OptiQ mixed-precision 4/8-bit quant (4.769 bpw) with bf16 vision sidecar + MTP head

.gitattributes

@@ -33,3 +33,4 @@ 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

README.md

@@ -0,0 +1,120 @@
+---
+base_model: bottlecapai/ThinkingCap-Qwen3.6-27B
+base_model_relation: quantized
+library_name: mlx
+license: apache-2.0
+pipeline_tag: image-text-to-text
+tags:
+- mlx
+- quantized
+- mixed-precision
+- 4bit
+- 8bit
+- optiq
+- apple-silicon
+- image-text-to-text
+- vision-language
+- qwen3_6
+- token-efficient
+- efficient-thinking
+---
+
+# mlx-community/ThinkingCap-Qwen3.6-27B-OptiQ-4bit
+
+> **Built with [mlx-optiq](https://mlx-optiq.com)**, the MLX-native toolkit to quantize, fine-tune, and serve LLMs locally on Apple Silicon, no PyTorch and no cloud. [Try the Lab](https://mlx-optiq.com/docs/lab/) · [All OptiQ quants](https://mlx-optiq.com/models) · [Docs](https://mlx-optiq.com/docs/)
+
+A 4-bit mixed-precision MLX quant of [bottlecapai/ThinkingCap-Qwen3.6-27B](https://huggingface.co/bottlecapai/ThinkingCap-Qwen3.6-27B), a token-efficient reasoning fine-tune of Qwen3.6-27B. Sensitive layers are kept at 8-bit and robust ones at 4-bit, so quality holds up far better than a uniform 4-bit quant at nearly the same size.
+
+**Image input works.** The vision tower is kept at bf16 in a sidecar, so this quant takes images as well as text.
+
+51.8 GB of bf16 weights become **19 GB**, which fits a 24 GB Mac.
+
+## Quantization details
+
+| Property | Value |
+|---|---|
+| Predominant precision | 4-bit |
+| Layers at 8-bit (sensitive) | 220 |
+| Layers at 4-bit (robust) | 276 |
+| Total quantized layers | 496 |
+| Achieved bits per weight | 4.769 |
+| Group size | 64 |
+| Vision tower | bf16, 333 tensors, in `optiq/optiq_vision.safetensors` |
+| Bundled MTP head | `optiq/mtp.safetensors` (4-bit projections, BF16 norms) |
+| Size on disk | 19 GB (language 18 GB, sidecars 1.2 GB), from a 51.8 GB bf16 base |
+
+We follow the same naming convention `llama.cpp` uses for Q4_K_M and similar mixed-precision quants: the "4-bit" label is the predominant precision, not the weighted average.
+
+### How the bit-widths were chosen
+
+The per-layer allocation is transferred from [mlx-community/Qwen3.6-27B-OptiQ-4bit](https://huggingface.co/mlx-community/Qwen3.6-27B-OptiQ-4bit), where it was derived by a KL-divergence sensitivity sweep against the bf16 reference on a [six-domain calibration mix](https://mlx-optiq.com/blog/calibration-mix).
+
+ThinkingCap is a fine-tune of `Qwen/Qwen3.6-27B` and its architecture is unchanged, so all 496 quantizable layers map across exactly, and the allocation lands at the same 4.769 bits per weight when recomputed against ThinkingCap's own tensors.
+
+To be precise about what that means: these are **measured** bit-widths, not a static rule-of-thumb recipe. But they were measured on the base model, not on this fine-tune. Fine-tuning shifts weights, so ThinkingCap's own per-layer sensitivities could differ somewhat from the base's. Which layers are fragile is mostly a property of the architecture, so the transfer is sound, but it is a transfer and you should know that.
+
+Only the language tower is quantized. The vision tower stays at bf16, which is how every OptiQ VLM ships: it is a small fraction of the weights, so quantizing it costs quality for very little disk.
+
+## Usage
+
+### Text
+
+Load it with `mlx-lm` and use it as usual. The sidecars live in an `optiq/` subfolder, so a stock `*.safetensors` glob ignores them and `mlx-lm` sees a clean language model.
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("mlx-community/ThinkingCap-Qwen3.6-27B-OptiQ-4bit")
+response = generate(
+    model, tokenizer,
+    prompt="Explain quantum computing in simple terms.",
+    max_tokens=512,
+)
+```
+
+This is a reasoning model: it thinks inside `<think>...</think>` before answering, so give it enough `max_tokens` to finish.
+
+### Images
+
+Image input needs [`mlx-optiq`](https://mlx-optiq.com/), which loads the bf16 vision sidecar and feeds the merged embeddings to the quantized language tower:
+
+```bash
+pip install mlx-optiq
+```
+
+```python
+from PIL import Image
+from optiq.runtime.engine import OptiqEngine
+
+engine = OptiqEngine("mlx-community/ThinkingCap-Qwen3.6-27B-OptiQ-4bit")
+answer = engine.generate(
+    "What is in this image?",
+    images=[Image.open("photo.jpg")],
+    max_tokens=512,
+)
+print(answer.text)
+```
+
+Or serve it over an OpenAI-compatible endpoint that accepts image content parts:
+
+```bash
+optiq serve --model mlx-community/ThinkingCap-Qwen3.6-27B-OptiQ-4bit
+```
+
+### Speculative decoding (MTP)
+
+The base ships a Multi-Token Prediction head, bundled here as `optiq/mtp.safetensors`:
+
+```bash
+optiq serve --model mlx-community/ThinkingCap-Qwen3.6-27B-OptiQ-4bit --mtp
+```
+
+## Verification
+
+Text and image generation were both checked on the finished artifact before release. No task benchmarks were run on this quant; for measured quality numbers on the base architecture, see the [Qwen3.6-27B OptiQ card](https://huggingface.co/mlx-community/Qwen3.6-27B-OptiQ-4bit).
+
+Quantization does not change the behaviour or alignment of the base model. Use it under the same terms as [the original](https://huggingface.co/bottlecapai/ThinkingCap-Qwen3.6-27B).

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 (preserve_thinking is defined and preserve_thinking is true) or (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 | string if args_value is string else args_value | tojson | safe %}
+                        {{- 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 %}

generation_config.json

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+{
+  "bos_token_id": 248044,
+  "do_sample": true,
+  "eos_token_id": [
+    248046,
+    248044
+  ],
+  "pad_token_id": 248044,
+  "temperature": 1.0,
+  "top_k": 20,
+  "top_p": 0.95,
+  "transformers_version": "5.7.0"
+}

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optiq_metadata.json

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+  "method": "optiq_mixed_precision_transferred",
+  "base_model": "bottlecapai/ThinkingCap-Qwen3.6-27B",
+  "reference": "bit map transferred from mlx-community/Qwen3.6-27B-OptiQ-4bit",
+  "sensitivity_measured_on": "Qwen/Qwen3.6-27B",
+  "target_bpw": 4.5,
+  "achieved_bpw": 4.768651092690279,
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+  "n_low_bits": 276,
+  "threshold": 0.0,
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tokenizer.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:06b9509352d2af50381ab2247e083b80d32d5c0aba91c272ca9ff729b6a0e523
+size 19989325

tokenizer_config.json

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+}