Duplicate from eadx/Rio-3.5-Open-397B

Co-authored-by: dx <eadx@users.noreply.huggingface.co>

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+library_name: transformers
+language:
+- pt
+- en
+license: mit
+base_model:
+- Qwen/Qwen3.5-397B-A17B
+pipeline_tag: image-text-to-text
+---
+
+# Rio 3.5 Open 397B
+
+![Rio 3.5 Open 397B benchmark results](rio-3.5-open-benchmarks.png)
+
+**Rio 3.5 Open 397B** is a frontier-class general-purpose AI model developed by [IplanRIO](https://iplanrio.rio.rj.gov.br/), the municipal IT company of Rio de Janeiro's city government. Post-trained from Qwen 3.5 397B, Rio 3.5 Open 397B delivers state-of-the-art open-model performance across agentic coding, mathematics, STEM, multilingual, and multimodal benchmarks — surpassing its base model by significant margins and competing with the world's best open and proprietary models.
+
+Rio 3.5 Open 397B features **SwiReasoning**, a training-free inference framework based on [Shi et al. (2025)](https://arxiv.org/abs/2510.05069) that dynamically switches between explicit chain-of-thought and latent-space reasoning, guided by entropy-based confidence signals. This enables both higher accuracy and dramatically improved token efficiency. This model was explicitly trained to maximize the efficiency gained via latent reasoning.
+
+## Key Features
+
+- **397B total / 17B active parameters** (Mixture-of-Experts)
+- **1,010,000 token (1M) context window**
+- **SwiReasoning integration** — dynamic explicit/latent reasoning switching for Pareto-superior accuracy and efficiency
+- **General-purpose** — strong agentic coding, reasoning, instruction-following, and multimodal performance
+- **Post-trained from Qwen 3.5 397B**
+- **Multilingual** — strong performance in Portuguese, English, Chinese, and dozens of other languages
+- **MIT License** — fully open for commercial and research use
+
+## Benchmark Results
+
+### Agentic Coding & Software Engineering
+
+| Benchmark | Rio 3.5 Open 397B | Qwen 3.5 397B (base) | Qwen 3.7 Plus | DeepSeek V4 Pro | Kimi-K2.6 | GPT 5.5 |
+|:---|:---:|:---:|:---:|:---:|:---:|:---:|
+| Terminal-Bench 2.1 | 70.8 | 52.5 | 70.3 | 67.9 | 66.7 | **78.2** |
+| DeepSWE | 23.0 | 6.0 | – | 8.0 | 24.0 | **70.0** |
+| SWE-Bench Pro | 58.1 | 50.9 | 57.6 | 59.0 | **59.5** | 58.6 |
+| SWE-Bench Verified | 80.2 | 76.2 | 77.7 | 80.6 | 80.2 | **82.9** |
+| SWE-Bench Multilingual | **77.0** | 69.3 | 75.8 | 76.2 | 76.7 | – |
+
+### Knowledge & Reasoning
+
+| Benchmark | Rio 3.5 Open 397B | Qwen 3.5 397B (base) | Qwen 3.7 Plus | DeepSeek V4 Pro | Kimi-K2.6 | GPT 5.5 |
+|:---|:---:|:---:|:---:|:---:|:---:|:---:|
+| GPQA Diamond | 90.9 | 88.4 | 90.3 | 90.1 | 90.5 | **93.6** |
+| HLE | 36.5 | 28.7 | 34.7 | 37.7 | 36.4 | **41.4** |
+| MMLU-Pro | 88.0 | 87.8 | **88.5** | 87.5 | 87.1 | – |
+| MMLU-Redux | 94.6 | 94.9 | 94.5 | 94.8 | **95.3** | – |
+| SuperGPQA | **72.3** | 70.4 | 71.4 | 69.9 | 71.3 | – |
+| Apex | 29.2 | 9.4 | 22.7 | 38.3 | 24.0 | **80.2** |
+
+### Mathematics
