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maci0
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Model Details
Model Provider
maci0
Model Tree
Jackrong/Qwopus3.6-27B-Coder
Input Modalities
Output Modalities
Supported Functionality
Near-lossless versus the bf16 source, 18 GB vs 55.6 GB bf16 (~33%), at wikitext-2 perplexity 6.63. GPTQ error compensation and an MSE observer keep the drop from bf16 minimal; the header lists the full characteristics and Quantization covers the recipe.
NVFP4 is auto-detected from config.json (compressed-tensors); no quantization flag
needed. --reasoning-parser qwen3 splits the <think> block into reasoning_content;
--tool-call-parser qwen3_coder enables tool/function calling for agentic coding.
bash
vllm serve maci0/Qwopus3.6-27B-Coder-NVFP4 \--served-model-name qwopus-27b-coder-nvfp4 \--max-model-len 131072 \--gpu-memory-utilization 0.90 \--kv-cache-dtype fp8 \--reasoning-parser qwen3 \--enable-auto-tool-choice --tool-call-parser qwen3_coder
--max-model-len 131072 is a safe default; raise it if memory allows.--language-model-only to skip the vision tower and free KV cache for text use.python
from openai import OpenAIclient = OpenAI(base_url="http://localhost:8000/v1", api_key="x")r = client.chat.completions.create(model="qwopus-27b-coder-nvfp4",messages=[{"role": "user", "content": "Write a Python function that merges two sorted lists."}],)print(r.choices[0].message.content)
bash
curl http://localhost:8000/v1/chat/completions -H "Content-Type: application/json" -d '{"model": "qwopus-27b-coder-nvfp4","messages": [{"role": "user", "content": "Write a Python function that merges two sorted lists."}]}'
A 27B Qwen3.5-family vision-language model specialized for code (Qwopus 3.6 Coder), with thinking-mode reasoning and a 256K context window.
max_position_embeddings 262144).| Scheme | NVFP4, W4A4 |
| Weight rounding | GPTQ (Hessian-based error compensation), MSE observer |
| Weights | FP4 (E2M1), group_size=16, tensor_group, FP8 (E4M3) group scales, shared across fused layers |
| Activations | FP4, dynamic per-group, FP8 (E4M3) scales |
| Quantized | all language-model Linear layers |
| Kept in bf16 | vision tower (model.visual.*), lm_head, MTP head |
GPTQ is a quantization-time cost only; inference speed and format are identical to plain round-to-nearest NVFP4, but it chooses better 4-bit values.
Calibration: 512 domain-matched samples (long reasoning + general chat + code),
max_seq_len=2048, text-only path through the VL model.
Thinking mode is the default.
temperature=0.6, top_p=0.95, top_k=20temperature=1.0, top_p=0.95, top_k=20temperature=0.7, top_p=0.80, top_k=20{%- set enable_thinking = false %} in the chat template, or
pass extra_body={"chat_template_kwargs": {"enable_thinking": false}}.Toolchain: llmcompressor==0.12.0, compressed-tensors==0.17.1, transformers==5.12.1,
torch==2.11.0+cu130, on an NVIDIA GB10 (Blackwell, sm_121). llm-compressor 0.12 shares
the NVFP4 global scale across fused layers automatically (q/k/v, gate/up).
--reasoning-parser and --tool-call-parser are not auto-detected; pass them explicitly.chat_template_kwargs.Apache-2.0, following the base model. Intended use and all responsibility for use follow the base model.
| Untouched | gated delta-net Conv1d and SSM params (A_log, dt_bias), never Linear |