DeepSeek-V3 is an open-source AI model with 671B total (37B active via MoE) parameters from DeepSeek. DeepSeek flagship chat & code model — top-tier on coding benchmarks, long context tasks, and instruction following. Access it for free on LITHOVEX AI — no download, no API key, no credit card required.
DeepSeek-V3 is an AI model released December 2024 by DeepSeek, a leading organization in large language model research. DeepSeek flagship chat & code model — top-tier on coding benchmarks, long context tasks, and instruction following. With 671B total (37B active via MoE) and a 128K tokens context window, DeepSeek-V3 is designed to excel across a range of demanding tasks — from software engineering and mathematical problem-solving to multilingual content generation and long-document analysis.
DeepSeek-V3 employs a Mixture-of-Experts (MoE) architecture with 671B total (37B active via MoE). In a MoE design, only a subset of "expert" sub-networks activates for each token during inference — DeepSeek-V3 has 671B total (37B active via MoE) total parameters but uses only a fraction per token. This allows the model to store significantly more learned knowledge than a comparably-priced dense model. MoE architectures have proven effective at reaching frontier-level capability while keeping serving costs manageable — a key reason DeepSeek-V3 can be offered at the scale that platforms like LITHOVEX AI make possible.
As of 2026-10-16, DeepSeek-V3 by DeepSeek demonstrates measurable performance on standard AI evaluation benchmarks. On MMLU — which tests world knowledge across 57 academic subjects from elementary to professional level — it achieves 88.5%. For software engineering tasks, DeepSeek-V3 scores 89.9% on HumanEval, which tests ability to write correct functions from docstrings. In mathematical reasoning, DeepSeek-V3 records 90.2% on MATH-500. Across all 5 benchmarks tracked, the model shows consistent capability in its primary task domains. These scores place DeepSeek-V3 — at 671B total (37B active via MoE) of parameters — in a competitive position within its model class. Note that benchmark scores reflect controlled evaluation conditions; real-world performance varies by task, prompt design, and domain specificity.
The primary strengths of DeepSeek-V3 are: MIT license — fully free for commercial use; Trained for ~$5.6M in compute — order of magnitude cheaper than comparable Western models; Strong general-purpose: coding, writing, reasoning, analysis; Fast inference despite large total params thanks to MoE sparse activation. These make it particularly well-suited for General-purpose coding and software development, Business document analysis, API building at high quality and low cost, Enterprise AI integration at scale. Users working on complex, multi-step problems benefit most from DeepSeek-V3's ability to maintain coherence across long inputs and produce structured, verifiable outputs.
Like all current AI systems, DeepSeek-V3 has limitations: Superseded by DeepSeek-V3-0324 and V3.1 with significant improvements; Not a reasoning model — lacks R1's chain-of-thought; Knowledge cutoff December 2024. For production deployments, validating outputs against authoritative sources — especially for domain-specific or time-sensitive information — remains best practice. DeepSeek continues to improve DeepSeek-V3 through ongoing research.
DeepSeek-V3 is available on LITHOVEX AI with a free account. Unlike direct API access — which requires billing setup, API key management, and per-token charges — LITHOVEX AI provides a seamless browser interface with no setup required, making DeepSeek-V3 accessible to students, researchers, developers, and early-stage teams globally.
As of 2026-10-16, DeepSeek-V3 by DeepSeek demonstrates measurable performance on standard AI evaluation benchmarks. On MMLU — which tests world knowledge across 57 academic subjects from elementary to professional level — it achieves 88.5%. For software engineering tasks, DeepSeek-V3 scores 89.9% on HumanEval, which tests ability to write correct functions from docstrings. In mathematical reasoning, DeepSeek-V3 records 90.2% on MATH-500. Across all 5 benchmarks tracked, the model shows consistent capability in its primary task domains. These scores place DeepSeek-V3 — at 671B total (37B active via MoE) of parameters — in a competitive position within its model class. Note that benchmark scores reflect controlled evaluation conditions; real-world performance varies by task, prompt design, and domain specificity.
Mixture-of-Experts: 671B total parameters / 37B active per token
The training pipeline for DeepSeek-V3 involves multiple stages: large-scale pretraining on 14.8 trillion high-quality tokens including code, math, web data, and multilingual corpora to develop broad world knowledge, followed by supervised fine-tuning on instruction-response pairs, and alignment techniques such as RLHF or DPO. Each stage refines the model's helpfulness, accuracy, and safety. DeepSeek's research team — based in China — has optimized DeepSeek-V3 for the specific capability profile described above.
Inference efficiency: DeepSeek-V3 at 671B total (37B active via MoE) is designed to deliver quality outputs at practical serving speeds. Its 128K tokens context window enables processing entire documents, multi-file codebases, and extended conversation histories — particularly valuable for contract review, technical documentation analysis, and codebase-level AI assistance.
Getting started with DeepSeek-V3 on LITHOVEX AI takes under two minutes. Follow these steps:
For best results with DeepSeek-V3: provide specific, context-rich prompts; include examples when generating code; specify output format when structure matters; break complex tasks into focused sub-questions.
DeepSeek is a Chinese AI research company founded in 2023, backed by High-Flyer — one of China's leading quantitative hedge funds. Despite its brief history, DeepSeek has made an outsized global impact with open-weight releases, particularly the DeepSeek-R1 and DeepSeek-V3 families. The company's research philosophy prioritizes efficiency and transparency: models are released under MIT licenses, and detailed technical reports accompany each release, influencing the broader AI research community. DeepSeek's engineering team demonstrated that frontier-level performance could be achieved at dramatically lower training costs than Western competitors — a revelation that reshaped industry assumptions about AI development economics. As of 2025, DeepSeek's models rank among the most-used open AI models globally.
Funding: Backed by High-Flyer Capital Management
Founded: 2023, headquartered in China.
DeepSeek-V3 by DeepSeek competes in a field with several strong alternatives. Below is a detailed side-by-side comparison against commonly listed alternatives, using benchmark data and capability profiles in the catalog.
Both DeepSeek-V3 and the models above are available free on LITHOVEX AI — test them side by side on your real tasks before committing to a subscription with any provider.
DeepSeek-V3 is released under MIT, which means you can download and run it on your own hardware. Below are the quickest ways to get started.
LITHOVEX AI runs DeepSeek-V3 on cloud infrastructure, so you can use it instantly in your browser without downloading anything, configuring drivers, or managing VRAM. Create a free account and start in under 60 seconds.
DeepSeek-V3 is deployed globally across research institutions, startups, and enterprises. As an open-source model from DeepSeek (China), it is freely available in every country without geographic restrictions. Developers worldwide use it for local deployment on their own hardware, eliminating data privacy concerns. Its open nature enables fine-tuning for specific languages, domains, and regional use cases — making it particularly valuable for under-resourced language communities.
DeepSeek-V3 by DeepSeek has the following version history and notable updates:
For the complete changelog and latest release notes, visit the official DeepSeek model page.