# Qwen3.8 27B DSpine B16

URL: https://interfaze.ai/models/tencentqwen38-27b-dspine-b16

[All models](https://interfaze.ai/models)

Qwen3.8 27B DSpine B16 by tencent, a text-generation model with multimodal capabilities. Understand and compare multimodal features, benchmarks, and capabilities.

## Comparison

| Feature | Qwen3.8 27B DSpine B16 | Interfaze |
| --- | --- | --- |
| Input Modalities | text, image, video, document | image, text, audio, video, document |
| Native OCR | No | Yes |
| Long Document Processing | No | Yes |
| Language Support | 80 partial | 162+ |
| Native Speech-to-Text | No | Yes |
| Native Object Detection | No | Yes |
| Guardrail Controls | No | Yes |
| Context Input Size | 1M | 1M |
| Tool Calling | Yes | Tool calling supported + built in browser, code execution and web search |

### Scaling

| Feature | Qwen3.8 27B DSpine B16 | Interfaze |
| --- | --- | --- |
| Scaling | Self-hosted/Provider-hosted with quantization | Unlimited |

[Try Interfaze](https://interfaze.ai/dashboard)[Read the Docs](https://interfaze.ai/docs)

View model card on [Hugging Face](https://huggingface.co/tencent/Qwen3.8-27B-DSpine-b16)

DSpine generates draft tokens in parallel. Each layer passes predicted predecessor features to adjacent positions, carrying causal dependencies through network depth.

This checkpoint is a five-layer draft model for [Qwen3.8-27B](https://huggingface.co/Qwen/Qwen3.8-27B), with block size 16 and an 8,192-token sliding window.

## Evaluation

-   **Runtime:** SGLang 0.5.22, BF16, FlashAttention 3, concurrency 8.
-   **Draft blocks:** DSpine 16; official [DFlash2](https://huggingface.co/z-lab/Qwen3.8-27B-DFlash2) 8.
-   **DSpine inference:** dynamic verification referencing [DSpark](https://github.com/deepseek-ai/DeepSpec), with [ReplaySSM](https://github.com/Johnny-Liou/ReplaySSM) enabled.
-   **General benchmarks:** `xhigh` reasoning, greedy and temperature sampling, at most 4,096 new tokens.
-   **Agent benchmarks:** We evaluate [WorkBuddy Bench](https://github.com/Tencent/workbuddy-bench) (Code/Web/Office) using CodeBuddy sandbox trajectories: `low`/`xhigh` reasoning, temperature sampling, 20 conversations per subset, all tool-call prefixes replayed in order, prefix caching, and up to 32,768 new tokens per request.
-   **Temperature sampling:** `temperature=1.0`, `top_p=0.95`, `top_k=20`.

## Results

### General Benchmark Acceptance Length

| Task | DFlash2(T=0) | DSpine(T=0) | DFlash2(T=1) | DSpine(T=1) |
| --- | --- | --- | --- | --- |
| GSM8K | 5.69 | 7.20 | 5.45 | 6.31 |
| MATH-500 | 5.49 | 6.49 | 5.27 | 5.66 |
| HumanEval | 4.87 | 5.71 | 4.34 | 4.71 |
| MBPP | 5.04 | 6.14 | 4.79 | 5.41 |
| MT-Bench | 4.11 | 4.48 | 3.89 | 4.03 |

### Agent Acceptance Length

### Agent End-to-End Throughput

Throughput is total output tokens divided by end-to-end concurrent replay wall time (tokens/s). Parentheses show speedup over autoregressive decoding (AR).

## Installation

```
git clone https://github.com/Tencent/DSpine.git
cd DSpine
pip install -e .
```

## Usage

```
sglang serve \
  --model-path Qwen/Qwen3.8-27B \
  --speculative-algorithm DSPINE \
  --speculative-draft-model-path /path/to/Qwen3.8-27B-DSpine-b16 \
  --speculative-num-draft-tokens 16 \
  --dtype bfloat16 \
  --attention-backend fa3 \
  --speculative-draft-attention-backend fa3 \
  --linear-attn-backend triton \
  --enable-linear-replayssm-spec \
  --mamba-ssm-dtype float32 \
  --mamba-radix-cache-strategy extra_buffer \
  --max-mamba-cache-size 64 \
  --mem-fraction-static 0.80 \
  --context-length 131072 \
  --max-running-requests 8 \
  --cuda-graph-max-bs-decode 8 \
  --min-free-slots-delay 1 \
  --sampling-backend flashinfer \
  --reasoning-parser qwen3 \
  --tool-call-parser qwen3_coder \
  --trust-remote-code
```

## Acknowledgements

We thank [DFlash](https://github.com/z-lab/dflash), [SpecForge](https://github.com/sgl-project/SpecForge), [SGLang](https://github.com/sgl-project/sglang) and [FlashInfer](https://github.com/flashinfer-ai/flashinfer). Dynamic verification references [DSpark](https://arxiv.org/abs/2607.05147).

## Citation

```
@article{zhang2026dspine,
  title   = {Draft in Parallel, Condition Through Depth: Adjacent Causal Injection for Speculative Decoding},
  author  = {Zhang, Haohui and Chen, Keyu and Sun, Haocheng and Gu, Weibo and Qiao, Ruizhi and Sun, Xing and Jiang, Bo},
  journal = {arXiv preprint arXiv:2609.36173},
  year    = {2026}
}
```

## License

[Apache 2.0](https://huggingface.co/tencent/Qwen3.8-27B-DSpine-b16/blob/main/LICENSE)

## Want more deterministic results?

[Try Interfaze](https://interfaze.ai/dashboard)[Read the Docs](https://interfaze.ai/docs)