{
 "id": "r9dc0747a006",
 "found": true,
 "parent_id": "rfd33f114311",
 "created_at": "2026-08-31 22:02:03.429778+00:00",
 "rows": [
  {
   "url": "https://z.ai/blog/glm-5.1",
   "title": "GLM-5.1: Towards Long-Horizon Tasks",
   "published_at": null,
   "release": {
    "organization": null,
    "model": "GLM-5.1",
    "release_date": "2026-04-07",
    "parameters": null,
    "context_window": null,
    "license": "MIT License",
    "summary": "next-generation flagship model for agentic engineering, with significantly stronger coding capabilities than its predecessor",
    "organization_evidence": null,
    "model_evidence": [
     "GLM-5.1: Towards Long-Horizon Tasks",
     "GLM-5.1 is our next-generation flagship model for agentic engineering, with significantly stronger coding capabilities than its predecessor."
    ],
    "release_date_evidence": [
     "2026-04-07 \u00b7 Research",
     "GLM-5.1: Towards Long-Horizon Tasks"
    ],
    "parameters_evidence": null,
    "context_window_evidence": null,
    "license_evidence": [
     "GLM-5.1: Towards Long-Horizon Tasks",
     "GLM-5.1 is released as open source under the MIT License."
    ],
    "summary_evidence": [
     "GLM-5.1: Towards Long-Horizon Tasks",
     "GLM-5.1 is our next-generation flagship model for agentic engineering, with significantly stronger coding capabilities than its predecessor."
    ]
   }
  },
  {
   "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro?show_file_info=model.safetensors.index.json",
   "title": "deepseek-ai/DeepSeek-V4-Pro \u00b7 Hugging Face",
   "published_at": "2026-04-24T02:53:41",
   "release": {
    "organization": "DeepSeek-AI",
    "model": "DeepSeek-V4",
    "release_date": "2026",
    "parameters": "1.6T total (49B activated) for DeepSeek-V4-Pro, 284B total (13B activated) for DeepSeek-V4-Flash",
    "context_window": "1,000,000 tokens",
    "license": "MIT",
    "summary": " Mixture-of-Experts language models designed for efficient million-token context intelligence, coding, reasoning, and agentic tasks.",
    "organization_evidence": [
     "# DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence",
     "@misc{deepseekai2026deepseekv4, title={DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence}, author={DeepSeek-AI}, year={2026}, }"
    ],
    "model_evidence": [
     "# DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence",
     "We present a preview version of **DeepSeek-V4** series, including two strong Mixture-of-Experts (MoE) language models \u2014 **DeepSeek-V4-Pro** with 1.6T parameters (49B activated) and **DeepSeek-V4-Flash** with 284B parameters (13B activated) \u2014 both supporting a context length of **one million tokens**."
    ],
    "release_date_evidence": [
     "# DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence",
     "@misc{deepseekai2026deepseekv4, title={DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence}, author={DeepSeek-AI}, year={2026}, }"
    ],
    "parameters_evidence": [
     "# DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence",
     "We present a preview version of **DeepSeek-V4** series, including two strong Mixture-of-Experts (MoE) language models \u2014 **DeepSeek-V4-Pro** with 1.6T parameters (49B activated) and **DeepSeek-V4-Flash** with 284B parameters (13B activated) \u2014 both supporting a context length of **one million tokens**."
    ],
    "context_window_evidence": [
     "# DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence",
     "We present a preview version of **DeepSeek-V4** series, including two strong Mixture-of-Experts (MoE) language models \u2014 **DeepSeek-V4-Pro** with 1.6T parameters (49B activated) and **DeepSeek-V4-Flash** with 284B parameters (13B activated) \u2014 both supporting a context length of **one million tokens**."
    ],
    "license_evidence": [
     "# DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence",
     "This repository and the model weights are licensed under the [MIT License](/deepseek-ai/DeepSeek-V4-Pro/blob/main/LICENSE)."
    ],
    "summary_evidence": [
     "# DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence",
     "We present a preview version of **DeepSeek-V4** series, including two strong Mixture-of-Experts (MoE) language models \u2014 **DeepSeek-V4-Pro** with 1.6T parameters (49B activated) and **DeepSeek-V4-Flash** with 284B parameters (13B activated) \u2014 both supporting a context length of **one million tokens**."
    ]
   }
  },
  {
   "url": "https://huggingface.co/zai-org/GLM-4.5/discussions/20/files",
   "title": "zai-org/GLM-4.5 \u00b7 Improve model card with detailed quick start, system requirements, and paper link clarification",
   "published_at": "2025-08-11T13:14:01",
   "release": {
    "organization": "Zhipu AI",
    "model": "GLM-4.5",
    "release_date": "2025-08-11",
    "parameters": "355B total parameters with 32B active parameters",
    "context_window": "128K",
    "license": "MIT",
    "summary": "foundation models designed for intelligent agents",
    "organization_evidence": [
     "# GLM-4.5",
     "\ud83d\udcd6 Check out the GLM-4.5 <a href=\"https://z.ai/blog/glm-4.5\" target=\"_blank\">technical blog</a>, <a href=\"https://arxiv.org/abs/2508.06471\" target=\"_blank\">technical report</a>, and <a href=\"https://zhipu-ai.feishu.cn/wiki/Gv3swM0Yci7w7Zke9E0crhU7n7D\" target=\"_blank\">Zhipu AI technical documentation</a>."
    ],
    "model_evidence": [
     "# GLM-4.5",
     "The **GLM-4.5** series models are foundation models designed for intelligent agents."
    ],
    "release_date_evidence": [
     "# GLM-4.5",
     "\ud83d\udcd6 Check out the GLM-4.5 <a href=\"https://z.ai/blog/glm-4.5\" target=\"_blank\">technical blog</a>, <a href=\"https://arxiv.org/abs/2508.06471\" target=\"_blank\">technical report</a>, and <a href=\"https://zhipu-ai.feishu.cn/wiki/Gv3swM0Yci7w7Zke9E0crhU7n7D\" target=\"_blank\">Zhipu AI technical documentation</a>."
    ],
    "parameters_evidence": [
     "# GLM-4.5",
     "GLM-4.5 has **355** billion total parameters with **32** billion active parameters, while GLM-4.5-Air adopts a more compact design with **106** billion total parameters and **12** billion active parameters."
    ],
    "context_window_evidence": [
     "# GLM-4.5",
     "Under the configurations in the table below, the models can utilize their full 128K context length:",
     "| Model | Precision | GPU Type and Count | Test Framework |"
    ],
    "license_evidence": [
     "# GLM-4.5",
     "We have open-sourced the base models, hybrid reasoning models, and FP8 versions of the hybrid reasoning models for both GLM-4.5 and GLM-4.5-Air. They are released under the MIT open-source license and can be used commercially and for secondary development."
    ],
    "summary_evidence": [
     "# GLM-4.5",
     "The **GLM-4.5** series models are foundation models designed for intelligent agents."
    ]
   }
  }
 ],
 "notes": [
  "Merged 8 queries (1279 total) \u2192 1277 unique results",
  "Search result set: rfd33f114311 (1277 rows), reference it as FROM rfd33f114311 in follow-up queries"
 ]
}