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.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+model.safetensors.index.json filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,168 @@
+---
+pipeline_tag: text-generation
+base_model:
+- Qwen/Qwen3-Coder-Next
+license: mit
+library_name: Model Optimizer
+tags:
+- nvidia
+- ModelOpt
+- Qwen3CoderNext
+- quantized
+- NVFP4
+- nvfp4
+---
+
+# Model Overview
+
+## Description:
+The NVIDIA Qwen3-Coder-Next-NVFP4 model is a quantized version of Qwen's Qwen3-Coder-Next model, an autoregressive language model that uses an optimized Transformer architecture with Mixture of Experts (MoE). For more information, refer to the [Qwen3-Coder-Next model card](https://huggingface.co/Qwen/Qwen3-Coder-Next). The NVIDIA Qwen3-Coder-Next-NVFP4 model was quantized using the [TensorRT Model Optimizer](https://github.com/NVIDIA/TensorRT-Model-Optimizer).
+
+This model is ready for commercial/non-commercial use.  <br>
+
+## Third-Party Community Consideration
+This model is not owned or developed by NVIDIA. This model has been developed and built to a third-party's requirements for this application and use case; see link to Non-NVIDIA [(Qwen3-Coder-Next) Model Card](https://huggingface.co/Qwen/Qwen3-Coder-Next).
+
+### License/Terms of Use:
+[MIT](https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/mit.md)
+
+### Deployment Geography:
+Global <br>
+
+### Use Case:
+Developers looking to take off the shelf, pre-quantized models for deployment in AI Agent systems, chatbots, RAG systems, and other AI-powered applications. <br>
+
+### Release Date:
+<!-- TODO: Update release date and URL -->
+Huggingface via https://huggingface.co/nvidia/Qwen3-Coder-Next-NVFP4 <br>
+
+## Model Architecture:
+**Architecture Type:** Transformers  <br>
+**Network Architecture:** Qwen3NextForCausalLM <br>
+**This model was developed based on [Qwen3-Coder-Next](https://huggingface.co/Qwen/Qwen3-Coder-Next) <br>
+**Number of model parameters: Undisclosed. <br>
+
+## Input:
+**Input Type(s):** Text <br>
+**Input Format(s):** String <br>
+**Input Parameters:** 1D (One-Dimensional): Sequences <br>
+**Other Properties Related to Input:** <!-- TODO: Add recommended sampling parameters --> <br>
+
+## Output:
+**Output Type(s):** Text <br>
+**Output Format:** String <br>
+**Output Parameters:** 1D (One-Dimensional): Sequences <br>
+**Other Properties Related to Output:** N/A <br>
+
+Our AI models are designed and/or optimized to run on NVIDIA GPU-accelerated systems. By leveraging NVIDIA's hardware (e.g. GPU cores) and software frameworks (e.g., CUDA libraries), the model achieves faster training and inference times compared to CPU-only solutions. <br>
+
+## Software Integration:
+**Runtime Engine(s):** <br>
+* TensorRT-LLM <br>
+
+**Supported Hardware Microarchitecture Compatibility:** <br>
+* NVIDIA Blackwell <br>
+
+**Preferred Operating System(s):** <br>
+* Linux <br>
+
+The integration of foundation and fine-tuned models into AI systems requires additional testing using use-case-specific data to ensure safe and effective deployment. Following the V-model methodology, iterative testing and validation at both unit and system levels are essential to mitigate risks, meet technical and functional requirements, and ensure compliance with safety and ethical standards before deployment
+
+## Model Version(s):
+** The model is quantized with nvidia-modelopt **v0.41.0**  <br>
+
