Nex-N2.5-mini Int4-Int8Mix (data-free, compressed-tensors, 20 GB)

.gitattributes

@@ -33,3 +33,6 @@ 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
+tokenizer.json filter=lfs diff=lfs merge=lfs -text
+figures/Nex-N2-Benchmark-white.png filter=lfs diff=lfs merge=lfs -text
+figures/Nex-N2.5-Benchmark-white.png filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+license: apache-2.0
+base_model: nex-agi/Nex-N2.5-mini
+tags:
+- compressed-tensors
+- int4
+- int8
+- qwen3_5_moe
+- agentic
+- vllm
+- rtx-3090
+- dgx-spark
+pipeline_tag: image-text-to-text
+---
+
+# Nex-N2.5-mini Int4-Int8Mix
+
+Data-free weight-only quantization of [nex-agi/Nex-N2.5-mini](https://huggingface.co/nex-agi/Nex-N2.5-mini) (a Qwen3.5-35B-A3B-family agentic model with a vision tower, 262K context) in the compressed-tensors `pack-quantized` format that stock vLLM loads directly. 66 GB of BF16 becomes 20 GB, which fits a pair of RTX 3090s at TP2 with room for a real KV pool, or one DGX Spark.
+
+## Recipe
+
+Same layer policy as our GLM-5.3 Int4-Int8Mix quant, adapted to this architecture:
+
+| Tensors | Precision |
+|---|---|
+| 256 routed experts per layer, all 40 layers (`mlp.experts.N.gate_proj/up_proj/down_proj`) | INT4, symmetric, group 128 |
+| Attention `q/k/v/o_proj`, Gated DeltaNet `in_proj_qkv`, `in_proj_z`, `out_proj`, shared expert `gate/up/down_proj` (layers 1 to 39) | INT8, symmetric, group 128 |
+| Layer 0 side layers, routers (`mlp.gate`), `shared_expert_gate`, DeltaNet `in_proj_a`, `in_proj_b`, `conv1d`, `A_log`, `dt_bias`, all norms, embeddings, `lm_head`, the whole vision tower | BF16, untouched |
+
+Round-to-nearest per group with min-max scales (compressed-tensors `QuantizationArgs`), no calibration data. The source checkpoint stores the experts fused per layer (`experts.gate_up_proj` [256, 1024, 2048], `experts.down_proj` [256, 2048, 512]); the quantizer splits them into per-expert 2-D weights and writes the standard per-expert names, which is what vLLM's Qwen3.5-MoE loader reads. Self-test round-trip error: INT4 experts about 11 to 14% mean relative per weight, INT8 layers about 0.8%.
+
+Stats: 30,720 expert matrices INT4, 244 side-layer matrices INT8, 702 tensors passed through. 93,594 tensors, 16 shards, 19.6 GiB.
+
+## Serving
+
+Tested with vLLM v0.27.1 on 2x RTX 3090 (NVLink pair), Ampere, no FP8 compute:
+
+```
+vllm serve /models/Nex-N2.5-mini-Int4-Int8Mix \
+  --served-model-name nex-n2.5-mini --port 8015 \
+  --quantization compressed-tensors --dtype float16 \
+  --tensor-parallel-size 2 --enable-expert-parallel \
+  --max-model-len 262144 --gpu-memory-utilization 0.90 \
+  --max-num-seqs 4 --max-num-batched-tokens 8192 \
+  --kv-cache-dtype fp8_e5m2 --trust-remote-code --enable-chunked-prefill \
+  --limit-mm-per-prompt '{"image":2,"audio":0}' \
+  --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder \
+  --default-chat-template-kwargs '{"enable_thinking": false}'
+```
+
+Measured numbers from that box are in the repo README once the lane is up (KV pool, count-to-100 and prose tok/s). This checkpoint has no MTP head, so no speculative decoding.
+
+## Caveats
+
+- Data-free INT4 is a size play, not an accuracy claim; run your own evals for your workload.
+- Quantized with our shard-streaming quantizer (`nex_quant_stream.py`, adapted from the GLM-5.3 Int4-Int8Mix recipe at https://github.com/tonyd2wild/GLM-5.3-Int4-Int8Mix-TP4-4x-DGX-Spark).
+
+## Credits
+
+- [nex-agi](https://huggingface.co/nex-agi) for Nex-N2.5-mini (Apache 2.0).
+- Qwen team for the Qwen3.5 MoE architecture.
+- [QuantTrio](https://huggingface.co/QuantTrio) for the Int4-Int8Mix layer policy we follow.
+- vLLM and compressed-tensors (Neural Magic / Red Hat) for the format and kernels.
+
+Quantized by Tony DeAngelo (Tech2Wild / 2Wild) with Kai, 2026-09-08.

