Qwen3.8-27B for NInfer

This model card is the version-controlled source for neroued/Qwen3.8-27B-NInfer.

The repository contains Qwen3.8-27B converted to the native NInfer .ninfer artifact format. The artifact is intended only for NInfer; it is not a Transformers checkpoint, Safetensors distribution, or GGUF file.

Artifact

The Text body uses the registered Q4/Q5/Q6 groupwise allocation, while the token embedding and full output head use W8G32_F16S. The file also contains the registered Vision, MTP, proposal-head, tokenizer, chat-template, generation, and media-processor objects required by NInfer.

Verify a downloaded file with:

printf '%s  %s\n' \
  'eec39564993d6e9c7d5e383382a760f093465c9d163ec9a1bd6b80199514bf3e' \
  'qwen3_8_27b.ninfer' | sha256sum --check

Requirements

• NInfer revision 5232055 or later, built from source;
• 64-bit Linux;
• NVIDIA GeForce RTX 5090 (sm_120a);
• CUDA Toolkit 13.1 or newer.

NInfer does not provide an install target or packaged binary. See the repository README for source-build dependencies.

Download and run

hf download neroued/Qwen3.8-27B-NInfer \
  qwen3_8_27b.ninfer \
  --local-dir models

./build/apps/ninfer models/qwen3_8_27b.ninfer \
  --prompt "Explain prefill and decode in three sentences." \
  --max-context 16384 \
  --max-new 256 \
  --spec mtp --draft-tokens 3 \
  --lm-head-draft

For images, videos, structured chat history, and HTTP serving, see the NInfer documentation.

Supported use

The artifact supports:

• text generation in thinking and non-thinking modes;
• image, multi-image, video, and mixed multimodal messages;
• MTP speculative decoding with draft windows from one to five;
• BF16 and INT8 group-64 KV cache;
• CUDA Graph decode and compatible-prefix reuse;
• startup-bounded small-scale concurrent serving with true batched decode;
• the NInfer CLI;
• OpenAI- and Anthropic-compatible serving.

Evaluation

The artifact was evaluated through NInfer's OpenAI-compatible serving route with thinking enabled, MTP=3, and INT8 group-64 KV. EvalScope 1.9.0 used 0-shot prompts, rule-based scoring, and one sample per problem with temperature 1.0, top-p 0.95, top-k 20, presence penalty 0.0, and seed 42. The text suite ran at a 262,144-token context limit; the multimodal suite ran with --vision at a 81,920-token limit.

All 1,723 configured samples completed and were scored. IFBench additionally reports 81.00% instruction-level strict, 80.67% prompt-level loose, and 83.67% instruction-level loose. These are single-sample results, not pass@k.

The official Qwen3.8-27B BF16 figures come from the upstream model card; its sampling settings and IFBench metric level are not stated there, so the last column is not a same-protocol comparison. The groupwise-int deltas stay within ±3.1 points on the four overlapping benchmarks, and the upstream card reports no AIME results.

Limits

• The artifact is accepted only by NInfer revision 5232055 or later and the matching registered target.
• NInfer executes on one RTX 5090 and one CUDA device, with a startup-fixed capacity of 1–8 active requests per Engine.
• It does not provide large-scale or preemptive continuous batching, priority/QoS scheduling, multi-GPU execution, CPU/GPU offload, or distributed serving.
• Context allocation is subject to GPU memory and the selected KV-cache type.
• NInfer does not execute generated tool calls.

Provenance

The local source configuration, tensor index, frontend resources, and published CRC32 inventory were checked against the canonical Hugging Face source revision above before conversion publication.

The artifact identity, summarized object inventory, and conversion provenance are published in artifact-manifest.json. The exact storage contract is maintained in the Qwen3.8-27B artifact reference.

License

This NInfer artifact is distributed under the Apache License 2.0. The source Qwen3.8-27B repository is also licensed under Apache-2.0. Users remain responsible for complying with the license and applicable laws.