AI Model2026
An OpenAI-compatible LLM checkpoint optimized for agentic and long-context scenarios, shipping DSpark speculative decoding and vLLM/SGLang deployment recipes; tailored for code-agent and multi-step reasoning workloads and released under MIT.
AI Model2026
Enables local use of a GGUF-quantized DeepSeek-V4-Flash-0731 via Unsloth Dynamic quantizations; provides a Q8 (162GB) lossless option and smaller Q4 variants for lower-memory inference and agentic scenarios using Unsloth tooling.
AI Model2026
Provides a GGUF-quantized, llama.cpp-compatible build of LiquidAI's LFM2.5-2.6B for local CPU inference and offline deployment. Supports multilingual generation and long-context workflows; optimized for low-memory, on-device use.
AI Model2026
Finetunes Qwen3.6‑35B using an adversarial generator–critic loop that synthesizes ~10,000 verifiable “frontier” tasks to boost scientific research, long‑horizon reasoning, coding and tool use; supports an extended 262,144‑token context and common serving stacks.
AI Model2026
A 35B additive ternary-quantized variant of Mach-1 that aims to preserve most capabilities of its BF16 teacher while reducing compute and memory; shows ~95% mean retention across 12 benchmarks and competitive per-task parity on several evaluations.
AI Model2026
Provides GGUF-quantized, ComfyUI-ready MiniMax‑H3 model files (FL2VA/REF2VA, text encoder, audio/video VAEs) to enable local ComfyUI inference for short video + stereo audio generation; requires the official VAEs and sufficient VRAM.
AI Model2026
Provides ComfyUI-ready INT8 MiniMax‑H3 checkpoints (conditioning encoder plus optional generation tail) for a Heretic-edited Qwen3‑VL‑32B source; preserves the vision tower in BF16 and uses row-wise ConvRot INT8 quantization to reduce VRAM needs for ~32GB GPUs. Not a full Transformers generation repository.
AI Model2026
ComfyUI-ready H3 conditioning encoder builds for Qwen3-VL-32B: a BF16 full-precision checkpoint, an INT8 ConvRot quantized checkpoint, and an optional generation tail (layers 50–63). Retains vision tower in BF16 and targets H3 workflows and lower-VRAM systems.
AI Model2026
A quickly trained 2D "tine" VAE for MiniMax‑H3 that speeds up preview renders of video outputs and typically outperforms latent2rgb for preview use. Currently only compatible with the ModelPreviewOverride node in ComfyUI‑KJNodes and intended for previewing rather than production-grade decoding.
AI Video2026
Experimental MiniMax H3 variant that injects learned stylistic and motion 'character' from LTX 2.3, Wan 2.2 and Krea 2 into H3 by surgically grafting attention and MLP components; preserves H3 modality routing while shifting t2v/i2v aesthetics, with limited audio impact and community-license constraints.
AI Model2026
A 20B ternary-weight Mixture-of-Experts reasoning LLM optimized for on-device and low-memory inference—delivers high throughput (200+ tok/s on M4) and an extremely long 131k-context for math/logic benchmarks, but is a preview with limited agentic fine-tuning.
AI Model2026
An uncensored NVFP4-quantized text encoder for MiniMax-H3 video generation that fits on a single 16 GB GPU. Mixed-precision bake (mostly NVFP4, embedding left as INT8), preserves ConvRot rotation semantics, and includes the unrotate step required to avoid corrupted conditioning.