LFM2.5-VL-3B-DSpark is an experimental speculative-decoding draft model for the vision-language target model LiquidAI/LFM2.5-VL-3B. It is intended to enable faster decoding while preserving the target model's output. The source lists compatibility with LFM2.5-VL-3B and its GGUF counterpart, and describes draft model details such as 279.5M BF16 parameters, a specified backbone configuration, Markov and confidence heads, and a vocabulary of 128,000.
Model size
0.28B
Format
FP16 weights
Context
128,000
Freshness 90 out of 100. Repository age: 27 days old, Sep 18, 2026. Measures age, not quality.Freshness90/10027 days old
Popularity 40 out of 100. 1,115 downloads in 30 days; 20 lifetime likes. Checked Oct 15, 2026. Measures adoption, not quality.Popularity40/1001.1K downloads / 30d
LFM2.5 VL 3B DSpark GGUF is a GGUF build of LiquidAI/LFM2.5-VL-3B-DSpark for llama.cpp. It is a standalone draft sidecar containing only a drafter with 4 attention layers, a Markov head, a confidence head, and block size 9, used for speculative decoding with a compatible LFM2.5-VL-3B-GGUF target model. Token embeddings and the LM head are shared from the target model at load time, so pairing with the target file is required. The supplied F16 drafter file is 567 MB. Speculative decoding is described as exact under greedy decoding because the target verifies every proposed token.
Format
GGUF
Freshness 90 out of 100. Repository age: 27 days old, Sep 18, 2026. Measures age, not quality.Freshness90/10027 days old
Popularity 41 out of 100. 1,608 downloads in 30 days; 12 lifetime likes. Checked Oct 15, 2026. Measures adoption, not quality.Popularity41/1001.6K downloads / 30d