Qwen3.8-Cold-Fusion-GAIN-NM-DAU-NEO-MAX-MTP

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What Qwen3.8-Cold-Fusion-GAIN-NM-DAU-NEO-MAX-MTP is

version also reduces thinking tokens by 1/2 to as much as 1/10 the amount, while maintaining core details AND reasoning power. Model exceeds all Qwen 3.8, 3.6 and 3.5 27B critical core benchmarks. MTP speeds are also faster. A model that gets down to business faster, with less "talking" and is smarter too. Part of the tech is based on (2200+ likes, 3m + downloads): Fable-Fusion-711 Cold Fusion has 1/5 (as low as 1/10 in some cases) to 1/2 the thinking tokens (vs reg Qwen 3.8) across all 3 modes of operation, and it is faster and smarter too created using the COLD FUSION method of training. This is a high detail focused model, with tuning specific to address over reasoning/over thinking and excessive token consumption. EXAMPLE generations at the bottom of the page. A Colab between myself (tuning, COLD Fusion), Nightmedia (benching), and TeichAI (Datasets). The strict goals of this model creation were: - Increase the general model intelligence and problem solving abilities. - Reduce thinking block size from 1/2 to as low as 1/10 the size [median reduction: 2/3 roughly]. - Reformatting the thinking block, as well as improving it. - Speed up token generation, especially MTP. - Ensure all updates work with all three modes of thinking. - ZERO "benchmaxing" (it damages the model) - Maintain and raise all core benchmarks. 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" (2100+ likes, 3 million + downloads, 60+ quant repos): https://huggingface.co/DavidAU/Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-NEO-MAX-MTP-GGUF The "GAIN" is the core invented component, then coupled with Unsloth's trainers/systems = AKA - COLD FUSION. The "GAIN" method (programming) automatically (and dynamically) changes training on a per sample basis in real time during training AS THE MODEL LEARNS. The method improved metrics as well as overall model performance without overcooking or damaging the model. This has also resulted, in the strongest and most stable model at both 4 bit and 8 bit and made 4 bit performance 99% of 8 bit performance too. Note this model (Qwen3.8-27B-Cold-Fusion-GAIN-V1.1)

Summarised from the published model card. Read the full card on the HuggingFace links below.

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Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

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Call it like any OpenAI endpoint

Once AxForge deploys qwen3-8-cold-fusion-gain-nm-dau-neo-max-mtp for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (qwen3-8-cold-fusion-gain-nm-dau-neo-max-mtp below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/chat/completions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"qwen3-8-cold-fusion-gain-nm-dau-neo-max-mtp","messages":[{"role":"user","content":"Hello"}]}'

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