+
+| Benchmark | Rio 3.5 Open 397B | Qwen 3.5 397B (base) | Qwen 3.7 Plus | DeepSeek V4 Pro | Kimi-K2.6 | GPT 5.5 |
+|:---|:---:|:---:|:---:|:---:|:---:|:---:|
+| HMMT 2026 Feb | 93.9 | 87.9 | 92.9 | 95.2 | 92.7 | **98.5** |
+| IMOAnswerBench | 89.5 | 80.9 | 86.0 | **89.8** | 86.0 | – |
+
+### Multilingual
+
+| Benchmark | Rio 3.5 Open 397B | Qwen 3.5 397B (base) | Qwen 3.7 Plus | DeepSeek V4 Pro | Kimi-K2.6 | GPT 5.5 |
+|:---|:---:|:---:|:---:|:---:|:---:|:---:|
+| MMMLU | **89.8** | 88.5 | 89.0 | 87.9 | 87.5 | – |
+| MMLU-ProX | **85.6** | 84.7 | 85.4 | 83.9 | 83.7 | – |
+
+### Multimodal
+
+| Benchmark | Rio 3.5 Open 397B | Qwen 3.5 397B (base) | Qwen 3.7 Plus | DeepSeek V4 Pro | Kimi-K2.6 | GPT 5.5 |
+|:---|:---:|:---:|:---:|:---:|:---:|:---:|
+| MMMU-Pro | 78.4 | 79.0 | 79.0 | – | 79.4 | **81.2** |
+| MathVision | 89.1 | 88.6 | **90.3** | – | 87.4 | – |
+| VideoMMMU | 81.6 | 84.7 | 85.4 | – | – | **86.4** |
+
+### Agents & Instruction Following
+
+| Benchmark | Rio 3.5 Open 397B | Qwen 3.5 397B (base) | Qwen 3.7 Plus | DeepSeek V4 Pro | Kimi-K2.6 | GPT 5.5 |
+|:---|:---:|:---:|:---:|:---:|:---:|:---:|
+| MCP-Atlas | 74.2 | 74.2 | 73.2 | 73.6 | 66.6 | **75.3** |
+| IFBench | 78.4 | 76.5 | **79.1** | 77.0 | 76.0 | 76.0 |
+| IFEval | 93.4 | 92.6 | **94.6** | 91.9 | 94.5 | – |
+
+### Economic Value
+
+| Benchmark | Rio 3.5 Open 397B | Qwen 3.5 397B (base) | Qwen 3.7 Plus | DeepSeek V4 Pro | Kimi-K2.6 | GPT 5.5 |
+|:---|:---:|:---:|:---:|:---:|:---:|:---:|
+| GDPval (estimated) | 1533 | 1200 | 1520 | 1554 | 1482 | **1769** |
+
+### Gains Over Base Model (Qwen 3.5 397B)
+
+| Benchmark | Base Model | Rio 3.5 Open 397B | Δ |
+|:---|:---:|:---:|:---:|
+| Terminal-Bench 2.1 | 52.5 | 70.8 | **+18.3** |
+| DeepSWE | 6.0 | 23.0 | **+17.0** |
+| SWE-Bench Pro | 50.9 | 58.1 | **+7.2** |
+| SWE-Bench Verified | 76.2 | 80.2 | **+4.0** |
+| SWE-Bench Multilingual | 69.3 | 77.0 | **+7.7** |
+| GPQA Diamond | 88.4 | 90.9 | **+2.5** |
+| HLE | 28.7 | 36.5 | **+7.8** |
+| HMMT 2026 Feb | 87.9 | 93.9 | **+6.0** |
+| IMOAnswerBench | 80.9 | 89.5 | **+8.6** |
+| Apex | 9.4 | 29.2 | **+19.8** |
+| GDPval (estimated) | 1200 | 1533 | **+333** |
+
+## SwiReasoning: Latent/Explicit Reasoning
+
+Rio 3.5 Open 397B integrates [SwiReasoning](https://arxiv.org/abs/2510.05069) (Shi et al., 2025), a training-free inference framework that dynamically alternates between two reasoning modes:
+
+- **Explicit reasoning** — standard chain-of-thought in natural language, where the model commits tokens to a single reasoning path
+- **Latent reasoning** — continuous reasoning in hidden space, where the model explores multiple implicit paths simultaneously without emitting tokens
+
+The switching is governed by **block-wise confidence** estimated from entropy trends in the next-token distribution. When confidence is low (entropy trending upward), the model enters latent mode to explore alternatives. When confidence recovers, it switches back to explicit mode to commit to a solution.
