commit model card and model files

Co-authored-by: BoZhang <BoZhang@users.noreply.huggingface.co>
Co-authored-by: sY713 <sY713@users.noreply.huggingface.co>

.gitattributes

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+*.model filter=lfs diff=lfs merge=lfs -text
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+*.pt filter=lfs diff=lfs merge=lfs -text
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+*.safetensors filter=lfs diff=lfs merge=lfs -text
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+figures/agents-m1-benchmark.png filter=lfs diff=lfs merge=lfs -text
+figures/agents-m1.png filter=lfs diff=lfs merge=lfs -text
+logo_nobg.png filter=lfs diff=lfs merge=lfs -text
+figures/a1_benchmarks_altair_grid.pdf filter=lfs diff=lfs merge=lfs -text
+figures/a1_benchmarks_altair_grid.png filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+library_name: transformers
+license: apache-2.0
+pipeline_tag: text-generation
+---
+
+<div align="center">
+<img src="./figures/logo_nobg.png" width="20%"/>
+</div>
+
+---
+
+<div style="display: flex; justify-content: center; align-items: center; gap: 10px; flex-wrap: nowrap;">
+  <img src="./figures/hf-logo.svg" width="16" height="16" alt="Hugging Face">
+  <a href="https://huggingface.co/InternScience/Agents-A1"><b>Hugging Face</b></a>
+  <span style="color: #ccc;">|</span>
+  
+  <img src="./figures/github-logo.svg" width="16" height="16" alt="GitHub">
+  <a href="https://github.com/InternScience/Agents-A1"><b>Github</b></a>
+  <span style="color: #ccc;">|</span>
+  
+  <!-- <img src="./figures/modelscope-logo.svg" width="16" height="16" alt="Model Scope">
+  <a href="https://modelscope.cn/models/Shanghai_AI_Laboratory/Agents-A1"><b>ModelScope</b></a>
+  <span style="color: #ccc;">|</span> -->
+
+  <img src="./figures/24px.svg" width="16" height="16" alt="Technical Report" style="filter: invert(0.5);">
+  <a href="https://github.com/InternScience/Agents-A1/blob/main/Agents-A1.pdf"><b>Technical Report</b></a>
+</div>
+
+# Agents-A1: Scaling the Horizon, Not the Parameters: Reaching Trillion-Parameter Performance with a 35B Agent
+
+> [!Note]
+> This repository contains model weights and configuration files for Agents-A1 in the Hugging Face Transformers format.
+>
+> These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, etc.
+
+**Agents‑A1** is a 35B Mixture‑of‑Experts agentic model from [InternScience](https://huggingface.co/InternScience), built to scale heterogeneous agentic abilities across multiple domains including **Long‑horizon Search, Engineering, Scientific Research, Instruction Following, and Tool-calling**. We investigate agent-horizon scaling from two perspectives: scaling long-horizon trajectories and scaling heterogeneous agent abilities. 
+
+From the scaling of long-horizon trajectories, **Agents‑A1** is trained with the assistance of a domain-grounded knowledge-action infrastructure that jointly constructs actions, observations, and verifier outcomes, turning the agent's process into a trainable target. From the scaling of heterogeneous agent abilities, **Agents‑A1** presents a three-stage training paradigm for building scalable general-purpose agentic model. First, we perform full-domain supervised fine-tuning to align the base model with broad agentic behaviors. Second, we train domain-level teacher models to capture specialized expertise in each domain. Third, we propose multi-teacher multi-domain on-policy distillation with heterogeneity-aware optimization to improve knowledge transfer efficiency across different domains.
+
+
+![Agents-A1 Benchmark Overview](./figures/a1_benchmarks_altair_grid.svg)
+
+## Highlights
+
+- **Agentic Reasoning**: Agents-A1 excels at decomposing complex tasks into executable sub-steps, planning ahead, and adapting its strategy based on intermediate results.
+- **Tool Use**: Natively supports function calling and tool integration, enabling seamless interaction with APIs, code interpreters, search engines, and other external tools.