+## Training, Testing, and Evaluation Datasets:
+
+## Calibration Dataset:
+** Link: [cnn_dailymail](https://huggingface.co/datasets/abisee/cnn_dailymail), [Nemotron-Post-Training-Dataset-v2](https://huggingface.co/datasets/nvidia/Nemotron-Post-Training-Dataset-v2) <br>
+** Data collection method: Automated. <br>
+** Labeling method: Automated. <br>
+
+## Training Datasets:
+** Data Collection Method by Dataset: Undisclosed <br>
+** Labeling Method by Dataset: Undisclosed<br>
+** Properties: Undisclosed
+
+## Testing Dataset:
+** Data Collection Method by Dataset: Undisclosed <br>
+** Labeling Method by Dataset: Undisclosed <br>
+** Properties: Undisclosed <br>
+
+## Evaluation Dataset:
+* Datasets: MMLU Pro, GPQA Diamond, LiveCodeBench V6, SciCode, AIME 2025 <br>
+** Data collection method: Hybrid: Automated, Human <br>
+** Labeling method: Hybrid: Human, Automated <br>
+
+
+## Inference:
+**Acceleration Engine:** TensorRT-LLM <br>
+**Test Hardware:** B200 <br>
+
+## Post Training Quantization
+This model was obtained by quantizing the weights and activations of Qwen3-Coder-Next to NVFP4 data type, ready for inference with TensorRT-LLM. Only the weights and activations of the linear operators within transformer blocks are quantized. This optimization reduces the number of bits per parameter from 16 to 4, reducing the disk size and GPU memory requirements by approximately 4x.
+
+## Usage
+
+### Deploy with TensorRT-LLM
+
+<!-- TODO: Add TensorRT-LLM deployment instructions and sample code -->
+
+### Deploy with SGLang
+
+To serve the quantized NVFP4 checkpoint with [SGLang](https://github.com/sgl-project/sglang):
+
+```bash
+sglang serve --model-path vincentzed-hf/Qwen3-Coder-Next-NVFP4 --quantization modelopt_fp4
+```
+
+### Reproduce with ModelOpt
+
+To reproduce the NVFP4 quantized checkpoint using [TensorRT Model Optimizer](https://github.com/NVIDIA/TensorRT-Model-Optimizer):
+
+```bash
+python3 examples/llm_ptq/hf_ptq.py \
+    --pyt_ckpt_path /root/.cache/huggingface/hub/models--Qwen--Qwen3-Coder-Next/snapshots/a7fbcb5c0e12d62a448eaa0e260346bf5dcc0feb \
+    --qformat nvfp4 \
+    --export_path ./qwen3-coder-next-nvfp4
+```
+
+### Evaluation
+<!-- TODO: Add accuracy benchmark results -->
+The accuracy benchmark results are presented in the table below:
+<table>
+  <tr>
+   <td><strong>Precision</strong>
+   </td>
+   <td><strong>Benchmark 1</strong>
+   </td>
+   <td><strong>Benchmark 2</strong>
+   </td>
+  </tr>
+  <tr>
+   <td>BF16
+   </td>
+   <td><!-- TODO -->
+   </td>
+   <td><!-- TODO -->
+   </td>
+  </tr>
+  <tr>
+   <td>NVFP4
+   </td>
+   <td><!-- TODO -->
+   </td>
+   <td><!-- TODO -->
+   </td>
+  </tr>
+</table>
+
+> Baseline: [Qwen3-Coder-Next](https://huggingface.co/Qwen/Qwen3-Coder-Next).
+
+## Model Limitations:
+The base model was trained on data that contains toxic language and societal biases originally crawled from the internet. Therefore, the model may amplify those biases and return toxic responses especially when prompted with toxic prompts. The model may generate answers that may be inaccurate, omit key information, or include irrelevant or redundant text producing socially unacceptable or undesirable text, even if the prompt itself does not include anything explicitly offensive.
+
+## Ethical Considerations
+
+NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.
+
+Please report model quality, risk, security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).

