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Model Details
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waldie
Model Tree
DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1
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Output Modalities
Supported Functionality
GGUFS, examples, how to modify reasoning settings (jinja) and detailed model card are here:
https://huggingface.co/DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1-NM-DAU-NEO-MAX-MTP-GGUF
IMPORTANT: The COLD FUSION (GAIN+Unsloth) method of training maintains 99% of performance of BF16, at both 8 bit and 4 bit levels.
FINALS STATUS - WE HAVE A WINNER - GGUFs RELEASED:
STATUS:
COLD FUSION? This model uses the COLD FUSION (GAIN+Unsloth) fine tuning and training methods as noted here:
https://huggingface.co/DavidAU/Qwen3.6-27B-V1.1-FF711-Darker-Hero-GAIN-H2.0
And the OFF THE SCALE version: 2000+ likes, 2.9 million+ downloads, 71 quant repos, exceeds all Qwen 3.6 27B performance levels AND metrics (confirmed by third party testing):
About this model: Qwen3.8-27B-Cold-Fusion-GAIN-V1.1 [working title]
This training is about assessing root Qwen3.8-27B and a trained version on known datasets using the COLD FUSION (GAIN+UNSLOTH) training tech which was invented by my team during the R & D of "Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic".
The "GAIN" is the core invented component, then coupled with Unsloth's trainers/systems => AKA -> COLD FUSION.
The training (datasets) itself is focused on raising general intelligence of the model and reducing thinking tokens to 1/10 to 1/2 of "normal qwens".
This is a very light, but strongly focused tune.
The reduction in thinking tokens may need additional balancing to maintain output level detail - this is unclear at the moment.
Qwen 3.8-27B, and trained version[s] of Qwen3.8-27B-Cold-Fusion-GAIN-V1.1 will be benched, compared and human tested.
A second "cook" is in progress to address/assess thinking/output specifically detail levels in both VS untuned Qwen 3.8.
This is prep for more advanced Fable Fusion 711 27B "3.8" version(s) ; which has a far more complex and longer training pipeline (6 stages, with multiple sub-stages) and takes 7-10 days to "run"; run time is due to hardware limits.
Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic is an example a model built using this pipeline, as well as the TWO 40B Qwen 3.6s ("Eleanor" (10 stages), and "Grand Intelligence" (9 stages)) versions and the newest (soon to be released) "Qwen3.6-27B-V1.1-FF711-Darker-Hero-GAIN-H2.0" (working title, 8 stages).
Qwen3.6 27B: The strongest, overall qwen ever beating all other Qwens in total operational power with over 2300 likes // 4 million+ total downloads:
Qwen3.8 27B: The highest scoring Qwen in brute, raw intelligence, using Qwen 3.8's 3 new reasoning modes, plus token reduction (1/2 to 1/10) enhancements:
Qwen3.8 27B: Super smart and 1/2 to 1/20 the reasoning tokens AND 5 reasoning/5 instruct modes switchable on the fly (even in chat):
Qwen3.8 27B: 99% power of BF 16 at 4 and 8 bit. Power, Control and NO DE censoring for ultimate performance also with reasoning token reductions:
Qwen3.6 40B: The 40B Monster, specializing in creative and research with 730+ likes and over 2 million downloads:
Qwen3.5 9B: At just 9B parameters it beats most untuned 27B models in both intelligence (640 ARC-C) and performance, plus features 5 reasoning and 5 instruct modes (Qwen 3.8) too:
Timeline for "Qwen3.8-27B-Cold-Fusion-GAIN-V1.1":
Prelim Testing Results (training #1, CP #1) // "1B":
Cold Fusion GENERATION(S) from TESTING (quant) below.
1B:
NOTES:
Important note on Qwen 27B 3.8 bench VS Qwen 3.6/3.5 27B versions:
Based on my testing / Qwen's own statements, community statements (ie localllama) and extended benchs for 3.8-27B version (team Qwen) this model is more focused on deeper thinking, coding and agentic functions than previous Qwen versions.
text
arc/c arc/e boolq hswag obkqa piqa wino Qwen3.8-27B-Cold-Fusion-GAIN-V1.1[non heretic, cook 1B - FINAL PUBLISED]mxfp8 0.655,0.838,0.898,0.751,0.498,0.807,0.738mxfp4 0.645,0.833,0.887,0.740,0.496,0.799,0.732 Qwen3.8-27B-Cold-Fusion-GAIN-V1.1 [non heretic, cook #1]mxfp8 0.657,0.830,0.900,0.751,0.498,0.807,0.738mxfp4 0.644,0.829,0.899,0.740,0.496,0.799,0.732 --- UNTUNED Qwen3.8-27B-Instruct: [base, non heretic]mxfp8 0.591,0.782,0.896,0.746,0.448,0.801,0.711mxfp4 0.581,0.771,0.889,0.738,0.442,0.798,0.713 Qwen3.6-27B-Instruct: [base, non heretic]mxfp8 0.647,0.803,0.910,0.773,0.450,0.806,0.742 Qwen3.6-35B-A3B-Instruct [base, non heretic]mxfp8 0.581,0.757,0.892,0.751,0.428,0.803,0.688 Qwen3.5-27B-Instruct: [base, non heretic]mxfp8 0.557,0.711,0.868,0.533,0.452,0.706,0.695NOTES:
Q4KS, non imatrix, standard Qwen settings, NO cache compression of any kind.
NOTE: Some formatting may be lost on copy/paste/export.
Example Generation is from BUILD/COOK #1.
For examples of COOK 1B - the final winner - see the above "GGUF" repo.
(Average size including thinking 5k to 7k ; normal Qwen exceeding 16k)
arc/c arc/e boolq hswag obkqa piqa winoQwen3.8-27B-Cold-Fusion-GAIN-V1.1[non heretic, cook 1B - FINAL PUBLISED]mxfp8 0.655,0.838,0.898,0.751,0.498,0.807,0.738mxfp4 0.645,0.833,0.887,0.740,0.496,0.799,0.732Qwen3.8-27B-Cold-Fusion-GAIN-V1.1 [non heretic, cook #1]mxfp8 0.657,0.830,0.900,0.751,0.498,0.807,0.738mxfp4 0.644,0.829,0.899,0.740,0.496,0.799,0.732--- UNTUNEDQwen3.8-27B-Instruct: [base, non heretic]mxfp8 0.591,0.782,0.896,0.746,0.448,0.801,0.711mxfp4 0.581,0.771,0.889,0.738,0.442,0.798,0.713Qwen3.6-27B-Instruct: [base, non heretic]mxfp8 0.647,0.803,0.910,0.773,0.450,0.806,0.742Qwen3.6-35B-A3B-Instruct [base, non heretic]mxfp8 0.581,0.757,0.892,0.751,0.428,0.803,0.688Qwen3.5-27B-Instruct: [base, non heretic]mxfp8 0.557,0.711,0.868,0.533,0.452,0.706,0.695