+- **Scientific and Professional Reasoning**: Handles tool-integrated scientific reasoning and professional knowledge question answering.
+- **Instruction Following**: Precisely follows detailed, multi-constraint instructions across diverse domains.
+
+We welcome developers and enterprises to integrate and try Agents-A1 and share their feedback.
+
+## Performance
+
+We evaluate Agents-A1 in real-world agentic and research-oriented workflows across six directions — long-horizon search, engineering tasks, scientific research, instruction following, general agentic tasks, and scientific agentic tasks. Despite operating in the ~35B model class, Agents-A1 delivers highly competitive performance against frontier-scale systems such as GPT-5.5, DeepSeek-V4-pro, and Kimi-K2.6. It achieves overall SOTA results on several challenging benchmarks, including Seal-0 (56.4), HiPhO (46.4), FrontierScience-Olympiad (79.0), FrontierScience-Research (40.00), IFBench (80.6), and IFEval (94.8), while also ranking as the best among comparable models on a broad range of tasks such as BrowseComp (75.5), XBench-DS-2510 (86.0), GAIA (96.0), SciCode (44.3), HLE with tools (47.6), and MolBench-bind (56.8). These results show that Agents-A1 combines strong long-horizon search ability, robust scientific reasoning, and reliable instruction following, establishing it as a highly capable and efficient agentic model that narrows the gap with much larger frontier models.
+
+
+<p>
+🥇 Overall SOTA &nbsp;&nbsp;
+🟢 Best Among Comparable Models (~35B)
+</p>
+
+<table>
+<thead>
+<tr>
+<th rowspan="2" align="left">Benchmark</th>
+<th colspan="3" align="center" style="text-align:center;">
+    📏 Comparable Models (~35B)
+</th>
+
+<th colspan="4" align="center" style="text-align:center;">
+    🚀 Larger-scale Models
+</th>
+
+<th colspan="2" align="center" style="text-align:center;">
+    ⭐ Ours
+</th>
+</tr>
+
+<tr>
+<th align="center">Qwen3.5-35B-A3B</th>
+<th align="center">Qwen3.6-35B-A3B</th>
+<th align="center">Nex-N2-mini</th>
+  
+<th align="center">Step-3.5-Flash</th>
+<th align="center">Kimi-K2.6</th>
+<th align="center">DeepSeek-V4-pro(Max)</th>
+<th align="center">GPT-5.5(xhigh)</th>
+
+<th align="center">Agents-A1</th>
+</tr>
+</thead>
+
+<tbody>
+
+<tr>
+    <td colspan="9" align="left"><b>🔍 Long-horizon Search</b></td>
+</tr>
+
+<tr>
+<td align="left">BrowseComp</td>
+<td align="center">61.0</td>
+<td align="center">67.93</td>
+<td align="center">74.1</td>
+<td align="center">69.0</td>
+<td align="center">83.2</td>
+<td align="center">83.4</td>
+<td align="center">🥇 84.4</td>
+<td align="center">🟢 75.51</td>
+</tr>
+
+<tr>
+<td align="left">XBench-DS-2510</td>
+<td align="center">77.0</td>
+<td align="center">71.0</td>
+<td align="center">82.0</td>
+<td align="center">56.3</td>
+<td align="center">🥇 90.0</td>
+<td align="center">🥇 90.0</td>
+<td align="center">84.0</td>
+<td align="center">🟢 86.0</td>
+</tr>
+
+<tr>
+<td align="left">Seal0</td>
+<td align="center">41.4</td>
+<td align="center">38.74</td>
+<td align="center">49.55</td>
+<td align="center">36.94</td>
+<td align="center">50.45</td>
+<td align="center">54.95</td>
+<td align="center">42.34</td>
+<td align="center">🥇 56.36</td>
+</tr>
+
+<tr>
+<td align="left">GAIA</td>
+<td align="center">59.8</td>
+<td align="center">78.64</td>
+<td align="center">82.52</td>
+<td align="center">84.5</td>
+<td align="center">80.58</td>
+<td align="center">🥇 98.06</td>
+<td align="center">87.38</td>
+<td align="center">🟢 96.04</td>
+</tr>
+
+<tr>
+    <td colspan="9" align="left"><b>⚙️ Engineering Tasks</b></td>
+</tr>
+
+<tr>
+<td align="left">SciCode</td>
+<td align="center">37.7</td>
+<td align="center">35.8</td>
+<td align="center">29.9</td>
+<td align="center">40.4</td>
+<td align="center">53.5</td>
+<td align="center">50.0</td>
+<td align="center">🥇 56.1</td>
+<td align="center">🟢 44.33</td>
+</tr>
+
+<tr>
+<td align="left">MLE-Lite</td>
