AI NEWS · 모델 정보기능을 이해하고 근거 있게 선택하세요. ↗기본 정보 우선 등록 · 상세 정보 지속 보완
THE AI MODEL DIRECTORY 모델 탐색을 시작하세요

나에게 맞는 AI 모델을 찾아보세요.

언어부터 이미지, 오픈 웨이트부터 API까지. 기능과 실제 비용을 비교하세요.
다음 아이디어에 맞는 AI를 찾아보세요.

인기 검색
85,003 개 모델13202 개 제공사 / 게시자45 개 기능 분류465개 비교 가능 요금 · 30개 공개 평가
T텍스트 생성▧이미지 생성▷영상 생성⌘코드 생성◖음성 합성♫음악 생성⬡3D 모델링▤문서 분석
DISCOVER & COMPARE

AI 모델 탐색 22972

주목할 모델을 찾아보세요

SecGPT-7B-GGUF

clouditera

我们基于 **Qwen2.5-Instruct 系列** 与 **DeepSeek-R1 系列** 模型,结合自建安全任务集与安全知识库, 在 **8台A100 GPU** 集群上持续训练一周以上,完成大规模预训练 + 指令微调 + 强化学习, 显著提升模型在安全场景中的**理解、推理与响应能力**。 我们已构建了一个超大规模、结构完备的网络安全语料库,总量超过 **5TB**、共计 **106,721 个原始文件**,其中超过 **40% 内容为人工精选与结构化处理**。私有数据部分系统整合了具备 **70+ 字段 / 14 类结构标签体系** 的安全数据资源,经过统一清洗、语义标注与重构,构建出 **数百亿 Tokens 级**的高质量语料,为大模型深度推理能力提供坚实支撑。 为全面评估 SecGPT 的安全实战能力,我们构建了一套覆盖**安全证书问答、安全通识、编程能力、知识理解与推理能力**的综合评估体系,主要采用以下标准化数据集:CISSP、CS-EVAL、CEVAL、GSM8K、BBH。

번역 대기 중 · 원문 표시

입력 텍스트→ 출력 텍스트
요금 미확인멀티모달 및 채널 요금 별도 확인
자세히 보기 ↗
출처 / 문서 ↗

This is an English & Chinese MoE Model , slightly different with cloudyu/Mixtral_34Bx2_MoE_60B, and also based on * [jondurbin/bagel-dpo-34b-v0.2] * [SUSTech/SUS-Chat-34B]

번역 대기 중 · 원문 표시

입력 텍스트→ 출력 텍스트
요금 미확인멀티모달 및 채널 요금 별도 확인
자세히 보기 ↗
출처 / 문서 ↗

A 180B MoE model built on the Qwen3.8-Flash-Next architecture: Gated DeltaNet linear attention interleaved with Qwen Sparse Attention (QSA), 512 experts with top-10 routing plus a shared expert, gated residual (hyper-connection) streams, and a 51B-parameter hashed n-gram embedding table. Only ~6B parameters are computed per token, so throughput on CPU is closer to a 6B dense model while quality is that of a much larger one. - JiRack is a cloud-ready model that helps save money on cloud infrastructure. It can be used as an expert model in RAG deployments, with the ONNX JiRack Java server as an alternative. **Important:** until QAT is complete, the JiRack 180B weights are numerically identical to the base model (lambda = 0 means BitLinear is a pure passthrough). The ternary benefits described on this card apply after QAT. Published in this repository. Before QAT all of them are quantizations of the unchanged base-model weights.

번역 대기 중 · 원문 표시

입력 텍스트→ 출력 텍스트
요금 미확인멀티모달 및 채널 요금 별도 확인
자세히 보기 ↗
출처 / 문서 ↗

JiRackDeltaNet_27b

CMSManhattan

A fast and efficient 27B model optimized for CPU inference. Built on a Qwen3.8-style DeltaNet architecture (hybrid attention + SSM), with an updated tokenizer that includes **Routing**, **Media**, **Vision**, **Sound**, **Tool call**, and **Robotics** tags. Ready-to-run GGUF quantizations, and native Ollama support with reasoning disabled by default for fast, direct responses. - JiRack is a cloud-ready model that helps save money on cloud infrastructure. It can be used as an expert model in RAG deployments, with the ONNX JiRack Java server as an alternative. Once the container is running, open your browser and navigate to: `http://localhost:7869` This opens the JiRack UI — a clean web interface. The listening port can be easily modified directly from the **Settings** panel within the JiRack UI.

