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AI 모델 84753
- Qwen2.5 72B Instruct↗
阿里巴巴 · Qwen
Qwen2.5 72B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabilities in coding and...
- qwen3-0.6b↗
阿里巴巴 · Qwen
Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training, Qwen3 delivers groundbreaking advancements in reasoning, instruction-following, agent capabilities, and multilingual support, with the following key features: **Qwen3-0.6B** has the following features: - Type: Causal Language Models - Training Stage: Pretraining & Post-training - Number of Parameters: 0.6B - Number of Paramaters (Non-Embedding): 0.44B - Number of Layers: 28 - Number of Attention Heads (GQA): 16 for Q and 8 for KV - Context Length: 32,768 For more details, including benchmark evaluation, hardware requirements, and inference performance, please refer to our blog, GitHub, and Documentation.
- GLM5.3-Flash-E224-DGX-Spark↗
autotrust
> [!IMPORTANT] > **Try AutoTrust/GuruSearch live (new, 11 October 2026).** A recommendation and search demo in which every ranking is a > calibrated System 1 decision, made in about half a second: > * **Recommendation:** the latest headlines from 6 news feeds, ranked by importance. > * **Search:** results from Google News, Bing News and Yahoo News re-ranked by relevance, side by side with the > search engines' own order, plus a short answer with citations. **autotrust/GLM5.3-Flash-E224-DGX-Spark is a compact build of zai-org/GLM-5.3-Flash for desktop Blackwell systems like NVIDIA DGX Spark. It's an unofficial derivative.** > 🚀 **Deploying on DGX Spark?** A complete, field-tested runbook for > serving this checkpoint on **two ConnectX-7-linked DGX Sparks** > (vLLM 0.31.0, TP=2, fp8 KV cache) is here: > **DEPLOY-2X-DGX-SPARK.md** — network setup, > NCCL/CX7 pitfalls, memory budgeting, ops & troubleshooting, and > measured throughput (15.7 tok/s single-stream, 71.8 tok/s at 8-way > concurrency, both GPUs ≈96% utilized).
- JEV-9B↗
autotrust
> [!IMPORTANT] > **Try AutoTrust/GuruSearch live (new, 11 October 2026).** A recommendation and search demo in which every ranking is a > calibrated System 1 decision, made in about half a second: > * **Recommendation:** the latest headlines from 6 news feeds, ranked by importance. > * **Search:** results from Google News, Bing News and Yahoo News re-ranked by relevance, side by side with the > search engines' own order, plus a short answer with citations. **Fast, calibrated System 1 decisions that are indistinguishable from the closed TypeSafe Jev 1.13 by KL, and deliberate System 2 generation and reasoning from an untouched Qwen3.5-9B — one set of weights, one vLLM engine, routed per request. The fastest model of the family: it answers a single decision in about a third of the time the hosted API takes. Its successor, autotrust/JEV-27B, is closer to Jev, transfers better to unseen tasks and has a stronger System 2.** JEV-9B now takes images. Every step below is **one System 1 decision**: camera image or screenshot in, a probability for every action out, in a single forward pass (about 0.2 s on one GPU). Run it with `bash vl/serve.sh` (see Images: quick start).
- ozone-research_0x-lite-GGUF↗
bartowski
- Sailor2-1B-Chat-GGUF↗
bartowski
- Qwen3-4b-Z-Image-Engineer-V4↗
BennyDaBall
V4 still rocks as the original Qwen3 prompt-engineer build. The new V6 release is the native Z-Image Turbo text-encoder build, rebuilt with SMART DoRA and trained locally for ComfyUI drop-in use plus LM Studio prompt enhancement. This is Z-Engineer V4, the culmination of extensive research into what makes an AI prompt engineer actually *good* at its job. Built on the Qwen 3 architecture and trained using a novel **SMART Training** methodology, this 4B parameter model doesn't just describe scenes—it understands the craft of visual storytelling down to the lens flare. Z-Engineer V4 is a fully fine-tuned (not LoRA, we went *all in*) version of the text encoder from Tongyi-MAI/Z-Image-Turbo. It's been specifically trained to understand the nuances of AI Image Generation workflows.
- rf-r16-sp03↗
bmars8218
- DeepSeek-Coder-V2-Instruct-GGUF↗
bullerwins
- stable-audio-3↗
Comfy-Org
- https://huggingface.co/stabilityai/stable-audio-3-medium - https://huggingface.co/stabilityai/stable-audio-3-medium-base - https://huggingface.co/stabilityai/stable-audio-3-small-music - https://huggingface.co/stabilityai/stable-audio-3-small-music-base - https://huggingface.co/stabilityai/stable-audio-3-small-sfx - https://huggingface.co/stabilityai/stable-audio-3-small-sfx-base