DeepSeek-V4-Pro is a frontier Mixture-of-Experts model with a large context window and three reasoning modes.
DeepSeek-OCR is a vision-language model that can perform token-efficient OCR.
DeepSeek-R1 is a family of open reasoning models with performance approaching that of leading models, such as O3 and Gemini 2.5 Pro.
DeepSeek Coder is a capable coding model trained on two trillion code and natural language tokens.
DeepSeek-V3.1-Terminus is a hybrid model that supports both thinking mode and non-thinking mode.
A fully open-source family of reasoning models built using a dataset derived by distilling DeepSeek-R1.
A version of the DeepSeek-R1 model that has been post trained to provide unbiased, accurate, and factual information by Perplexity.
An upgraded version of DeekSeek-V2 that integrates the general and coding abilities of both DeepSeek-V2-Chat and DeepSeek-Coder-V2-Instruct.
A strong Mixture-of-Experts (MoE) language model with 671B total parameters with 37B activated for each token.
A reset version of Eriktonon's DeepSeekv4.1-Flash - Ready for use in AI Agent Scenarios
UNCENSORED (Abliterated + SecOps) — DeepSeek-V4.1-Flash-1017 (9B Compact & 27B Large 128K Edition) — Fine-tuned & Orthogonally Abliterated for Agents Architecture, Rust Systems & Autonomous Tool-Use.
A fine-tuned DeepSeek-R1-70B model for CVE-worthiness review, exploit-path analysis, and JSON-only vulnerability triage.
Uncensored DeepSeek-R1-0528-Qwen3-8B via Heretic: 4/100 refusals (from 89), KL 0.041. Reasoning model, MIT.
Jackrong/Qwen3.5-9B-DeepSeek-V4-Flash - is an efficient reasoning model distilled using high-quality data from DeepSeek-V4. + vision. ollama v.0.30.0-rc20 +
DeepSeek.
pull from hf.co/Jackrong/Qwen3.5-9B-DeepSeek-V4-Flash-GGUF
Omnigenesis Lyapunov stability specialist based on DeepSeek R1 1.5B
DeepSeek-V4-Flash 284B MoE (13B active), single-file IQ2_M merged from AtomicChat's GGUF shards so Ollama can pull it. ~33 tok/s on a 128 GB Apple Silicon Mac. Model by DeepSeek (MIT), quantization by AtomicChat.
DeepSeek-V4-Flash-Fast is a custom agent build based on DeepSeek-V4-Flash (Open Weights, Apache-2.0, MoE, ~285B total / ~20B active). Weights in low-bit quantization for fully CPU-only deployment:
No Oficial 29 t/s en 8 VRAM - Calidad a escala fronteriza como GPT-5.5, DeepSeek-V4-pro y Kimi-K2.6.