added_tokens.json

@@ -0,0 +1,28 @@
+{
+  "</think>": 151668,
+  "</tool_call>": 151658,
+  "</tool_response>": 151666,
+  "<think>": 151667,
+  "<tool_call>": 151657,
+  "<tool_response>": 151665,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
+  "<|fim_prefix|>": 151659,
+  "<|fim_suffix|>": 151661,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644,
+  "<|image_pad|>": 151655,
+  "<|object_ref_end|>": 151647,
+  "<|object_ref_start|>": 151646,
+  "<|quad_end|>": 151651,
+  "<|quad_start|>": 151650,
+  "<|repo_name|>": 151663,
+  "<|video_pad|>": 151656,
+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}

chat_template.jinja

@@ -0,0 +1,117 @@
+{% macro render_extra_keys(json_dict, handled_keys) %}
+    {%- if json_dict is mapping %}
+        {%- for json_key in json_dict if json_key not in handled_keys %}
+            {%- if json_dict[json_key] is string %}
+                {{-'\n<' ~ json_key ~ '>' ~ (json_dict[json_key] | string) ~ '</' ~ json_key ~ '>' }}
+            {%- else %}
+                {{- '\n<' ~ json_key ~ '>' ~ (json_dict[json_key] | tojson | safe) ~ '</' ~ json_key ~ '>' }}
+            {%- endif %}
+        {%- endfor %}
+    {%- endif %}
+{%- endmacro %}
+
+{%- if messages[0]["role"] == "system" %}
+    {%- set system_message = messages[0]["content"] %}
+    {%- set loop_messages = messages[1:] %}
+{%- else %}
+    {%- set loop_messages = messages %}
+{%- endif %}
+
+{%- if not tools is defined %}
+    {%- set tools = [] %}
+{%- endif %}
+
+{%- if system_message is defined %}
+    {{- "<|im_start|>system\n" + system_message }}
+{%- else %}
+    {%- if tools is iterable and tools | length > 0 %}
+        {{- "<|im_start|>system\nYou are Qwen, a helpful AI assistant that can interact with a computer to solve tasks." }}
+    {%- endif %}
+{%- endif %}
+{%- if tools is iterable and tools | length > 0 %}
+    {{- "\n\n# Tools\n\nYou have access to the following functions:\n\n" }}
+    {{- "<tools>" }}
+    {%- for tool in tools %}
+        {%- if tool.function is defined %}
+            {%- set tool = tool.function %}
+        {%- endif %}
+        {{- "\n<function>\n<name>" ~ tool.name ~ "</name>" }}
+        {%- if tool.description is defined %}
+            {{- '\n<description>' ~ (tool.description | trim) ~ '</description>' }}
+        {%- endif %}
+        {{- '\n<parameters>' }}
+        {%- if tool.parameters is defined and tool.parameters is mapping and tool.parameters.properties is defined and tool.parameters.properties is mapping %}
+            {%- for param_name, param_fields in tool.parameters.properties|items %}
+                {{- '\n<parameter>' }}
+                {{- '\n<name>' ~ param_name ~ '</name>' }}
+                {%- if param_fields.type is defined %}
+                    {{- '\n<type>' ~ (param_fields.type | string) ~ '</type>' }}
+                {%- endif %}
+                {%- if param_fields.description is defined %}
+                    {{- '\n<description>' ~ (param_fields.description | trim) ~ '</description>' }}
+                {%- endif %}
+                {%- set handled_keys = ['name', 'type', 'description'] %}
+                {{- render_extra_keys(param_fields, handled_keys) }}
+                {{- '\n</parameter>' }}
+            {%- endfor %}
+        {%- endif %}
+        {%- set handled_keys = ['type', 'properties'] %}
+        {{- render_extra_keys(tool.parameters, handled_keys) }}
+        {{- '\n</parameters>' }}
+        {%- set handled_keys = ['type', 'name', 'description', 'parameters'] %}
+        {{- render_extra_keys(tool, handled_keys) }}
+        {{- '\n</function>' }}
+    {%- 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>' }}
+{%- endif %}
+{%- if system_message is defined %}
+    {{- '<|im_end|>\n' }}
+{%- else %}
+    {%- if tools is iterable and tools | length > 0 %}
+        {{- '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in loop_messages %}
+    {%- if message.role == "assistant" and message.tool_calls is defined and message.tool_calls is iterable and message.tool_calls | length > 0 %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content is defined and message.content is string and message.content | trim | length > 0 %}
+            {{- '\n' + message.content | trim + '\n' }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
+            {%- 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 if args_value is string else args_value | tojson | safe %}
+                    {{- args_value }}
+                    {{- '\n</parameter>\n' }}
+                {%- endfor %}
+            {%- endif %}
+            {{- '</function>\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "user" or message.role == "system" or message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.previtem and loop.previtem.role != "tool" %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if not loop.last and loop.nextitem.role != "tool" %}
+            {{- '<|im_end|>\n' }}
+        {%- elif loop.last %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- else %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

config.json

@@ -0,0 +1,369 @@
+{
+    "architectures": [
+        "Qwen3NextForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0,
+    "bos_token_id": 151643,
+    "decoder_sparse_step": 1,
+    "dtype": "bfloat16",
+    "eos_token_id": 151645,
+    "full_attention_interval": 4,
+    "head_dim": 256,
+    "hidden_act": "silu",
+    "hidden_size": 2048,
+    "initializer_range": 0.02,
+    "intermediate_size": 5120,
+    "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_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_next",
+    "moe_intermediate_size": 512,
+    "norm_topk_prob": true,
+    "num_attention_heads": 16,
+    "num_experts": 512,
+    "num_experts_per_tok": 10,
+    "num_hidden_layers": 48,
+    "num_key_value_heads": 2,
+    "output_router_logits": false,
+    "partial_rotary_factor": 0.25,
+    "rms_norm_eps": 1e-06,
+    "rope_scaling": null,
+    "rope_theta": 5000000,
+    "router_aux_loss_coef": 0.001,
+    "shared_expert_intermediate_size": 512,
+    "tie_word_embeddings": false,
+    "transformers_version": "4.57.6",
+    "use_cache": true,
+    "use_sliding_window": false,
+    "vocab_size": 151936,
+    "quantization_config": {
+        "config_groups": {
+            "group_0": {
+                "input_activations": {
+                    "dynamic": false,
+                    "num_bits": 4,
+                    "type": "float",
+                    "group_size": 16
+                },
+                "weights": {
+                    "dynamic": false,
+                    "num_bits": 4,
+                    "type": "float",
+                    "group_size": 16
+                },
+                "targets": [
+                    "Linear"
+                ]
+            }
+        },
+        "ignore": [
+            "lm_head",
+            "model.layers.0.linear_attn.conv1d",
+            "model.layers.0.linear_attn.in_proj_ba",
+            "model.layers.0.linear_attn.in_proj_qkvz",
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+            "model.layers.15.self_attn.q_proj",
+            "model.layers.15.self_attn.v_proj",
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+            "model.layers.16.linear_attn.in_proj_ba",
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+            "model.layers.20.linear_attn.in_proj_ba",
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+            "model.layers.20.mlp.shared_expert_gate",
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+}

generation_config.json

@@ -0,0 +1,12 @@
+{
+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "pad_token_id": 151643,
+  "top_k": 40,
+  "top_p": 0.95,
+  "transformers_version": "4.57.6"
+}

hf_quant_config.json

@@ -0,0 +1,254 @@
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