AI Model2026
Provides an FP8-post-trained 27B multimodal causal language model with a native vision encoder, large-context support (262,144 native, extensible to 1,000,000), controllable thinking-mode reasoning, and compatibility with common inference engines for deployment.
AI Model2026
Provides a 27B Qwen3.8 GGUF build for local/offline deployment, optimized with Unsloth Dynamic V3.0 quantization. Offers switchable thinking-mode, native vision-language understanding, and native long-context support (262k+ tokens).
AI Model2026
Provides a Mixture-of-Experts language model tuned for million-token contexts and agentic workflows, with DSpark speculative decoding, FP4/FP8 mixed-precision support, and vLLM/SGLang deployment recipes for low-latency production inference.
AI Model2026
A 27B Qwen3.8 vision‑language causal transformer quantized to NVFP4 for lower‑memory inference. Provides 262K native context (extensible to 1M), Unsloth Dynamic V3.0 4‑bit quantization and MTP support so Qwen3.8‑class multimodal workloads can run on 24GB‑class GPUs.
AI Dataset2026
Provides a machine-readable catalog of 117 AI/AX safety and deployment-readiness diagnostic criteria for assessing model intrinsic and serving/infrastructure risks. Includes MODEL-SCAN and AX-SCAN axes, bilingual source fields, per-item evidence guidance, severity/assurance metadata, and a CC BY-NC 4.0 release-candidate.