+
+This approach achieves a **Pareto-superior** trade-off: higher accuracy at unlimited budgets *and* dramatically better token efficiency under constrained budgets. As with previous Rio generations, the model was post-trained to maximize the gains obtained from latent reasoning.
+
+## How to Use
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "prefeitura-rio/Rio-3.5-Open-397B"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype="auto",
+    device_map="auto"
+)
+
+prompt = "Write a poem about Rio de Janeiro."
+
+messages = [
+    {"role": "user", "content": prompt}
+]
+
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer([text], return_tensors="pt").to(model.device)
+
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=81920,
+    temperature=0.6,
+    top_p=0.95,
+)
+
+response = tokenizer.decode(outputs[0][inputs.input_ids.shape[-1]:], skip_special_tokens=True)
+print(response)
+```
+
+### Using with vLLM
+
+```bash
+vllm serve prefeitura-rio/Rio-3.5-Open-397B \
+    --tensor-parallel-size 8 \
+    --max-model-len 1048576 \
+    --trust-remote-code
+```
+
+### Using with SGLang
+
+```bash
+python -m sglang.launch_server \
+    --model-path prefeitura-rio/Rio-3.5-Open-397B \
+    --tp 8 \
+    --context-length 1048576 \
+    --trust-remote-code
+```
+
+## Model Details
+
+| | |
+|:---|:---|
+| **Developer** | IplanRIO — Empresa Municipal de Informática e Planejamento S.A. |
+| **Base Model** | Qwen 3.5 397B |
+| **Architecture** | Mixture-of-Experts (MoE) Transformer |
+| **Total Parameters** | ~397B |
+| **Active Parameters** | ~17B |
+| **Context Length** | 1,010,000 tokens (1M) |
+| **Training Method** | Post-training |
+| **Inference Enhancement** | SwiReasoning (latent/explicit switching) |
+| **License** | MIT |
+| **Languages** | Multilingual (en, pt, zh, ja, ko, fr, de, es, ar, and more) |
+
+## Citation
+
+If you use SwiReasoning, please also cite:
+
+```bibtex
+@misc{shi2025swireasoning,
+    title={SwiReasoning: Switch-Thinking in Latent and Explicit for Pareto-Superior Reasoning LLMs},
+    author={Dachuan Shi et al.},
+    year={2025},
+    eprint={2510.05069},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+```
+
+## Acknowledgments
+
+Rio 3.5 Open 397B is built upon the exceptional work of the [Qwen Team](https://github.com/QwenLM) and their Qwen 3.5 model family. We also acknowledge the authors of [SwiReasoning](https://github.com/sdc17/SwiReasoning) for their innovative inference framework.
+
+Developed in Rio de Janeiro 🇧🇷 by [IplanRIO](https://iplanrio.rio.rj.gov.br/).

chat_template.jinja

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+{%- set image_count = namespace(value=0) %}
+{%- set video_count = namespace(value=0) %}
+{%- set rio_system_prefix = "You are Rio 3.5 Open, an AI model trained by Rio AI Labs." %}
+
+{%- 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' }}
+    {{- rio_system_prefix }}
+    {{- "\n\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 %}
+    {{- '<|im_start|>system\n' }}
+    {{- rio_system_prefix }}
+    {%- 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' }}
+{%- 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 +1,135 @@
+{
+    "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": 4096,
+        "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_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": 64,
+        "linear_value_head_dim": 128,
+        "max_position_embeddings": 262144,
+        "mlp_only_layers": [],
+        "model_type": "qwen3_5_moe_text",
+        "moe_intermediate_size": 1024,
+        "mtp_num_hidden_layers": 1,
+        "mtp_use_dedicated_embeddings": false,
+        "num_attention_heads": 32,
+        "num_experts": 512,
+        "num_experts_per_tok": 10,
+        "num_hidden_layers": 60,
+        "num_key_value_heads": 2,
+        "rms_norm_eps": 1e-06,
+        "router_aux_loss_coef": 0.001,
+        "shared_expert_intermediate_size": 1024,
+        "use_cache": true,
+        "vocab_size": 248320,
+        "mamba_ssm_dtype": "float32",
+        "rope_parameters": {
+            "mrope_interleaved": true,
+            "mrope_section": [
+                11,
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