번역 대기 중 · 원문 표시

입력 텍스트→ 출력 텍스트
요금 미확인멀티모달 및 채널 요금 별도 확인
자세히 보기 ↗
출처 / 문서 ↗

JiRackUltra_14b

CMSManhattan

A fast and efficient 14B model optimized for CPU inference. The model was refactored with BitNet features and an updated tokenizer that includes new **Routing**, **Media**, **Vision**, **Sound**, **Tool call**, and **Robotics** tags. Built on a DeepSeek R1-14B architecture with native ternary (BitNet-style) support and ready-to-run GGUF quantizations. - JiRack is a cloud-ready model that helps save money on cloud infrastructure. It can be used as an expert model in RAG deployments, with the ONNX JiRack Java server as an alternative. https://huggingface.co/spaces/CMSManhattan/JiRackUltra_14b - https://huggingface.co/spaces/CMSManhattan/JiRack-36B-Chat - https://huggingface.co/spaces/CMSManhattan/JiRack-16B-Chat - https://huggingface.co/spaces/CMSManhattan/JiRack-8B-Chat - https://huggingface.co/spaces/CMSManhattan/JiRack-2B-Chat Once the container is running, open your browser and navigate to: `http://localhost:7869` This opens the JiRack UI — a clean web interface. The listening port can be easily modified directly from the **Settings** panel within the JiRack UI. - Model weights are released under the MIT License — free to use, modify, and distribute for any purpose, including commercial. No royalties, no per-user fees, no subscription. - The Docker image with UI and the pre-built Ollama quantizations are separate paid products. If you prefer to build your own secure deployment — take the weights, assemble your own stack, and you're done. - The JiRack Ultra 14B model for Docker and Ollama is provided under a commercial license ($12 per user per year). - All JiRack UI clients are provided under a commercial license. - However, the UI clients can be used for free when running together with the official JiRack Docker containers, as long as they are not redistributed separately. For commercial licensing, cluster deployment, or enterprise use of JiRack models, please contact us. - **JiRack MS Windows 11 Desktop Client (with Ollama API):** https://huggingface.co/kgrabko/JiRackTernary_1b/resolve/main/jirack-chat.zip - **Live email chat with the model:** support@cmsmanhattan.com | Use Case | CPU | RAM | Recommended Quant | Expected Speed | Recommendation | |-----------

번역 대기 중 · 원문 표시

입력 텍스트→ 출력 텍스트
요금 미확인멀티모달 및 채널 요금 별도 확인
자세히 보기 ↗
출처 / 문서 ↗

JiRackUltra_1b

CMSManhattan

A fast and efficient ~1.5B model optimized for CPU inference. The model was refactored with BitNet features and an updated tokenizer that includes new **Routing**, **Tool call**, and **Robotics** tags. Built on a redesigned DeepSeek R1 architecture with native ternary (BitNet-style) support and ready-to-run GGUF quantizations. - JiRack is a cloud-ready model that helps save money on cloud infrastructure. It can be used as an expert model in RAG deployments, with the ONNX JiRack Java server as an alternative. - Benefits high quality CPU inference TQ_2 on Llama.cpp and Ollama via QAT - Robotcs, Routing, Coding, Multimedia, Advanced tool calling via CMSManhattan/JiRackPrecisionTokenizer - We are working to support JiRack on Ollama for production systems also - added Jirack chat without reasoning feature https://ollama.com/cmsmanhattan - Follow fresh Ollama platform updates