+<td align="center">24.24</td>
+<td align="center">34.85</td>
+<td align="center">34.85</td>
+<td align="center">54.55</td>
+<td align="center">62.12</td>
+<td align="center">63.64</td>
+<td align="center">🥇 72.73</td>
+<td align="center">🟢 43.94</td>
+</tr>
+
+<tr>
+    <td colspan="9" align="left"><b>🧪 Scientific Research</b></td>
+</tr>
+
+<tr>
+<td align="left">HLE w/ tools</td>
+<td align="center">47.4</td>
+<td align="center">36.2</td>
+<td align="center">32.0</td>
+<td align="center">23.1</td>
+<td align="center">🥇 54.0</td>
+<td align="center">48.2</td>
+<td align="center">52.2</td>
+<td align="center">🟢 47.6</td>
+</tr>
+
+<tr>
+<td align="left">HiPhO</td>
+<td align="center">37.0</td>
+<td align="center">37.7</td>
+<td align="center">38.5</td>
+<td align="center">38.3</td>
+<td align="center">41.1</td>
+<td align="center">38.7</td>
+<td align="center">43.3</td>
+<td align="center">🥇 46.4</td>
+</tr>
+
+<tr>
+<td align="left">FrontierScience-Olympiad</td>
+<td align="center">64.5</td>
+<td align="center">60.3</td>
+<td align="center">52.0</td>
+<td align="center">61.0</td>
+<td align="center">73.0</td>
+<td align="center">76.0</td>
+<td align="center">78.0</td>
+<td align="center">🥇 79.0</td>
+</tr>
+
+<tr>
+<td align="left">FrontierScience-Research</td>
+<td align="center">2.5</td>
+<td align="center">2.9</td>
+<td align="center">5.0</td>
+<td align="center">6.7</td>
+<td align="center">17.9</td>
+<td align="center">13.3</td>
+<td align="center">26.7</td>
+<td align="center">🥇 40.0</td>
+</tr>
+
+<tr>
+    <td colspan="9" align="left"><b>📋 Instruction Following</b></td>
+</tr>
+
+<tr>
+<td align="left">IFBench</td>
+<td align="center">70.2</td>
+<td align="center">64.4</td>
+<td align="center">54.08</td>
+<td align="center">64.6</td>
+<td align="center">71.77</td>
+<td align="center">73.47</td>
+<td align="center">75.9</td>
+<td align="center">🥇 80.61</td>
+</tr>
+
+<tr>
+<td align="left">LongBench-v2</td>
+<td align="center">59.0</td>
+<td align="center">57.7</td>
+<td align="center">59.6</td>
+<td align="center">57.5</td>
+<td align="center">62.0</td>
+<td align="center">🥇 64.3</td>
+<td align="center">-</td>
+<td align="center">🟢 60.2</td>
+</tr>
+
+<tr>
+<td align="left">IFEval</td>
+<td align="center">91.9</td>
+<td align="center">91.3</td>
+<td align="center">88.4</td>
+<td align="center">93.53</td>
+<td align="center">94.45</td>
+<td align="center">93.35</td>
+<td align="center">93.35</td>
+<td align="center">🥇 94.82</td>
+</tr>
+
+<tr>
+    <td colspan="9" align="left"><b>🤖 General Agentic Tasks</b></td>
+</tr>
+
+<tr>
+<td align="left">τ<sup>2</sup>-Bench</td>
+<td align="center">🟢 81.2</td>
+<td align="center">79.0</td>
+<td align="center">74.53</td>
+<td align="center">75.77</td>
+<td align="center">81.93</td>
+<td align="center">🥇 82.2</td>
+<td align="center">81.63</td>
+<td align="center">79.81</td>
+</tr>
+
+<tr>
+<td align="left">VitaBench</td>
+<td align="center">31.9</td>
+<td align="center">35.6</td>
+<td align="center">23.0</td>
+<td align="center">30.0</td>
+<td align="center">35.63</td>
+<td align="center">🥇 49.04</td>
+<td align="center">45.0</td>
+<td align="center">🟢 38.75</td>
+</tr>
+
+<tr>
+    <td colspan="9" align="left"><b>🔬 Scientific Agentic Tasks</b></td>
+</tr>
+
+<tr>
+<td align="left">MatTools</td>
+<td align="center">21.0</td>
+<td align="center">15.9</td>
+<td align="center">34.1</td>
+<td align="center">44.93</td>
+<td align="center">63.8</td>
+<td align="center">47.1</td>
+<td align="center">🥇 68.8</td>
+<td align="center">🟢 47.1</td>
+</tr>
+
+<tr>
+<td align="left">MolBench-bind</td>
+<td align="center">46.0</td>
+<td align="center">48.7</td>
+<td align="center">51.4</td>
+<td align="center">45.95</td>
+<td align="center">21.6</td>
+<td align="center">37.8</td>
+<td align="center">🥇 62.2</td>
+<td align="center">🟢 56.8</td>
+</tr>
+
+</tbody>
+</table>
+
+
+## Usage
+
+### SGLang
+
