--- license: other license_name: swift-open-license-1.0 license_link: LICENSE library_name: vllm base_model: - ukisai/Swift-Qwen3.8-27b - TheUnderscore/Swift-Qwen3.8-27b-W4A16-AWQ tags: - qwen - qwen3.8 - swift - w4a16 - gptq - compressed-tensors - speculative-decoding - mtp - rtx-3090 - syv pipeline_tag: text-generation --- # Swift-Qwen3.8-27B-W4A16-syv-fast The [syv-ai/qwen38-27b-rtx3090](https://github.com/syv-ai/qwen38-27b-rtx3090) **fast-variant serving shape** of [ukisai/Swift-Qwen3.8-27b](https://huggingface.co/ukisai/Swift-Qwen3.8-27b) (the "reduced reasoning" finetune of Qwen3.8-27B), built entirely from Swift's own weights and outputs: - **Body**: TheUnderscore's W4A16 asymmetric-AWQ g128 compressed-tensors quant of Swift, carried through unmodified. - **lm_head + MTP**: int4 GPTQ (g128, symmetric) calibrated on **Swift's own hidden states** — 300k rows captured through the syv `drafter/` pipeline. lm_head KL to the bf16 head: **0.00234** (RTN: 0.00707; the official syv Qwen fast variant shipped at 0.0029). MTP relative errors 0.146–0.176, inside the range of the shipped syv fast variant. - **Embeddings**: int8 g128, requantized from Swift's own weights. - **Draft vocab**: counted over 4.23M tokens of **Swift's own outputs** on a coding-agent-weighted prompt corpus (35% Rust, 16% TypeScript, 11% debugging, 10% code-edit, 8% agent/tool-use, 10% architecture, 7% technical reasoning, 3% general; 61% thinking-on). Swift emits far fewer distinct tokens than base Qwen (~25.9k vs ~54k), so the draft head is 25,879 rows, not the base model's 40,960. Held-out coverage (10% of sequences, never counted against): | draft vocab | all tokens | code sources | |---|---|---| | **Swift-derived (this model)** | **99.81%** | **99.86%** | | base-Qwen 40k list | 96.69% | 96.67% | ## Serving Designed for the syv single-user stack (vLLM 0.28.0 + the repo's patch series — the MTP draft-vocab patch is required for the 25,879-row head; stock vLLM will not use it): ```bash MODEL=/path/to/Swift-Qwen3.8-27B-W4A16-syv-fast \ SPEC=mtp PREFIX_CACHE=1 CTX=long MAX_LEN=114688 \ bash single-user/start_qwen.sh # from the syv checkout ``` The syv `verify.sh` will report one false FAIL on this dir (it asserts an int8 lm_head; this is int4 by construction, like the official fast variant). ## Measured (RTX 3090, syv stack, MTP + prefix caching, 114,688 context) | | decode tok/s | MTP acceptance | tok/step | |---|---|---|---| | **this model** | 98.4 | **0.660** | 2.98 | | Swift + int8 heads, base draft vocab | 94.0 | 0.630 | 2.89 | | official syv Qwen fast variant | 98.2 | 0.634 | 2.90 | Quality battery (identical prompts): 8/9, matching the int8 build — tool calling, strict JSON, streaming and the qwen3 reasoning parser all clean. Swift's reasoning-termination behaviour is preserved (GPTQ heads verified not to shift it, including under greedy decoding). ## Provenance & licence Attribution chain: **Alibaba Cloud** Qwen3.8-27B (Apache-2.0, included as `LICENSE-APACHE-2.0`) → **UkisAI** Swift finetune (Swift Open License v1.0, included as `LICENSE`) → **TheUnderscore** W4A16-AWQ body (same licence) → this repository's int4-GPTQ heads, int8 embeddings and Swift-derived draft vocabulary (quantisation and calibration by **liamwh**, using the [syv-ai/qwen38-27b-rtx3090](https://github.com/syv-ai/qwen38-27b-rtx3090) `drafter/` pipeline with a coding-agent-weighted Swift corpus). Distributed under the Swift Open License v1.0; commercial use above its revenue threshold requires the Swift Enterprise License. Rebuild from scratch with the syv checkout's `drafter/` pipeline (`gen_data.py` → `capture.py` → GPTQ heads → `build_draft_vocab.py`) over a Swift-weighted prompt corpus; `swift_draft_vocab_ids.json` here is the exact id list this model serves.