번역 대기 중 · 원문 표시

입력 텍스트→ 출력 텍스트
요금 미확인멀티모달 및 채널 요금 별도 확인
자세히 보기 ↗
출처 / 문서 ↗

JiRackUltra_32b

CMSManhattan

A fast and efficient 32B model optimized for CPU inference. The model was refactored with BitNet features and an updated tokenizer that includes new **Routing**, **Media**, **Vision**, **Sound**, **Tool call**, and **Robotics** tags. Built on a DeepSeek R1-32B architecture with native ternary (BitNet-style) support and ready-to-run GGUF quantizations. - JiRack is a cloud-ready model that helps save money on cloud infrastructure. It can be used as an expert model in RAG deployments, with the ONNX JiRack Java server as an alternative. Once the container is running, open your browser and navigate to: `http://localhost:7869` This opens the JiRack UI — a clean web interface. The listening port can be easily modified directly from the **Settings** panel within the JiRack UI. - Model weights are released under the MIT License — free to use, modify, and distribute for any purpose, including commercial. No royalties, no per-user fees, no subscription. - The Docker image with UI and the pre-built Ollama quantizations are separate paid products. If you prefer to build your own secure deployment — take the weights, assemble your own stack, and you're done. - The JiRack Ultra 32B model for Docker and Ollama is provided under a commercial license ($12 per user per year). - All JiRack UI clients are provided under a commercial license. - However, the UI clients can be used for free when running together with the official JiRack Docker containers, as long as they are not redistributed separately. For commercial licensing, cluster deployment, or enterprise use of JiRack models, please contact us. - **JiRack MS Windows 11 Desktop Client (with Ollama API):** https://huggingface.co/kgrabko/JiRackTernary_1b/resolve/main/jirack-chat.zip - **Live email chat with the model:** support@cmsmanhattan.com | Use Case | CPU | RAM | Recommended Quant | Expected Speed | Recommendation | |-------------------|----------------------------|-----------|-------------------|---------------------|----------------| | Recommended | Ryzen 9 / Intel i9 / Xeon | 32–48 GB | Q4_K_M | Good interactive | Best choice | | High Performance | High-core server CPU | 64 GB+ | Full / Q4 | Excellent | Excellent | | Low

번역 대기 중 · 원문 표시

입력 텍스트→ 출력 텍스트
요금 미확인멀티모달 및 채널 요금 별도 확인
자세히 보기 ↗
출처 / 문서 ↗

JiRackUltra_7b

CMSManhattan

A fast and efficient 7B model optimized for CPU inference. The model was refactored with BitNet features and an updated tokenizer that includes new **Routing**, **Media**, **Vision** , **Sound** ,**Tool call**, and **Robotics** tags. Built on a DeepSeek R1 -7B architecture with native ternary (BitNet-style) support and ready-to-run GGUF quantizations. - JiRack is a cloud-ready model that helps save money on cloud infrastructure. It can be used as an expert model in RAG deployments, with the ONNX JiRack Java server as an alternative. The listening port can be easily modified directly from the **Settings** panel within the JiRack UI. For commercial licensing, cluster deployment, or enterprise use of JiRack models, please contact us.

번역 대기 중 · 원문 표시

입력 텍스트→ 출력 텍스트
요금 미확인멀티모달 및 채널 요금 별도 확인
자세히 보기 ↗
출처 / 문서 ↗
COST EXPLORER

좋은 모델, 명확한 비용.

비용 분석

월간 토큰 사용량으로 예상 API 비용을 비교하세요.

1 M = 100만 토큰 · USD
동일 채널의 기본 텍스트 토큰 요금 비교

수집된 백만 토큰당 USD 요금입니다. 캐시 할인, 구간 요금, 추가 추론 출력, 세금은 제외됩니다. 최신 요금은 출처에서 확인하세요.

MODEL HANDBOOK

이해하고 선택하세요

선택 가이드 및 FAQ
API 요금은 어떻게 비교하나요?+

입력, 출력, 캐시 요금을 구분하고 동일 작업량으로 비교하세요. 이미지, 음성, 영상은 개수, 시간, 해상도로 과금될 수 있습니다.

오픈 웨이트는 무료 상업 이용을 뜻하나요?+

반드시 그렇지는 않습니다. 버전별 라이선스, 상업 이용 제한, 정책을 확인하세요. 자체 호스팅에는 연산 및 유지 비용도 듭니다.

1위 모델이 나에게 가장 적합한가요?+

순위는 작업, 버전, 평가 방식에 따라 다릅니다. 실제 업무로 정확도, 지연, 안정성, 비용을 비교하세요.

AI NEWS · 정보에서 선택으로

뉴스로 흐름을, 도구로 효율을, 모델로 가능성을.

AI 뉴스 탐색 ↗AI 도구 찾기 ↗