+[SGLang](https://github.com/sgl-project/sglang) is a fast serving framework for large language models and vision language models.
+
+Install SGLang with uv:
+
+```shell
+uv venv --python 3.12 --seed --managed-python
+source .venv/bin/activate
+
+uv pip install sglang
+```
+
+See [its documentation](https://docs.sglang.ai/get_started/install.html) for more details.
+
+The following commands create API endpoints at `http://localhost:8000/v1`:
+
+- **Standard Version** (1 GPUs, 262K context):
+
+  ```shell
+  python -m sglang.launch_server \
+    --model-path InternScience/Agents-A1 \
+    --port 8000 \
+    --tp-size 1 \
+    --mem-fraction-static 0.8 \
+    --context-length 262144 \
+    --reasoning-parser qwen3
+  ```
+- **Tool Use**:
+
+  ```shell
+  python -m sglang.launch_server \
+    --model-path InternScience/Agents-A1 \
+    --port 8000 \
+    --tp-size 1 \
+    --mem-fraction-static 0.8 \
+    --context-length 262144 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
+  ```
+
+### vLLM
+
+[vLLM](https://github.com/vllm-project/vllm) is a high-throughput and memory-efficient inference and serving engine for LLMs.
+
+Install vLLM from the main branch via uv:
+
+```shell
+uv venv --python 3.12 --seed --managed-python
+source .venv/bin/activate
+
+uv pip install vllm --torch-backend=auto
+```
+
+See [its documentation](https://docs.vllm.ai/en/stable/getting_started/installation/index.html) for more details.
+
+The following commands create API endpoints at `http://localhost:8000/v1`:
+
+- **Standard Version** (1 GPUs, 262K context):
+
+  ```shell
+  vllm serve InternScience/Agents-A1 \
+    --port 8000 \
+    --tensor-parallel-size 1 \
+    --max-model-len 262144 \
+    --reasoning-parser qwen3
+  ```
+- **Tool Call**:
+
+  ```shell
+  vllm serve InternScience/Agents-A1 \
+    --port 8000 \
+    --tensor-parallel-size 1 \
+    --max-model-len 262144 \
+    --reasoning-parser qwen3 \
+    --enable-auto-tool-choice \
+    --tool-call-parser qwen3_coder
+  ```
+- **Text-Only** (skips vision encoder to free KV cache memory):
+
+  ```shell
+  vllm serve InternScience/Agents-A1 \
+    --port 8000 \
+    --tensor-parallel-size 1 \
+    --max-model-len 262144 \
+    --reasoning-parser qwen3 \
+    --language-model-only
+  ```
+
+### Recommended Sampling Parameters
+
+For the best generation quality, we recommend the following sampling parameters:
+
+- `temperature`: 0.85
+- `top_p`: 0.95
+- `top_k`: 20
+- `min_p`: 0.0
+- `presence_penalty`: 1.1
+- `repetition_penalty`: 1.0
+  
+
+## Agent Capability Evaluation
+
+To provide the community with a unified agent evaluation codebase for fair comparison, we have also open-sourced an evaluation framework for assessing agentic models across core capabilities, including tool use and multi-step reasoning. The evaluation code is included in the [Agents-A1/evaluation](https://github.com/InternScience/Agents-A1/tree/main/evaluation) of this repository.
+
+We use this framework to evaluate the released model under a standardized and reproducible setting. 
+Specifically, the model is tested on a set of agent-oriented tasks that require it to understand user goals, decompose complex instructions, interact with tools or environments when necessary, and produce final results. The evaluation results reported in [Model Card](https://huggingface.co/InternScience/Agents-A1) are generated using the open-source framework above, so that users can reproduce the experiments, compare other models under the same protocol, and further extend the benchmark for new agent scenarios. (**Note that:** To ensure a fair comparison, we report the benchmark results from their original technical reports. If a model does not report the corresponding benchmark results, we evaluate it using the same evaluation protocol as our model.)
+
+For detailed evaluation scripts, task definitions, metrics, and reproduction instructions, please refer to the evaluation codebase.
+
+## Citation
+
+If you find our work helpful, feel free to give us a cite.
+
+```
+
+```

