{
  "video_id": "reddit_1wcd4rx",
  "channel_slug": "LocalLLaMA",
  "channel_handle": "r/LocalLLaMA",
  "title": "Deepseek V4.1 Flash is 748B, not 552B",
  "url": "https://www.reddit.com/r/LocalLLaMA/comments/1wcd4rx/deepseek_v41_flash_is_748b_not_552b/",
  "external_url": null,
  "upload_date": "20260910",
  "published_at": "2026-09-10T08:27:47+00:00",
  "transcript": "People keep on getting confused about this, so I looked at the safetensors on hf.\n\nThe title should have been \"Deepseek V4.1 Flash is 748B total/552B base, not 284B or 305B or 485B or 522B\"\n\n- The model is not 284B. The original Deepseek V4 Flash is 284B, but not the V4.1 Flash model\n- The model is not 305B, [despite what some people claim](https://forums.developer.nvidia.com/t/deepseek-v4-1-flash/382725/11) `\"So: ~305B real backbone + 203B engram = 508B total\"` This is incorrect.\n- The model is not 485B, even though Huggingface lists the model as 485B, but that's because they're counting some FP4 packed weights as bytes instead of params (2 FP4 params per byte). This happens a lot; for example [Huggingface incorrectly thinks GLM-5.3-flash is 169b here](https://huggingface.co/nvidia/GLM-5.3-Flash-NVFP4)\n- The model is not 522B, even though [VLLM lists it as 522B for some weird reason](https://recipes.vllm.ai/deepseek-ai/DeepSeek-V4.1-Flash). They correct themselves later down the page (ctrl-f \"Params\" on that vllm page)\n- 552B is the only number out of this list that's somewhat correct; that only includes the base model without MTP and engrams and the vision encoder though.\n\nTo be precise, the main model about 551.566B parameters with 40 layers. The FFN experts total to 543.582B parameters, and the rest of the model (attention, shared experts, etc) are 7.984B.\n\nOn top of that, the engram is \\~196.929B, DSpark/MTP is \\~14.225B, and the vision encoder is just \\~0.485B. These parts are technically optional though. The vision encoder is also way smaller than I expected.\n\nAnyways, you need a beefy system for this. 128GB or 256GB of RAM/VRAM is not going to cut it.\n\n\n\n--- Top Comments ---\n\n\n[45 upvotes] So when DS v4.1 supersonic flash? \n\n[31 upvotes] If ngrams can be offloaded to SSD what SSD should be optimized for, linear speed or random 4k reads?\n\n[22 upvotes] It's flash because it's fast. It uses something ridiculous like 9B parameters for prefilling. ",
  "transcript_chars": 1985,
  "ingested_at": "2026-09-10T13:30:02.271031+00:00",
  "source": "reddit",
  "yt_meta": {
    "score": 126,
    "upvote_ratio": 0.89,
    "num_comments": 95,
    "author": "DistanceSolar1449",
    "is_self": true
  }
}