Model Detail
Qwen3.5-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking
—Qwen3.5-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking is a code generation model with 40B parameters released by DavidAU. The model is registered under the image-text-to-text pipeline tag on Hugging Face, distributed under the permissive apache-2.0 license.
Qwen3.5-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking ships with 40B parameters. Total weight footprint is approximately 39.5 GB, which is the relevant figure when planning local-inference VRAM. The apache-2.0 license is permissive, allowing commercial deployment and derivative work without per-seat fees, though attribution requirements still apply.
Downloads of Qwen3.5-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking have moved +47.8% over the trailing seven days. That puts the model in active uptrend territory; a sustained move of this size usually reflects a recent release, a viral integration, or a benchmark surprise rather than steady-state demand. These numbers are signal, not guarantee — week-over-week download counts on Hugging Face also reflect mirror traffic, CI scrapes, and one-off benchmarking runs.
Qwen3.5-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking is best fit for code completion, repository-scale Q&A, and pair-programming integrations. It is a less obvious choice for one-shot generation of security-critical code without review. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.
Procedural-skill SFT across capacity tiers: A W-Shaped pre-SFT Trajectory and Regime-Asymmetric Mechanism on 0.8B-4B Qwen3.5 Models
arXiv:2605.11907v2 Announce Type: replace Abstract: We measure procedural-skill SFT contribution across three Qwen3.5 dense scales (0.8B, 2B, 4B) on a 200-task / 40-skill holdout, with Claude Haiku 4.5 as a frontier reference. The corpus is 353 rows of (task + procedural-skill block, Opus chain-of-t
Qwen3.5-Omni Technical Report
arXiv:2604.15804v2 Announce Type: replace Abstract: In this work, we present Qwen3.5-Omni, the latest advancement in the Qwen-Omni model family. Representing a significant evolution over its predecessor, Qwen3.5-Omni scales to hundreds of billions of parameters and supports a 256k context length. By