chat_template.jinja

@@ -0,0 +1,154 @@
+{%- set image_count = namespace(value=0) %}
+{%- set video_count = namespace(value=0) %}
+{%- macro render_content(content, do_vision_count, is_system_content=false) %}
+    {%- if content is string %}
+        {{- content }}
+    {%- elif content is iterable and content is not mapping %}
+        {%- for item in content %}
+            {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
+                {%- if is_system_content %}
+                    {{- raise_exception('System message cannot contain images.') }}
+                {%- endif %}
+                {%- if do_vision_count %}
+                    {%- set image_count.value = image_count.value + 1 %}
+                {%- endif %}
+                {%- if add_vision_id %}
+                    {{- 'Picture ' ~ image_count.value ~ ': ' }}
+                {%- endif %}
+                {{- '<|vision_start|><|image_pad|><|vision_end|>' }}
+            {%- elif 'video' in item or item.type == 'video' %}
+                {%- if is_system_content %}
+                    {{- raise_exception('System message cannot contain videos.') }}
+                {%- endif %}
+                {%- if do_vision_count %}
+                    {%- set video_count.value = video_count.value + 1 %}
+                {%- endif %}
+                {%- if add_vision_id %}
+                    {{- 'Video ' ~ video_count.value ~ ': ' }}
+                {%- endif %}
+                {{- '<|vision_start|><|video_pad|><|vision_end|>' }}
+            {%- elif 'text' in item %}
+                {{- item.text }}
+            {%- else %}
+                {{- raise_exception('Unexpected item type in content.') }}
+            {%- endif %}
+        {%- endfor %}
+    {%- elif content is none or content is undefined %}
+        {{- '' }}
+    {%- else %}
+        {{- raise_exception('Unexpected content type.') }}
+    {%- endif %}
+{%- endmacro %}
+{%- if not messages %}
+    {{- raise_exception('No messages provided.') }}
+{%- endif %}
+{%- if tools and tools is iterable and tools is not mapping %}
+    {{- '<|im_start|>system\n' }}
+    {{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>" }}
+    {{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
+    {%- if messages[0].role == 'system' %}
+        {%- set content = render_content(messages[0].content, false, true)|trim %}
+        {%- if content %}
+            {{- '\n\n' + content }}
+        {%- endif %}
+    {%- endif %}
+    {{- '<|im_end|>\n' }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {%- set content = render_content(messages[0].content, false, true)|trim %}
+        {{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" %}
+        {%- set content = render_content(message.content, false)|trim %}
+        {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
+            {%- set ns.multi_step_tool = false %}
+            {%- set ns.last_query_index = index %}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if ns.multi_step_tool %}
+    {{- raise_exception('No user query found in messages.') }}
+{%- endif %}
+{%- for message in messages %}
+    {%- set content = render_content(message.content, true)|trim %}
+    {%- if message.role == "system" %}
+        {%- if not loop.first %}
+            {{- raise_exception('System message must be at the beginning.') }}
+        {%- endif %}
+    {%- elif message.role == "user" %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- set reasoning_content = reasoning_content|trim %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if tool_call.function is defined %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {%- if loop.first %}
+                    {%- if content|trim %}
+                        {{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                    {%- else %}
+                        {{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                    {%- endif %}
+                {%- else %}
+                    {{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                {%- endif %}
+                {%- if tool_call.arguments is defined %}
+                    {%- for args_name, args_value in tool_call.arguments|items %}
+                        {{- '<parameter=' + args_name + '>\n' }}
+                        {%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
+                        {{- args_value }}
+                        {{- '\n</parameter>\n' }}
+                    {%- endfor %}
+                {%- endif %}
+                {{- '</function>\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.previtem and loop.previtem.role != "tool" %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if not loop.last and loop.nextitem.role != "tool" %}
+            {{- '<|im_end|>\n' }}
+        {%- elif loop.last %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- else %}
+        {{- raise_exception('Unexpected message role.') }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- else %}
+        {{- '<think>\n' }}
+    {%- endif %}
+{%- endif %}