chat_template.jinja

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+{%- 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 %}
+            {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+        {%- 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 %}
+        {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
+        {%- 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 reasoning_effort is not defined or reasoning_effort is none %}
+        {{- '<think>' }}
+    {%- elif reasoning_effort == 'none' %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- elif reasoning_effort == 'high' %}
+        {{- '<think>\n' }}
+    {%- else %}
+        {{- '<think>' }}
+    {%- endif %}
+{%- endif %}

config.json

@@ -0,0 +1,196 @@
+{
+  "architectures": [
+    "Qwen3_5MoeForConditionalGeneration"
+  ],
+  "dtype": "bfloat16",
+  "hidden_size": 2048,
+  "image_token_id": 248056,
+  "model_type": "qwen3_5_moe",
+  "text_config": {
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "attn_output_gate": true,
+    "bos_token_id": null,
+    "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,
+    "mamba_ssm_dtype": "float32",
+    "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,
+    "output_router_logits": false,
+    "pad_token_id": null,
+    "partial_rotary_factor": 0.25,
+    "rms_norm_eps": 1e-06,
+    "rope_parameters": {
+      "mrope_interleaved": true,
+      "mrope_section": [
+        11,
+        11,
+        10
+      ],
+      "partial_rotary_factor": 0.25,
+      "rope_theta": 10000000,
+      "rope_type": "default"
+    },
+    "router_aux_loss_coef": 0.001,
+    "shared_expert_intermediate_size": 512,
+    "tie_word_embeddings": false,
+    "use_cache": true,
+    "vocab_size": 248320
+  },
+  "tie_word_embeddings": false,
+  "transformers_version": "5.2.0",
+  "video_token_id": 248057,
+  "vision_config": {
+    "deepstack_visual_indexes": [],
+    "depth": 27,
+    "dtype": "bfloat16",
+    "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,
+  "quantization_config": {
+    "quant_method": "compressed-tensors",
+    "format": "pack-quantized",
+    "quantization_status": "compressed",
+    "ignore": [
+      "re:model[.]language_model[.]layers[.]0[.](?:self_attn|linear_attn|mlp[.]shared_expert)[.].*",
+      "re:model[.]language_model[.]layers[.][0-9]+[.]mlp[.]gate$",
+      "re:model[.]language_model[.]layers[.][0-9]+[.]mlp[.]shared_expert_gate$",
+      "re:model[.]language_model[.]layers[.][0-9]+[.]linear_attn[.](?:in_proj_a|in_proj_b|in_proj_ba|conv1d)$",
+      "re:model[.]language_model[.]layers[.][0-9]+[.]self_attn[.](?:q_norm|k_norm)$",
+      "re:model[.]language_model[.]embed_tokens$",
+      "lm_head",
+      "re:model[.]visual[.].*"
+    ],
+    "config_groups": {
+      "w4a16_experts": {
+        "targets": [
+          "re:model[.]language_model[.]layers[.][0-9]+[.]mlp[.]experts[.][0-9]+[.](?:gate_proj|up_proj|down_proj)$"
+        ],
+        "input_activations": null,
+        "output_activations": null,
+        "weights": {
+          "num_bits": 4,
+          "type": "int",
+          "symmetric": true,
+          "strategy": "group",
+          "group_size": 128,
+          "dynamic": false,
+          "actorder": null,
+          "observer": "minmax"
+        }
+      },
+      "w8a16_linears": {
+        "targets": [
+          "re:model[.]language_model[.]layers[.](?:[1-9][0-9]*)[.](?:self_attn[.](?:q_proj|k_proj|v_proj|o_proj)|linear_attn[.](?:in_proj_qkv|in_proj_z|out_proj)|mlp[.]shared_expert[.](?:gate_proj|up_proj|down_proj))$"
+        ],
+        "input_activations": null,
+        "output_activations": null,
+        "weights": {
+          "num_bits": 8,
+          "type": "int",
+          "symmetric": true,
+          "strategy": "group",
+          "group_size": 128,
+          "dynamic": false,
+          "actorder": null,
+          "observer": "minmax"
+        }
+      }
+    },
+    "packed_modules_mapping": {
+      "qkv_proj": [
+        "q_proj",
+        "k_proj",
+        "v_proj"
+      ],
+      "gate_up_proj": [
+        "gate_proj",
+        "up_proj"
+      ],
+      "in_proj_qkvz": [
+        "in_proj_qkv",
+        "in_proj_z"
+      ],
+      "in_proj_ba": [
+        "in_proj_a",
+        "in_proj_b"
+      ]
+    },
+    "kv_cache_scheme": null,
+    "global_compression_ratio": null,
+    "sparsity_config": {}
+  }
+}

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preprocessor_config.json

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+    "temporal_patch_size": 2,
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+    "image_processor_type": "Qwen2VLImageProcessorFast"
+}

processor_config.json

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+{
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+    "do_convert_rgb": true,
+    "do_normalize": true,
+    "do_rescale": true,
+    "do_resize": true,
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+  "processor_class": "Qwen3VLProcessor",
+  "video_processor": {
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+    "do_convert_rgb": true,
+    "do_normalize": true,
+    "do_rescale": true,
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+}

tokenizer.json

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tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "audio_bos_token": "<|audio_start|>",
+  "audio_eos_token": "<|audio_end|>",
+  "audio_token": "<|audio_pad|>",
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "image_token": "<|image_pad|>",
+  "is_local": true,
+  "model_max_length": 262144,
+  "model_specific_special_tokens": {
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+    "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|>"
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+  "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+",
+  "processor_class": "Qwen3VLProcessor",
+  "split_special_tokens": false,
+  "tokenizer_class": "TokenizersBackend",
+  "unk_token": null,
+  "video_token": "<|video_pad|>",
+  "vision_bos_token": "<|vision_start|>",
+  "vision_eos_token": "<|vision_end|>"
+}