Downloads · 30 days
23
32% of all-time downloads
JasonW2025/Qwen3.6-27B-PrismaQuant-5.1bit-Hybrid
Qwen3.6-27B-PrismaQuant-5.1bit-Hybrid is a text generation model from JasonW2025. Use it when you need the model to write or continue text.
A 5.1 bits-per-weight, mixed-precision ("Hybrid") quantization of Qwen3.6-27B, built with PrismaQuant and served on vLLM (compressed-tensors). Precision is allocated per layer by measured sensitivity (Fisher diagonal…
Downloads · 30 days
23
32% of all-time downloads
All-time downloads
71
Public
Parameters
18B
22.4 GB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors22.4 GB · 100%
How the weights are stored.
U811.2B · 62%
From the Hugging Face model README
A 5.1 bits-per-weight, mixed-precision ("Hybrid") quantization of Qwen3.6-27B, built with PrismaQuant and served on vLLM (compressed-tensors). Precision is allocated per layer by measured sensitivity (Fisher diagonal + validated output-KL): NVFP4 (W4A4) on robust layers, FP8 on sensitive ones, BF16 on the most sensitive (embeddings, norms, lm_head, MTP head). Average 5.1 bpp. Per-layer map is in mixed_native_manifest.json.
At the time of upload, it scores the highest of any Qwen 3.6 27B in the best agentic tool-calling bench.
Measured on tool-eval-bench 2.0.7, deterministic harness (prefix-cache off, temp 0, single-stream, reference-validated in-session), identical serve recipe for both models:
| Model | Tool-eval (headline) | Hardmode | GSM8K | IFEval (prompt/instr) |
|---|---|---|---|---|
| Qwen3.6-27B-PrismaQuant-5.1bit-Hybrid | 93 | 83 | 90.5% | 76.5% / 82.6% |
Headline = full tool-eval across categories; hardmode = the hard split. Numbers are on one pinned harness version and are not comparable to scores from other versions.
vllm serve <path-or-repo> \
--dtype bfloat16 --gpu-memory-utilization 0.85 --max-model-len 32768 \
--trust-remote-code --attention-backend flashinfer \
--enable-chunked-prefill --no-enable-prefix-caching \
--quantization compressed-tensors --kv-cache-dtype fp8 \
--enable-auto-tool-choice --tool-call-parser qwen3_coder --reasoning-parser qwen3 \
--default-chat-template-kwargs '{"enable_thinking": false}' \
--speculative-config '{"method":"mtp","num_speculative_tokens":2}'
num_speculative_tokens=2 — k=2 maximizes decode throughput on tested hardware; k=3 is net overhead at the current acceptance rate. (The MTP head may be updated with a version trained against the quantized weights for higher acceptance.)