DeepSeek-V4.1-Flash-1017-TrellisMX-FLARE
JMNI-Labs · Kit
Serves DeepSeek V4.1 Flash across two NVIDIA DGX Sparks with an OpenAI-compatible API, from a compressed TrellisMX package. For teams running a large model on…
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DeepSeek-V4.1-Flash-1017-EXL3-franken-v100
philbert440 · Kit
Runs DeepSeek V4.1 Flash at its full 1M-token context on eight Tesla V100 32 GB cards, using an EXL3 expert pack and an SM70 vLLM build. For owners of such ser…
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DeepSeek-V4.1-Flash-NVFP4
nvidia · Kit
Reads text and images and writes text, as a smaller NVFP4 copy of DeepSeek-V4.1-Flash made by NVIDIA. For developers deploying agents, chatbots and retrieval s…
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DeepSeek-V4.1-Flash-1017-oQ4e-ngram-mtp
mlx-community · Kit
A mixed-precision MLX copy of DeepSeek-V4.1-Flash-1017 that keeps the Engram tables at FP8. Made for people with hundreds of GB of memory who want to run the m…
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DeepSeek-V4.1-Flash-1017-FLARE
local-inference-lab · Kit
Signed Flare runtime packages of DeepSeek V4.1 Flash 1017 for four-GPU serving, handling text and images behind an OpenAI-compatible API. For people running la…
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DeepSeek-V4.1-Flash-1017-GSQ-agentic-strata
kaushikvira · Kit
Runs the 763.2B-parameter DeepSeek V4.1 Flash as a 153 GiB mixed-precision build tuned for agentic and coding work on the strata engine. For people with a larg…
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DeepSeek-V4.1-Flash-1017 GGUF
ggml-org · Kit
GGUF files of DeepSeek's 748B V4.1 Flash 1017 model, converted by ggml-org with a vision file for images, for people with big-memory machines who run models th…
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DeepSeek-V3.2
deepseek-ai · Kit
A 685B open reasoning model from DeepSeek with sparse attention for long context and a chat template that lets it think while it calls tools. For teams that ru…
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DeepSeek V4.1 Flash GGUF for DwarfStar
antirez · Kit
Gives Mac users calibrated 2-bit and 4-bit GGUF files of DeepSeek V4.1 Flash, plus a separate vision encoder, for DwarfStar's Metal engine with SSD streaming.…
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DeepSeek-V4.1-Flash-1017-oQ4e-mtp
mlx-community · Kit
A mixed-precision MLX copy of DeepSeek-V4.1-Flash-1017, a huge multimodal mixture-of-experts model. Made for people with hundreds of GB of memory who want to r…
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Runs a pruned, 2-bit DeepSeek-V4.1-Flash on a 128 GB Mac through mlx-serve, keeping 192 of 384 experts and a 1M-token context. Strongest on code, reasoning and…
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DeepSeek-V4.1-Flash-1017-exl3
turboderp · Kit
Runs a compressed DeepSeek-V4.1-Flash-1017 in ExLlamaV3 at 1.68, 2.25 or 2.68 bits per weight. For people who run large models on their own hardware and want l…
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DeepSeek-V4.1-Flash-1017 TrellisMX K2 Mix
brandonmusic · Kit
A compressed copy of DeepSeek-V4.1-Flash-1017 sized for two 96 GB GPUs, with a few experts stored at higher precision. A research build for people who serve la…
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DeepSeek-V4.1-Flash-1017 Maya GGUF
peasantsmith · Kit
Runs a 748B DeepSeek mixture-of-experts model on a home PC through two GGUF quantizations made for Project Maya. For people with a big-RAM machine and a fast S…
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DeepSeek-V4.1-Flash-1017-NVFP4
nvidia · Kit
NVIDIA's NVFP4 quantized copy of DeepSeek AI's DeepSeek-V4.1-Flash-1017, a huge multimodal mixture-of-experts model for NVIDIA Blackwell GPUs.
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DeepSeek-V4.1-Flash-1017 EXL3 EAQ v1 2.9 bpw
Mia-AiLab · Kit
A 2.9 bits-per-weight EXL3 quantization of DeepSeek-V4.1-Flash-1017 that reads text and images. It cuts the model to about 210 GB for exllamav3 runtimes, and t…
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DeepSeek-V4.1-Flash-EXL3-3bpw-2x-RTX-PRO-6000
diffbot · Kit
Serves a 3-bit compressed copy of DeepSeek-V4.1-Flash-1017 on two 96 GB RTX PRO 6000 Blackwell cards with vLLM, for developers who host a large coding and agen…
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DeepSeek-V4.1-Flash-1017-Sushi-STQ-1.75bpw
beamster · Kit
Runs a 261B DeepSeek V4.1 Flash model packed to about 1.75 bits per weight for the sushi engine on Apple Silicon Macs, with image input and up to 1,048,576 tok…
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DeepSeek-V4.1-Flash-1017-Basalt
jesdga · Kit
Packs DeepSeek V4.1 Flash into single model files for the Basalt engine, which runs it on one NVIDIA Blackwell GPU with system RAM covering the experts that do…
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DeepSeek-R1
deepseek-ai · Kit
Generates text with a 684B reasoning model trained mainly through reinforcement learning, aimed at math, code and logic. Suits researchers and teams who host l…
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