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Nicolassuez/Qwen3.8-27B-W4A16
Qwen3.8-27B-W4A16 is a text generation model from Nicolassuez. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
A conservative int4 quantization of Qwen/Qwen3.8-27B: the MLP and full-attention projections go to int4, the Gated DeltaNet linear-attention projections stay in bf16.
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I3218.8B · 68%
From the Hugging Face model README
A conservative int4 quantization of Qwen/Qwen3.8-27B: the MLP and full-attention projections go to int4, the Gated DeltaNet linear-attention projections stay in bf16.
In most cases you want Qwen3.8-27B-W4A16-GDN instead, which quantizes the GDN block as well. It is smaller AND faster AND more concurrent, at quality measured identical. There is no axis on which this checkpoint wins. Keep reading for the numbers and for the two cases where this one is still the right file.
Measured from the safetensors headers, every tensor accounted for. Total 25.77 GiB on disk.
| block | precision | size | tensors |
|---|---|---|---|
| Gated DeltaNet linear attention | bf16 | 10.36 GiB | 432 |
| MLP | int4 | 8.22 GiB | 576 |
embed_tokens | bf16 | 2.37 GiB | 1 |
lm_head | bf16 | 2.37 GiB | 1 |
| Vision tower | bf16 | 0.86 GiB | 333 |
| Full attention | int4 | 0.81 GiB | 224 |
| MTP / NEXTN draft head | bf16 | 0.79 GiB | 15 |
| norms and misc | bf16 | ~0.00 GiB | 129 |
Quantized to int4: 9.03 GiB. Left in bf16: 15.96 GiB. The single largest weight block in this model is the one that was NOT quantized, and it is larger than everything the pass actually touched.
This checkpoint was built under the belief that serving engines had no int4 path for Gated DeltaNet.
That was tested afterwards and is false. The engine accepts int4 GDN weights and fails only in the
Marlin repack kernel, on exactly two tensors out of the whole block: in_proj_a and in_proj_b,
both 48 x 5120, which engines fuse into one in_proj_ba with 96 outputs where Marlin requires a
multiple of 64. Excluding those two, about 1% of the GDN's parameters, lets the other 99% compress.
That is what the -GDN sibling does.
H100 PCIe, SGLang, context 65536, fp8 KV cache, card otherwise empty. Decode is single stream.
| checkpoint | weights | no speculation | NEXTN 3 | NEXTN 4 | concurrent requests |
|---|---|---|---|---|---|
| this checkpoint | 25.21 GB | 62 tok/s | 125 tok/s | - | 12 without spec, 4 with |
Qwen3.8-27B-W4A16-GDN | 17.65 GB | 83 tok/s | 151 tok/s | 155 tok/s | 17 without spec, 6 with |
30% fewer bytes bought 34% more decode, and the KV pool grew from 330326 to 461132 tokens. This is not a size-against-speed trade: the engine runs at 86% of the card's bandwidth, so decode is simply bandwidth divided by bytes read, and compressing more makes it faster.
Both checkpoints were compared against Qwen/Qwen3.8-27B-FP8 on the same engine and flags, 8 bits
being close to lossless and not our own work. On a 27-item verification set both score 24/27 with
thinking off and 27/27 with thinking on, missing the same three arithmetic items as the official
FP8 reference, and both answer 4/4 on the multilingual set. At temperature 0 every verifiable
conclusion is identical across the three. So the extra 7.5 GB this checkpoint carries buys nothing
measurable in quality.
No delta against the bf16 source has been measured, so this is a not-broken gate rather than a precision figure.
-GDN checkpoint ever
misbehaves, and it is the artifact the -GDN results were compared against.size_n = 96 is not divisible by tile_n_size = 64.Outside those two cases, prefer the -GDN sibling.
A standard compressed-tensors checkpoint. Native context 262144, and it carries an MTP head, so
speculative decoding works and is worth roughly 2x on decode. Serving notes, memory levers and the
token-map trick that adds another 26% are documented on the
-GDN card; they apply here unchanged.
Two traps also documented there and worth repeating: do NOT pack the vocabulary and serve it on a
stock SGLang (it loads, reports healthy, and answers with an unbroken run of !, with nothing in the
logs), and reasoning_effort accepts only none, low, medium and xhigh on this family's chat
template, so high returns a 400.
Produced by script_quantif_w4a16.sh at its default settings, which is the standard profile of
run_qwen38_27b_w4a16.sh. The -GDN sibling is the same script with MAX_COMPRESSION=1. The
recipe.yaml in this repository records the exact modifier.