config.json

@@ -0,0 +1,115 @@
+{
+    "architectures": [
+        "Qwen3_5MoeForConditionalGeneration"
+    ],
+    "image_token_id": 248056,
+    "model_type": "qwen3_5_moe",
+    "text_config": {
+        "attention_bias": false,
+        "attention_dropout": 0.0,
+        "attn_output_gate": true,
+        "dtype": "bfloat16",
+        "eos_token_id": 248044,
+        "full_attention_interval": 4,
+        "head_dim": 256,
+        "hidden_act": "silu",
+        "hidden_size": 2048,
+        "initializer_range": 0.02,
+        "layer_types": [
+            "linear_attention",
+            "linear_attention",
+            "linear_attention",
+            "full_attention",
+            "linear_attention",
+            "linear_attention",
+            "linear_attention",
+            "full_attention",
+            "linear_attention",
+            "linear_attention",
+            "linear_attention",
+            "full_attention",
+            "linear_attention",
+            "linear_attention",
+            "linear_attention",
+            "full_attention",
+            "linear_attention",
+            "linear_attention",
+            "linear_attention",
+            "full_attention",
+            "linear_attention",
+            "linear_attention",
+            "linear_attention",
+            "full_attention",
+            "linear_attention",
+            "linear_attention",
+            "linear_attention",
+            "full_attention",
+            "linear_attention",
+            "linear_attention",
+            "linear_attention",
+            "full_attention",
+            "linear_attention",
+            "linear_attention",
+            "linear_attention",
+            "full_attention",
+            "linear_attention",
+            "linear_attention",
+            "linear_attention",
+            "full_attention"
+        ],
+        "linear_conv_kernel_dim": 4,
+        "linear_key_head_dim": 128,
+        "linear_num_key_heads": 16,
+        "linear_num_value_heads": 32,
+        "linear_value_head_dim": 128,
+        "max_position_embeddings": 262144,
+        "mlp_only_layers": [],
+        "model_type": "qwen3_5_moe_text",
+        "moe_intermediate_size": 512,
+        "mtp_num_hidden_layers": 1,
+        "mtp_use_dedicated_embeddings": false,
+        "num_attention_heads": 16,
+        "num_experts": 256,
+        "num_experts_per_tok": 8,
+        "num_hidden_layers": 40,
+        "num_key_value_heads": 2,
+        "rms_norm_eps": 1e-06,
+        "router_aux_loss_coef": 0.001,
+        "shared_expert_intermediate_size": 512,
+        "use_cache": true,
+        "vocab_size": 248320,
+        "mamba_ssm_dtype": "float32",
+        "rope_parameters": {
+            "mrope_interleaved": true,
+            "mrope_section": [
+                11,
+                11,
+                10
+            ],
+            "rope_type": "default",
+            "rope_theta": 10000000,
+            "partial_rotary_factor": 0.25
+        }
+    },
+    "tie_word_embeddings": false,
+    "transformers_version": "4.57.0.dev0",
+    "video_token_id": 248057,
+    "vision_config": {
+        "deepstack_visual_indexes": [],
+        "depth": 27,
+        "hidden_act": "gelu_pytorch_tanh",
+        "hidden_size": 1152,
+        "in_channels": 3,
+        "initializer_range": 0.02,
+        "intermediate_size": 4304,
+        "model_type": "qwen3_5_moe",
+        "num_heads": 16,
+        "num_position_embeddings": 2304,
+        "out_hidden_size": 2048,
+        "patch_size": 16,
+        "spatial_merge_size": 2,
+        "temporal_patch_size": 2
+    },
+    "vision_end_token_id": 248054,
+    "vision_start_token_id": 248053
+}

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preprocessor_config.json

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+{
+    "size": {
+        "longest_edge": 16777216,
+        "shortest_edge": 65536
+    },
+    "patch_size": 16,
+    "temporal_patch_size": 2,
+    "merge_size": 2,
+    "image_mean": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "image_std": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "processor_class": "Qwen3VLProcessor",
+    "image_processor_type": "Qwen2VLImageProcessorFast"
+}

processor_config.json

@@ -0,0 +1,60 @@
+{
+  "image_processor": {
+    "do_convert_rgb": true,
+    "do_normalize": true,
+    "do_rescale": true,
+    "do_resize": true,
+    "image_mean": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "image_processor_type": "Qwen2VLImageProcessor",
+    "image_std": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "merge_size": 2,
+    "patch_size": 16,
+    "resample": 3,
+    "rescale_factor": 0.00392156862745098,
+    "size": {
+      "longest_edge": 16777216,
+      "shortest_edge": 65536
+    },
+    "temporal_patch_size": 2
+  },
+  "processor_class": "Qwen3VLProcessor",
+  "video_processor": {
+    "do_convert_rgb": true,
+    "do_normalize": true,
+    "do_rescale": true,
+    "do_resize": true,
+    "do_sample_frames": true,
+    "fps": 2,
+    "image_mean": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "image_std": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "max_frames": 768,
+    "merge_size": 2,
+    "min_frames": 4,
+    "patch_size": 16,
+    "resample": 3,
+    "rescale_factor": 0.00392156862745098,
+    "return_metadata": false,
+    "size": {
+      "longest_edge": 25165824,
+      "shortest_edge": 4096
+    },
+    "temporal_patch_size": 2,
+    "video_processor_type": "Qwen3VLVideoProcessor"
+  }
+}

