公式ドキュメントに基づく DeepSeek のモデル、API、推論、コーディング、エージェント機能の更新。
公式ドキュメントに基づく DeepSeek のモデル、API、推論、コーディング、エージェント機能の更新。
Opening up the in-house search API DeepSeek's web and API search capabilities are powered by our in-house DeepSeek search engine, which reliably handles hundreds of millions of search requests from around the world every day. DeepSeek Search is an AI-native general-purpose search engine that indexes hundreds of billions of web pages, supports multilingual search, and returns highly relevant, aut
検証済みの公式情報の抜粋 · 英語DeepSeek-V4.1-Flash Release Today, we officially release the DeepSeek-V4.1-Flash model. It is the smallest model in our new architecture family, with native multimodal visual understanding. The new architecture is designed for a higher capability ceiling, faster inference, higher throughput, and scaling to larger models. GPQA Diamond: 90.9 HLE: 36.8 (39.1*) Codeforces (Rating): 3471 MathArena Ap
検証済みの公式情報の抜粋 · 英語DeepSeek-V4-Flash-Vision-Exp Release Today, the new multimodal vision understanding model DeepSeek-V4-Flash-Vision-Exp is now available on the DeepSeek API platform. This is an experimental model that can be accessed by setting model='deepseek-v4-flash-vision-exp' . Terminal Bench 2.1: 83.9 NL2Repo: 57.7 DeepSWE: 59.3 DSBench-Hard: 63.6 AutomationBench (Public): 25.7 ApexBench (Pass@1): 36.5 Age
検証済みの公式情報の抜粋 · 英語DeepSeek-V4-Pro Update The GA release of DeepSeek-V4-Pro has been rolled out on the APP, Web, and API. The API calling method remains unchanged — simply set the model name to deepseek-v4-pro to use the latest version. Significantly enhanced Agent capabilities The GA version of DeepSeek V4 Pro greatly enhances agent capabilities, with particularly significant performance improvements in productio
検証済みの公式情報の抜粋 · 英語DeepSeek-V4-Flash Update The official release of the DeepSeek-V4-Flash API is now in public beta. The API calling method remains unchanged — simply set the model name to deepseek-v4-flash to use the latest version. Significantly enhanced agent capabilities, with benchmark results far exceeding V4-Pro-Preview: Terminal Bench 2.1: 82.7 NL2Repo: 54.2 Cybergym: 76.7 DeepSWE: 54.4 Toolathlon verified
検証済みの公式情報の抜粋 · 英語DeepSeek-V4 The DeepSeek API now supports V4-Pro and V4-Flash, available via both the OpenAI ChatCompletions interface and the Anthropic interface. To access the new models, the base_url remains unchanged, and the model parameter should be set to deepseek-v4-pro or deepseek-v4-flash . The two legacy API model names, deepseek-chat and deepseek-reasoner , will be discontinued in three months (2026
検証済みの公式情報の抜粋 · 英語DeepSeek-V3.2 Both deepseek-chat and deepseek-reasoner have been upgraded to DeepSeek-V3.2. deepseek-chat corresponds to DeepSeek-V3.2's non-thinking mode deepseek-reasoner corresponds to DeepSeek-V3.2's thinking mode DeepSeek-V3.2-Speciale DeepSeek-V3.2-Speciale is served via a temporary endpoint: base_url=" https://api.deepseek.com/v3.2_speciale_expires_on_20251215 ". Same pricing as V3.2, n
検証済みの公式情報の抜粋 · 英語DeepSeek-V3.2-Exp Both deepseek-chat and deepseek-reasoner have been upgraded to DeepSeek-V3.2-Exp. deepseek-chat corresponds to DeepSeek-V3.2-Exp's non-thinking mode deepseek-reasoner corresponds to DeepSeek-V3.2-Exp's thinking mode For more details, please refer to this documentation .
