DeepSeek AI

2026DeepSeek AI

DeepSeek-V4-Flash vV4-Flash

Paid
DeepSeek-V4-Flash
DeepSeek-AI

DeepSeek-V4-Flash is a Mixture-of-Experts (MoE) language model developed by DeepSeek-AI, featuring 284 billion total parameters with 13 billion activated, and supporting a context length of one million tokens. It offers advanced capabilities in text generation and conversational AI, optimized for efficiency and scalability.

284 billion total parameters with 13 billion activated
Supports a context length of one million tokens
Optimized for efficiency and scalability
VersionV4-Flash
RegionChina
2026DeepSeek AI

DeepSeek-V4-Pro vV4-Pro

Paid
transformers
safetensors

DeepSeek-V4-Pro is a Mixture-of-Experts (MoE) language model developed by DeepSeek AI, featuring 1.6 trillion total parameters with 49 billion activated parameters. It utilizes a hybrid attention architecture combining Compressed Sparse Attention (CSA) and Heavily Compressed Attention (HCA), achieving 27% of single-token inference FLOPs compared to its predecessor, DeepSeek-V3.2, at a 1 million-token context length. The model supports a context window of 1 million tokens, enabling efficient processing of extensive text inputs. DeepSeek-V4-Pro is available under the MIT license, allowing for both commercial and non-commercial use. It is accessible through platforms like Hugging Face and NVIDIA NGC, with integration options for various libraries and inference providers. The model has been evaluated on multiple benchmarks, demonstrating strong performance across tasks such as reasoning, coding, and general language understanding. For instance, it achieved an 87.5% score on the MMLU-Pro benchmark and a 90.1% score on the GPQA Diamond benchmark. These evaluations highlight DeepSeek-V4-Pro's capabilities in complex reasoning and problem-solving tasks. The model is optimized for deployment on various hardware platforms, including NVIDIA GPUs and Huawei's Ascend AI processors, reflecting DeepSeek AI's commitment to supporting diverse hardware ecosystems. This versatility ensures that DeepSeek-V4-Pro can be effectively utilized across different computational environments, catering to a wide range of applications in natural language processing and AI-driven tasks.

1.6 trillion total parameters with 49 billion activated parameters
Hybrid attention architecture combining CSA and HCA
27% of single-token inference FLOPs compared to DeepSeek-V3.2 at 1 million-token context
VersionV4-Pro
RegionChina
2026DeepSeek AI

DeepSeek Harness vDeveloper Preview

Open Source
Featured
AI Agents
Open Source

DeepSeek Harness (dsh) is an open-source agent runtime framework designed for building autonomous agents. It utilizes a modular architecture where every component—including models, tools, session management, and the agent loop—is implemented as a plugin powered by the Cordis framework.

Plugin-based architecture powered by Cordis
Composable runtime via profiles and bundles
Durable session logging for replay and auditability
PricingOpen Source (MIT License)
VersionDeveloper Preview
2026DeepSeek AI

DeepSeek V4 Pro DSpark v1.0

Open Source
LLM
MoE

DeepSeek V4 Pro DSpark is an advanced mixture-of-experts (MoE) language model optimized for high-efficiency, million-token context intelligence. It features a specialized speculative decoding module to accelerate inference performance while maintaining state-of-the-art reasoning and agentic capabilities.

1.6 Trillion parameter MoE architecture (49B activated)
Support for 1 million token context length
Hybrid Attention Architecture (CSA and HCA) for efficiency
PricingFree
Version1.0
2026DeepSeek AI

DeepSeek-V4-Flash-0731 v0731

Open Source
LLM
Agentic AI

DeepSeek-V4-Flash-0731 is an official, re-post-trained version of the DeepSeek-V4-Flash model, featuring significantly enhanced agentic capabilities and a built-in DSpark speculative decoding module. It is designed for high-efficiency, large-scale tasks, offering competitive performance in coding, reasoning, and multi-step tool use.

1 million token context window
384K maximum output token length
DSpark speculative decoding module for enhanced throughput
Version0731
RegionChina

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