tokenizer.json

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+size 19989343

tokenizer_config.json

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+    "add_prefix_space": false,
+    "added_tokens_decoder": {
+        "248044": {
+            "content": "<|endoftext|>",
+            "lstrip": false,
+            "normalized": false,
+            "rstrip": false,
+            "single_word": false,
+            "special": true
+        },
+        "248045": {
+            "content": "<|im_start|>",
+            "lstrip": false,
+            "normalized": false,
+            "rstrip": false,
+            "single_word": false,
+            "special": true
+        },
+        "248046": {
+            "content": "<|im_end|>",
+            "lstrip": false,
+            "normalized": false,
+            "rstrip": false,
+            "single_word": false,
+            "special": true
+        },
+        "248047": {
+            "content": "<|object_ref_start|>",
+            "lstrip": false,
+            "normalized": false,
+            "rstrip": false,
+            "single_word": false,
+            "special": true
+        },
+        "248048": {
+            "content": "<|object_ref_end|>",
+            "lstrip": false,
+            "normalized": false,
+            "rstrip": false,
+            "single_word": false,
+            "special": true
+        },
+        "248049": {
+            "content": "<|box_start|>",
+            "lstrip": false,
+            "normalized": false,
+            "rstrip": false,
+            "single_word": false,
+            "special": true
+        },
+        "248050": {
+            "content": "<|box_end|>",
+            "lstrip": false,
+            "normalized": false,
+            "rstrip": false,
+            "single_word": false,
+            "special": true
+        },
+        "248051": {
+            "content": "<|quad_start|>",
+            "lstrip": false,
+            "normalized": false,
+            "rstrip": false,
+            "single_word": false,
+            "special": true
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+            "special": true
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+            "normalized": false,
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+            "special": true
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+            "normalized": false,
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+            "special": true
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+            "content": "<|image_pad|>",
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+            "special": true
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+            "lstrip": false,
+            "normalized": false,
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+            "single_word": false,
+            "special": false
+        },
+        "248059": {
+            "content": "</tool_call>",
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+            "normalized": false,
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+            "single_word": false,
+            "special": false
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+    ],
+    "bos_token": null,
+    "chat_template": "{%- set image_count = namespace(value=0) %}\n{%- set video_count = namespace(value=0) %}\n{%- macro render_content(content, do_vision_count, is_system_content=false) %}\n    {%- if content is string %}\n        {{- content }}\n    {%- elif content is iterable and content is not mapping %}\n        {%- for item in content %}\n            {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}\n                {%- if is_system_content %}\n                    {{- raise_exception('System message cannot contain images.') }}\n                {%- endif %}\n                {%- if do_vision_count %}\n                    {%- set image_count.value = image_count.value + 1 %}\n                {%- endif %}\n                {%- if add_vision_id %}\n                    {{- 'Picture ' ~ image_count.value ~ ': ' }}\n                {%- endif %}\n                {{- '<|vision_start|><|image_pad|><|vision_end|>' }}\n            {%- elif 'video' in item or item.type == 'video' %}\n                {%- if is_system_content %}\n                    {{- raise_exception('System message cannot contain videos.') }}\n                {%- endif %}\n                {%- if do_vision_count %}\n                    {%- set video_count.value = video_count.value + 1 %}\n                {%- endif %}\n                {%- if add_vision_id %}\n                    {{- 'Video ' ~ video_count.value ~ ': ' }}\n                {%- endif %}\n                {{- '<|vision_start|><|video_pad|><|vision_end|>' }}\n            {%- elif 'text' in item %}\n                {{- item.text }}\n            {%- else %}\n                {{- raise_exception('Unexpected item type in content.') }}\n            {%- endif %}\n        {%- endfor %}\n    {%- elif content is none or content is undefined %}\n        {{- '' }}\n    {%- else %}\n        {{- raise_exception('Unexpected content type.') }}\n    {%- endif %}\n{%- endmacro %}\n{%- if not messages %}\n    {{- raise_exception('No messages provided.') }}\n{%- endif %}\n{%- if tools and tools is iterable and tools is not mapping %}\n    {{- '<|im_start|>system\\n' }}\n    {{- \"# Tools\\n\\nYou have access to the following functions:\\n\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\" }}\n    {{- '\\n\\nIf you choose to call a function