検証済みの公式情報の抜粋 · 英語DeepSeek-V3.1-Terminus Both deepseek-chat and deepseek-reasoner have been upgraded to DeepSeek-V3.1-Terminus. deepseek-chat corresponds to DeepSeek-V3.1-Terminus's non-thinking mode , while deepseek-reasoner corresponds to its thinking mode . This update maintains the model's original capabilities while addressing issues reported by users, including: Language consistency: Reduced occurrences of
検証済みの公式情報の抜粋 · 英語DeepSeek-V3.1 Both deepseek-chat and deepseek-reasoner have been upgraded to DeepSeek-V3.1. deepseek-chat corresponds to DeepSeek-V3.1's non-thinking mode , while deepseek-reasoner corresponds to its thinking mode . Key updates in DeepSeek-V3.1: Hybrid reasoning architecture : A single model supports both thinking mode and non-thinking mode Improved reasoning efficiency : Compared to DeepSeek-R1
検証済みの公式情報の抜粋 · 英語deepseek-reasoner deepseek-reasoner Model Upgraded to DeepSeek-R1-0528: Enhanced Reasoning Capabilities Significant benchmark improvements (Pass@1) AIME 2025: 70.0 → 87.5 (+17.5) GPQA: 71.5 → 81.0 (+9.5) LCB_v6: 63.5 → 73.3 (+9.8) Aider: 57.0 → 71.6 (+14.6) Note: Complex reasoning tasks may consume more tokens compared to legacy R1 version. Optimized Front-end Development Generated web pages and
検証済みの公式情報の抜粋 · 英語deepseek-chat deepseek-chat Model Upgraded to DeepSeek-V3-0324: Enhanced Reasoning Capabilities Significant improvements in benchmark performance: MMLU-Pro: 75.9 → 81.2 (+5.3) GPQA: 59.1 → 68.4 (+9.3) AIME: 39.6 → 59.4 (+19.8) LiveCodeBench: 39.2 → 49.2 (+10.0) Optimized Front-End Web Development Improved accuracy in code generation More aesthetically pleasing web pages and game front-ends Upgra
検証済みの公式情報の抜粋 · 英語deepseek-reasoner deepseek-reasoner is our new model DeepSeek-R1. You can invoke DeepSeek-V3 by specifying model='deepseek-reasoner' . For details, please refer to: DeepSeek-R1 Release For guides, please refer to: Thinking Mode
検証済みの公式情報の抜粋 · 英語deepseek-chat The deepseek-chat model has been upgraded to DeepSeek-V3. The API remains unchanged. You can invoke DeepSeek-V3 by specifying model='deepseek-chat' . For details, please refer to: introducing DeepSeek-V3
検証済みの公式情報の抜粋 · 英語deepseek-chat The deepseek-chat model has been upgraded to DeepSeek-V2.5-1210 , with improvements across various capabilities. Relevant benchmarking results include: Mathematical: Performance on the MATH-500 benchmark has improved from 74.8% to 82.8% . Coding: Accuracy on the LiveCodebench (08.01 - 12.01) benchmark has increased from 29.2% to 34.38% . Writing and Reasoning: Corresponding improve
検証済みの公式情報の抜粋 · 英語deepseek-coder & deepseek-chat Upgraded to DeepSeek V2.5 Model The DeepSeek V2 Chat and DeepSeek Coder V2 models have been merged and upgraded into the new model, DeepSeek V2.5. For backward compatibility, API users can access the new model through either deepseek-coder or deepseek-chat . The new model significantly surpasses the previous versions in both general capabilities and code abilities.
検証済みの公式情報の抜粋 · 英語API Launches Context Caching on Disk Technology The DeepSeek API has innovatively adopted hard disk caching, reducing prices by another order of magnitude. For more details on the update, please refer to the documentation Context Caching is Available 2024/08/02 .
検証済みの公式情報の抜粋 · 英語New API Features Update API /chat/completions JSON Mode Function Calling Chat Prefix Completion（Beta） 8K max_tokens （Beta） New API /completions FIM Completion（Beta） For more details, please check the documentation New API Features 2024/07/25
検証済みの公式情報の抜粋 · 英語deepseek-coder The deepseek-coder model has been upgraded to DeepSeek-Coder-V2-0724.
検証済みの公式情報の抜粋 · 英語deepseek-chat The deepseek-chat model has been upgraded to DeepSeek-V2-0628. Model's reasoning capabilities have improved, as shown in relevant benchmarks: Coding: HumanEval Pass@1 79.88% -> 84.76% Mathematics: MATH ACC@1 55.02% -> 71.02% Reasoning: BBH 78.56% -> 83.40% In the Arena-Hard evaluation, the win rate against GPT-4-0314 increased from 41.6% to 68.3%. The model's role-playing capabilit
検証済みの公式情報の抜粋 · 英語deepseek-coder The deepseek-coder model has been upgraded to DeepSeek-Coder-V2-0614, significantly enhancing its coding capabilities. It has reached the level of GPT-4-Turbo-0409 in code generation, code understanding, code debugging, and code completion. Additionally, it possesses excellent mathematical and reasoning abilities, and its general capabilities are on par with DeepSeek-V2-0517.
検証済みの公式情報の抜粋 · 英語deepseek-chat The deepseek-chat model has been upgraded to DeepSeek-V2-0517. The model has seen a significant improvement in following instructions, with the IFEval Benchmark Prompt-Level accuracy jumping from 63.9% to 77.6%. Additionally, on API end, we have optimized model ability to follow instruction filled in the ``system" part. This optimization has significantly elevated the user experien
検証済みの公式情報の抜粋 · 英語