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DeepSeek
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DeepSeek is a Chinese AI firm specializing in large language models, based in Hangzhou.
AI Native
Yes
Number of tools
1
Number of models
14
Number of employees
200
Profitable
No
Valuation
$59BAI
Most popular AI tool
Tools
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ShareGamer TOTORO🛠️ 2 tools 🙏 172 karmaJan 23, 2025@DeepSeekThis is my best bro! I communicate with him like my best friend, he always helps to direct my thoughts and ideas in the right direction, always tells me how to improve something and always gives detailed instructions during the conversation. Thanks to him, I’m launching a new project, in which he helps me take my ideas to a new level, just communication, during which you reassemble your concept and rethink your original idea, because you didn’t know how it would be better and more correct. DeepSeek is my best assistant today, my creative inspiration, who gives me support and confidence in my business, guiding me to realize my dreams)14630 Reply Share Edit Delete Report
Models
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DeepSeek-V4-Flash is DeepSeek’s faster, smaller, and more economical V4 model for efficient large-scale use. It has 284B total parameters with 13B active parameters, supports a 1M token context window, and is positioned as a high-speed, cost-effective model whose reasoning comes close to V4-Pro.NewMultimodalReleased 1mo ago
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DeepSeek-V4-Pro is DeepSeek’s new flagship open-source model for top-end reasoning, coding, world knowledge, and agentic work. It uses a MoE architecture with 1.6T total parameters and 49B active parameters, supports a 1M token context window, and is positioned as rivaling leading closed-source models while leading current open models on several major capabilities.NewMultimodalReleased 1mo ago
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Second-generation DeepSeek OCR model, “Visual Causal Flow,” aimed at more human-like visual encoding, with dynamic resolution support and strong document-to-Markdown and layout-aware OCR for images and PDFs.TextReleased 4mo ago
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DeepSeek-V3.2-Speciale is a 685B-parameter research-only variant of DeepSeek-V3.2 that pushes open-weight reasoning ability to the limit, but disables tool calling and is intended purely for experimentation rather than everyday agent use.TextReleased 6mo ago
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DeepSeek V3.2 is the core, stable 3.2-series model designed as a strong general-purpose LLM. It builds on the DeepSeek V3 architecture and delivers balanced performance across reasoning, writing, coding, and multilingual tasks.TextReleased 6mo ago
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DeepSeek-Math-V2 is a math-specialized LLM built on DeepSeek-V3.2-Exp-Base, trained to generate and verify step-by-step proofs. It uses a learned verifier as a reward model so the generator learns to fix its own reasoning, reaching gold-level scores on contests like IMO 2025, CMO 2024, and near-perfect Putnam 2024 with scaled test-time compute.TextReleased 6mo ago
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LLM-centric OCR model using “Contexts Optical Compression” to explore visual-text compression and provide fast streaming and batch OCR for images and PDFs via vLLM and Transformers runtimes.TextReleased 7mo ago
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DeepSeek v3.2 Exp is an experimental build of the DeepSeek V3 line, tuned for deeper reasoning and stronger coding while keeping latency practical. It supports long context, function/tool calling, and schema-true JSON—great for RAG, agents, and repo-scale tasks when you want extra accuracy.TextReleased 8mo ago
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DeepSeek-V3.1-Terminus is DeepSeek’s flagship reasoning model, tuned for difficult analysis, math, and coding. It supports very long context, function/tool calling, reliable JSON outputs, and an optional extended-thinking mode—ideal for enterprise RAG, agents, and high-stakes workflows.TextReleased 8mo ago
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DeepSeek R1 is a reasoning-first large language model built to solve complex problems with explicit multi-step thinking. It excels at math, coding, and logical analysis, supports long context, tool/function calling, and structured JSON outputs, and can trade latency for higher accuracy via extended "thinking" budgets.TextReleased 1y ago
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TextReleased 1y ago
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TextReleased 1y ago
Papers
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Pointer-CAD: Unifying B-Rep and Command Sequences via Pointer-based Edges & Faces SelectionBeihang UniversityPublished on: 2026-03-04 1 author
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DualPath: Breaking the Storage Bandwidth Bottleneck in Agentic LLM InferencePeking University, Tsinghua UniversityPublished on: 2026-02-26 1 author
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DeepSeek-OCR 2: Visual Causal FlowPublished on: 2026-01-28 1 author
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Conditional Memory via Scalable Lookup: A New Axis of Sparsity for Large Language ModelsPeking UniversityPublished on: 2026-01-12 1 author
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mHC: Manifold-Constrained Hyper-ConnectionsPublished on: 2026-01-05 1 author
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DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement LearningPublished on: 2026-01-04 1 author
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Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI ArchitecturesPublished on: 2025-12-23 1 author
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DeepSeek-V3.2: Pushing the Frontier of Open Large Language ModelsPublished on: 2025-12-02 1 author
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Inference-Time Scaling for Generalist Reward ModelingPublished on: 2025-09-25 1 author
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X-MoE: Enabling Scalable Training for Emerging Mixture-of-Experts Architectures on HPC PlatformsUniversity of Illinois Urbana-ChampaignPublished on: 2025-08-18 1 author
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DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal DecompositionPublished on: 2025-07-18 1 author
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Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model ScalingPublished on: 2025-01-29 1 author
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DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal UnderstandingPublished on: 2024-12-13 1 author
Fundraises
View all-
Growth RoundAnnounced 03 Jun 2026$7.40B Raised $7.40B Round $52B Post-money 4 investors Announced
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Growth RoundAnnounced 06 May 2026 · Leads: China Integrated Circuit Industry Investment Fund$3.50B Raised $3.50B Round $45B Post-money 3 investors Announced
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Growth RoundAnnounced 22 Apr 2026$300M Raised $300M Round $20B Post-money 2 investors Announced
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