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// 55m agoMODEL RELEASE
DeepSeek-V4.1-Flash drops with 552B MoE
DeepSeek’s new 552B-parameter MoE model targets coding and agentic workflows with native multimodal support, a one-million-token context window, and only 8B–16B active parameters. Its reported scores include 74.2 on DeepSWE v1.1 and 88.1 on CyberGym.
// ANALYSIS
DeepSeek is making model size less relevant to deployment economics: V4.1-Flash pairs frontier-scale capacity with unusually low active compute and a compressed KV cache.
- –DeepSWE v1.1 edges Claude Opus 5 and GPT-5.6 Sol in DeepSeek’s published comparison.
- –CyberGym’s 88.1 score is especially notable for security-oriented coding agents.
- –The asymmetric 8B prefill, 16B decode design should improve throughput and inference costs.
- –A one-million-token context window makes the model practical for large repositories and long-running agents.
- –Developers should validate the self-reported benchmarks under their own scaffolds before treating it as a universal frontier-model replacement.
// TAGS
deepseek-v4.1-flashllmmoeai-codingcoding-agentmultimodallong-context
DISCOVERED
55m ago
2026-09-11
PUBLISHED
1h ago
2026-09-11
RELEVANCE
10/ 10
AUTHOR
cutetoxicguy
