at a fraction of the per-token compute.

Yes. Qwen3.5 is a unified vision-language model with a vision encoder trained by early fusion, and its card reports results on visual reasoning and video benchmarks. Send OpenAI-style multimodal content parts (image_url) in your chat messages.

262,144 tokens natively, extensible up to 1,010,000 per the model card. The chute's default max_tokens is 1,024; the card recommends 32,768-token outputs for most queries and up to 81,920 for hard math and coding.

For thinking mode: temperature 0.6, top_p 0.95, top_k 20, min_p 0 (also the generation_config.json defaults). For non-thinking mode: temperature 0.7, top_p 0.8, top_k 20. presence_penalty between 0 and 2 reduces endless repetition, at some risk of language mixing.

Yes. The model is released under the Apache-2.0 license, which permits commercial use, modification, and redistribution.

TEE stands for Trusted Execution Environment. Inference runs inside attested confidential-compute hardware, so your prompts and the model's outputs are processed within a hardware-isolated enclave rather than on an open host.

Set base_url to https://llm.chutes.ai/v1 with your Chutes API key and model to Qwen/Qwen3.5-397B-A17B-TEE. Chat completions, raw completions, and streaming work through the standard SDK methods.

No. The model card's best practices say historical turns should contain only the final output, not the thinking content. The official chat template handles this automatically; if you manage history yourself, strip reasoning blocks before resending.