DeepSeek
@deepseek_ai
Unravel the mystery of AGI with curiosity. Answer the essential question with long-termism.
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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!
The DeepSeek-V4-Pro discount has been extended until May 31, 2026, 15:59 UTC!
🔥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-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:
Show more
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.
3/n
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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:
1/n
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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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