ONLY reply in the following format with NO suffix:\\n\\n<tool_call>\\n<function=example_function_name>\\n<parameter=example_parameter_1>\\nvalue_1\\n</parameter>\\n<parameter=example_parameter_2>\\nThis is the value for the second parameter\\nthat can span\\nmultiple lines\\n</parameter>\\n</function>\\n</tool_call>\\n\\n<IMPORTANT>\\nReminder:\\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\\n- Required parameters MUST be specified\\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\\n</IMPORTANT>' }}\n    {%- if messages[0].role == 'system' %}\n        {%- set content = render_content(messages[0].content, false, true)|trim %}\n        {%- if content %}\n            {{- '\\n\\n' + content }}\n        {%- endif %}\n    {%- endif %}\n    {{- '<|im_end|>\\n' }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {%- set content = render_content(messages[0].content, false, true)|trim %}\n        {{- '<|im_start|>system\\n' + content + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n    {%- set index = (messages|length - 1) - loop.index0 %}\n    {%- if ns.multi_step_tool and message.role == \"user\" %}\n        {%- set content = render_content(message.content, false)|trim %}\n        {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}\n            {%- set ns.multi_step_tool = false %}\n            {%- set ns.last_query_index = index %}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if ns.multi_step_tool %}\n    {{- raise_exception('No user query found in messages.') }}\n{%- endif %}\n{%- for message in messages %}\n    {%- set content = render_content(message.content, true)|trim %}\n    {%- if message.role == \"system\" %}\n        {%- if not loop.first %}\n            {{- raise_exception('System message must be at the beginning.') }}\n        {%- endif %}\n    {%- elif message.role == \"user\" %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {%- set reasoning_content = '' %}\n        {%- if message.reasoning_content is string %}\n            {%- set reasoning_content = message.reasoning_content %}\n        {%- else %}\n            {%- if '</think>' in content %}\n                {%- set reasoning_content = content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n                {%- set content = content.split('</think>')[-1].lstrip('\\n') %}\n            {%- endif %}\n        {%- endif %}\n        {%- set reasoning_content = reasoning_content|trim %}\n        {%- if loop.index0 > ns.last_query_index %}\n            {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content + '\\n</think>\\n\\n' + content }}\n        {%- else %}\n            {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- endif %}\n        {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if tool_call.function is defined %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {%- if loop.first %}\n                    {%- if content|trim %}\n                        {{- '\\n\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                    {%- else %}\n                        {{- '<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                    {%- endif %}\n                {%- else %}\n                    {{- '\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                {%- endif %}\n                {%- if tool_call.arguments is defined %}\n                    {%- for args_name, args_value in tool_call.arguments|items %}\n                        {{- '<parameter=' + args_name + '>\\n' }}\n                        {%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}\n                        {{- args_value }}\n                        {{- '\\n</parameter>\\n' }}\n                    {%- endfor %}\n                {%- endif %}\n                {{- '</function>\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.previtem and loop.previtem.role != \"tool\" %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if not loop.last and loop.nextitem.role != \"tool\" %}\n            {{- '<|im_end|>\\n' }}\n        {%- elif loop.last %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- else %}\n        {{- raise_exception('Unexpected message role.') }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n    {%- if enable_thinking is defined and enable_thinking is false %}\n        {{- '<think>\\n\\n</think>\\n\\n' }}\n    {%- else %}\n        {{- '<think>\\n' }}\n    {%- endif %}\n{%- endif %}",
+    "clean_up_tokenization_spaces": false,
+    "eos_token": "<|im_end|>",
+    "errors": "replace",
+    "model_max_length": 262144,
+    "pad_token": "<|endoftext|>",
+    "split_special_tokens": false,
+    "tokenizer_class": "Qwen2Tokenizer",
+    "unk_token": null,
+    "add_bos_token": false,
+    "pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
+    "extra_special_tokens": {
+        "audio_bos_token": "<|audio_start|>",
+        "audio_eos_token": "<|audio_end|>",
+        "audio_token": "<|audio_pad|>",
+        "image_token": "<|image_pad|>",
+        "video_token": "<|video_pad|>",
+        "vision_bos_token": "<|vision_start|>",
+        "vision_eos_token": "<|vision_end|>"
+    }
+}

video_preprocessor_config.json

@@ -0,0 +1,21 @@
+{
+    "size": {
+        "longest_edge": 25165824,
+        "shortest_edge": 4096
+    },
+    "patch_size": 16,
+    "temporal_patch_size": 2,
+    "merge_size": 2,
+    "image_mean": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "image_std": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "processor_class": "Qwen3VLProcessor",
+    "video_processor_type": "Qwen3VLVideoProcessor"
+}