DeepSeek
@deepseek_ai
Unravel the mystery of AGI with curiosity. Answer the essential question with long-termism.
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🌐 Supporting open source. Expanding deployment options.
We’ll work closely with the open-source community on V4.1-Flash inference support and explore more deployment options.
Planning a large-scale deployment with 2,000 GPUs + a storage cluster? Let’s talk.
🔹 Model:
🔹 Paper:
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⚡ V4.1-Flash is now live on the DeepSeek API with native multimodal support.
Set your model to deepseek-flash.
🔹 V4-Flash & V4-Flash-Vision-Exp are retired. For compatibility, deepseek-v4-flash and deepseek-v4-flash-vision-exp temporarily route to V4.1-Flash.
🔹 Tests by multiple parties put V4.1-Flash ahead of V4-Pro on performance, cost, speed & total runtime. We’re phasing out V4-Pro.
🔹 Starting at 04:00 UTC on Sept 14, 2026, all deepseek-v4-pro requests will route to V4.1-Flash at V4.1-Flash rates. This will continue until V4.1-Pro launches.
🤝 Official partners @WorkBuddy_AI (including Codebuddy) & @opencode now fully support V4.1-Flash. Try it today!
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💾 Smaller KV cache. Bigger savings.
Compared with the previous generation, V4.1-Flash’s KV cache needs just:
🔹 1/4 the HBM
🔹 1/8 the SSD storage
Cache-hit charges often account for a large share of agent costs. Compressing the cache cuts those costs significantly.
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🧠 Asymmetric architecture. More intelligence, less cost.
🔹 552B-parameter MoE.
🔹 New Causal Encoder–Decoder architecture: just 8B active parameters for input, 16B for output.
🔹 New pre-training methods + larger-scale RL post-training deliver benchmark results ahead of flagship models, including DeepSeek-V4-Pro.
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🚀 Introducing DeepSeek-V4.1-Flash: smarter, faster, more efficient.
🔹 Introducing the smallest model in our new architecture family, with native visual understanding.
🔹 Designed for greater capability, faster inference, higher throughput, and scaling to larger models.
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Multimodal API support 🔌
🔹 Set model='deepseek-v4-flash-vision-exp'
🔹 Images are tokenized for billing: up to 384 tokens each, at V4-Flash pricing
🔹 Supports Chat Completions, Messages & Responses
🔹 Supports mixed text + image input; images can be provided via base64, external URLs, or the Files API.
Docs:
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Multimodality unlocks more agent use cases. 👀
V4-Flash-Vision-Exp works smoothly across agent frameworks, combining visual understanding with a wide range of tools to unlock more practical workflows.
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DeepSeek-V4-Flash-Vision-Exp is now live on the DeepSeek API Platform! 🚀
🔹 This experimental multimodal model matches DeepSeek-V4-Flash on text capabilities—including agents, reasoning, and world knowledge.
🔹 On multimodal agent benchmarks, V4-Flash-Vision-Exp makes a major leap over V4-Flash, bringing multimodal agent performance close to Opus-4.8.
Try it with model='deepseek-v4-flash-vision-exp'. DeepSeek Harness 0.1.1 was released today with out-of-the-box support for the new model.
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🧩 DeepSeek Harness v0.1 is now available in Developer Preview!
🔹 We’re opening it up to developers building agent harnesses worldwide and open-sourcing the codebase in MIT license.
🔹 Powered by the Cordis meta-framework, DeepSeek Harness is an agent harness built around one core idea: Everything is a plugin. Models, tools, skills, sessions, sandboxes, filesystems, loops, orchestration, and UI are ALL implemented as plugins, and can be mixed, matched, replaced, and extended.
Try it now!
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We’re launching DeepSeek-V4-Pro today! 🚀
🔷 Major Agent upgrades with strong production gains!
🔷 Flexible reasoning effort for V4-Pro & V4-Flash: low for simple tasks, high for daily Agent workflows, max for complex tasks.
🔷 Native OpenAI Responses API support, optimized for Codex with one-click setup.
V4 Pro is now available on app/web. Try it via “Expert Mode”.
V4 Pro is also available via API. Model names remain unchanged—please refer to the API docs for setup details.
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🚀 DeepSeek-V4-Flash Official API is now LIVE in public beta!
🔷 We’ve massively upgraded its Agent capabilities—benchmark scores are now far surpassing the V4-Pro-Preview. Check out the massive performance leap below! 👇
🔷 The official V4-Flash now natively supports the Responses API format and is fully adapted for Codex!
Check out the configuration details in our official API docs:
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We are making our discount permanent! 🎉
Enjoy building with DeepSeek-V4-Pro and bring your innovative ideas to life! 🚀
The DeepSeek-V4-Pro discount has been extended until May 31, 2026, 15:59 UTC!
🔥DeepSeek Input Cache Price Drop!
Effective immediately, the price for input cache hits across the ENTIRE DeepSeek API series is reduced to just 1/10th of the original price! Build more efficiently for less.
📌Reminder: The DeepSeek-V4-Pro 75% OFF promotion is still active until May 5th, 2026, 15:59 (UTC Time).
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🔥DeepSeek-V4-Pro API is 75% OFF until May 5th, 2026, 15:59 (UTC Time)! Don't miss out on this massive discount.
🛠️Integration Updates:
🔹Claude Code: Set model to deepseek-v4-pro[1m] to unlock 1M context!
🔹OpenCode: Update to v1.14.24+
🔹OpenClaw: Update to v2026.4.24+
Check the latest official API docs for full details:
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DeepSeek-V4-Flash
🔹 Reasoning capabilities closely approach V4-Pro.
🔹 Performs on par with V4-Pro on simple Agent tasks.
🔹 Smaller parameter size, faster response times, and highly cost-effective API pricing.
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🚀 DeepSeek-V4 Preview is officially live & open-sourced! Welcome to the era of cost-effective 1M context length.
🔹 DeepSeek-V4-Pro: 1.6T total / 49B active params. Performance rivaling the world's top closed-source models.
🔹 DeepSeek-V4-Flash: 284B total / 13B active params. Your fast, efficient, and economical choice.
Try it now at via Expert Mode / Instant Mode. API is updated & available today!
📄 Tech Report:
🤗 Open Weights:
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🚀 Launching DeepSeek-V3.2 & DeepSeek-V3.2-Speciale — Reasoning-first models built for agents!
🔹 DeepSeek-V3.2: Official successor to V3.2-Exp. Now live on App, Web & API.
🔹 DeepSeek-V3.2-Speciale: Pushing the boundaries of reasoning capabilities. API-only for now.
📄 Tech report:
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⚠️ Heads-up to anyone using the DeepSeek-V3.2-Exp inference demo: earlier versions had a RoPE implementation mismatch in the indexer module that could degrade performance. Indexer RoPE expects non-interleaved input, MLA RoPE expects interleaved. Fixed in
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🚀 Introducing DeepSeek-V3.2-Exp — our latest experimental model!
✨ Built on V3.1-Terminus, it debuts DeepSeek Sparse Attention(DSA) for faster, more efficient training & inference on long context.
👉 Now live on App, Web, and API.
💰 API prices cut by 50%+!
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