Model · Image and text to text
Jun Kim
This model was quantized using oQ (oMLX v0.7.1) mixed-precision quantization with Improved oQe Quantization (jundot/omlx#4385). A mixed-precision MLX checkpoint of deepseek-ai/DeepSeek-V4.1-Flash, a multimodal mixture-of-experts model with 552B backbone parameters, a Causal Encoder-Decoder layout, Compressed Sparse Attention 2 (CSA2), Engram conditional memory and DSpark speculative decoding. It includes the language model, the Engram tables, the vision encoder, the multimodal aligner and the DSpark MTP weights. The effective average is 3.104 bits/weight excluding the Engram tables, or 3.592 bits/weight for the complete checkpoint. oQ2.5e allocates bits by measured layer sensitivity, then…
Open weights
mit
102.4B parameters
1,048,576 tokens
mlx
Excellent 50% prune by Nickyang utilizing new RAZOR methodology. cleyesode further reduced memory requirements via nvfp4 quantization for use on Blackwell sm120 gpus. Quantization via NVIDIA/Model-Optimizer custom qwen4exp workflow: Please see post-quantization verificationreport for details. PLE isolated, full model repack for reduced memory pressure. Calibrated on curated samples from Nickyang/RazorCal: This model demonstrates very impressive retention of pre-prune / pre-quantize abilities - benchmarks in-progress. MTP is present but untested, updates will be posted as they become available. vLLM compatible via the latest branch: Example launch on 4 5060Ti 16GB GPUs (tensor parallel 4…
Open weights
other
88.1B parameters
262,144 tokens
transformers
autotrust/GLM5.3-Flash-E192-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. It keeps 192 of the 288 routed experts in each layer by Neural Architecture Search (NAS), uses NVFP4 for the experts and still activates 18 B parameters per token. The weights take 124 GiB, the smallest in the family: two DGX Sparks connected by ConnectX-7 get about 62 GiB of weights per node and the most KV room of any build, and a single 180 GB Blackwell GPU (B200/GB200) runs it with 32 GiB of KV cache. The KV cache uses FP8. The repo includes a ready-to-use NVFP4 MTP draft in mtp-nvfp4/ (6.95 GB) for speculative decoding. On…
Open weights
mit
110.7B parameters
1,048,576 tokens
vllm
Public research conversion of badtheorylabs/Tinfield-1, derived from Qwen/Qwen3.8-Flash-Next. The source checkpoint was pinned to f7c714a97b71342db9e2fc04009d2704c656c80c. This Hugging Face repository contains the complete original export, including all 10 safetensors shards: - PLE embeddings, vision, MTP and other non-expert weights: retained in BF16. - The original configuration, tokenizer, processors and tensor index accompany the shards. The ple-int8-e579 Kaggle variant is a separate quantized PLE derivative. This Hugging Face checkpoint contains BF16 PLE. Load all shards and the configuration from this repository together. Conversion used NVIDIA Model-Optimizer recipe commit…
Open weights
other
117B parameters
262,144 tokens
transformers
Model · Image and text to text
Qwen
Over recent months, we have intensified our focus on developing foundation models that deliver exceptional utility and performance. Qwen3.5 represents a significant leap forward, integrating breakthroughs in multimodal learning, architectural efficiency, reinforcement learning scale, and global accessibility to empower developers and enterprises with unprecedented capability and efficiency. For more details, please refer to our blog post Qwen3.5. WMT24++: a harder subset of WMT24 after difficulty labeling and rebalancing; we report the averaged scores on 55 languages using XCOMET-XXL. Empty cells (--) indicate scores not yet available or not applicable. Empty cells (--) indicate scores not…
Open weights
apache-2.0
125.1B parameters
262,144 tokens
transformers
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. It keeps 224 of the 288 routed experts in each layer by Neural Architecture Search (NAS), uses NVFP4 for the experts and still activates 18 B parameters per token. The weights take 141 GiB, which is small enough for two DGX Sparks connected by ConnectX-7 (256 GB of unified memory in total) with room left for long-context KV cache. A single 180 GB Blackwell GPU (B200/GB200) can also run it. The original GLM-5.3-Flash MTP layer ships unmodified in mtp/ (BF16) as an optional speculative-decoding draft. It gives about 1.85×…
Open weights
mit
127.6B parameters
1,048,576 tokens
vllm
