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NVFP4 (W4A4, compressed-tensors) quantization of
InternScience/Agents-A1-4B
— a 4B agentic model on the Qwen3.5 dense architecture (
Qwen3_5ForConditionalGeneration
: hybrid DeltaNet linear attention + full attention every 4 layers, Qwen3-VL vision tower, 262K context).
Bonus — grafted MTP:
the source checkpoint declares
mtp_num_hidden_layers: 1
but ships no
mtp.*
weights. This repo grafts the 15-tensor bf16 MTP draft head from the base model
Qwen/Qwen3.5-4B
(identical text-config dims), enabling speculative decoding:
63–66% draft acceptance, ~+20% single-stream decode
(measured, see below)
Scheme:
NVFP4 W4A4, group size 16, via llm-compressor 0.11.0 / compressed-tensors 0.16.0
Measured throughput — single GPU (vLLM 0.22.0, RTX PRO 2000 Blackwell SM120, KV fp8, 512-tok decode)
Config
single-stream (c1)
aggregate 8-way (c8)
vs base
base (no MTP)
73.6 t/s
492.9 t/s
—
MTP n=3 (grafted)
88.6 t/s
474.5 t/s
+20.4% c1
/ −3.7% c8
SpecDecoding metrics (vLLM): mean acceptance length ~2.9, per-position acceptance 0.83 / 0.66 / 0.48, avg draft acceptance
63–66%
— remarkable for a draft head grafted from the pre-fine-tune base model across InternScience's 3-stage agentic distillation. As usual, MTP is a latency win (single-stream / low concurrency); at saturation the extra draft forward costs slightly more than it saves.
Speculative decoding is lossless — outputs are identical to base decoding.
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