[AMD] [Qwen 3.5 Day 0] Add Qwen 3.5 nightly accuracy tests (#19479)

docs/supported_models/text_generation/generative_models.md

@@ -29,7 +29,7 @@ in the GitHub search bar.
 | **Kimi K2** (Thinking, Instruct)    | `moonshotai/Kimi-K2-Instruct`                    | Moonshot AI's 1 trillion parameter MoE model (32B active) with 128K–256K context; state-of-the-art agentic intelligence with stable long-horizon agency across 200–300 sequential tool calls. Features MLA attention and native INT4 quantization. [See Reasoning Parser docs](../advanced_features/separate_reasoning.ipynb)|
 | **Kimi Linear** (48B-A3B)           | `moonshotai/Kimi-Linear-48B-A3B-Instruct`        | Moonshot AI's hybrid linear attention model (48B total, 3B active) with 1M token context; features Kimi Delta Attention (KDA) for up to 6× faster decoding and 75% KV cache reduction vs full attention. |
 | **GPT-OSS**       | `openai/gpt-oss-20b`, `openai/gpt-oss-120b`       | OpenAI’s latest GPT-OSS series for complex reasoning, agentic tasks, and versatile developer use cases.|
-| **Qwen** (3, 3MoE, 3Next, 2.5, 2 series)       | `Qwen/Qwen3-0.6B`, `Qwen/Qwen3-30B-A3B` `Qwen/Qwen3-Next-80B-A3B-Instruct `      | Alibaba’s latest Qwen3 series for complex reasoning, language understanding, and generation tasks; Support for MoE variants along with previous generation 2.5, 2, etc. [SGLang provides Qwen3 specific reasoning parser](../advanced_features/separate_reasoning.ipynb)|
+| **Qwen** (3.5, 3, 3MoE, 3Next, 2.5, 2 series)       | `Qwen/Qwen3.5-397B-A17B`, `Qwen/Qwen3-0.6B`, `Qwen/Qwen3-30B-A3B`      | Alibaba’s latest Qwen3 series for complex reasoning, language understanding, and generation tasks; Support for MoE variants along with previous generation 2.5, 2, etc. [SGLang provides Qwen3 specific reasoning parser](../advanced_features/separate_reasoning.ipynb)|
 | **Llama** (2, 3.x, 4 series)        | `meta-llama/Llama-4-Scout-17B-16E-Instruct`       | Meta's open LLM series, spanning 7B to 400B parameters (Llama 2, 3, and new Llama 4) with well-recognized performance. [SGLang provides Llama-4 model-specific optimizations](../basic_usage/llama4.md)  |
 | **Mistral** (Mixtral, NeMo, Small3) | `mistralai/Mistral-7B-Instruct-v0.2`             | Open 7B LLM by Mistral AI with strong performance; extended into MoE (“Mixtral”) and NeMo Megatron variants for larger scale. |
 | **Gemma** (v1, v2, v3)              | `google/gemma-3-1b-it`                            | Google’s family of efficient multilingual models (1B–27B); Gemma 3 offers a 128K context window, and its larger (4B+) variants support vision input. |