Uploaded September 2026 | Updated September 2026, 3 hours ago
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Deepseek-V4.1-Flash tech report: huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash/blob/main/DeepSeek_V41_Tech_Report.pdf?fbclid=IwY2xjawUPu9VwZG9mA2V4dG4DYWVtAjExAHNydGMGYXBwX2lkATAAAR5ZIQ8DYGcBBTCpNihWDOEibcCkNerVHRv5HPbtV56YflMjzP1LS4p9Wxfe7w_aem_rfnVBAxmIPNX12ZEIy2WRQ
Model weights: huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash
API release and migration notice: api-docs.deepseek.com/news/news260910
Reasoning settings: api-docs.deepseek.com/guides/thinking_mode
Our Context Engineering workshop at @aiDotEngineer : youtu.be/WP3hjUXd918
How to start in AI/ML - A Complete Guide:
►louisbouchard.ai/learnai
Become a member of the YouTube community, support my work and get a cool Discord role :
youtube.com/channel/UCUzGQrN-lyyc0BWTYoJM_Sg/join
DeepSeek V4.1 Flash review for AI engineers: what changed over V4 Flash, how its causal encoder-decoder architecture and CSA2 reduce KV cache memory, and what our writing benchmark says about cost, quality, and high versus max effort. I walk through the paper’s results and limits before sharing where I’d use this open-weight model.
Writing results shown are from our September 10, 2026 snapshot: 148 configurations, 10 tasks, 5 drafts per configuration per task, and 3 blind model judges. We’ll share more about the benchmark soon.
Cache figures refer to global or persistent KV state as labeled. Writing costs are token-based averages for the tested routes and rates; Claude Code costs use API-equivalent accounting. Results and timing depend on the task and provider.
Chapters:
00:00 - Introduction: DeepSeek Flash V4.1
02:04 - Why KV Cache Matters for Agent Costs
03:23 - DeepSeek V4.1 Flash Overview & Specs
04:50 - Optimization 1: Split Architecture & Causal Encoder
06:04 - Optimization 2: Compressed Sparse Attention (CSA2)
07:53 - Optimization 3: Deployment & Cache Replay
09:25 - Performance, Benchmarks & Agentic Tasks
10:31 - The Reasoning Effort Dial
10:56 - Writing Benchmark Results
13:11 - Final Takeaways & Upcoming Book Announcement
#llm #deepseek #deepseekflash
Sign up for updates on our NEW AI engineering book: louisbouchard.ai/book/?utm_source=yt-lf&utm_medium=video&utm_campaign=book
Deepseek-V4.1-Flash tech report: huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash/blob/main/DeepSeek_V41_Tech_Report.pdf?fbclid=IwY2xjawUPu9VwZG9mA2V4dG4DYWVtAjExAHNydGMGYXBwX2lkATAAAR5ZIQ8DYGcBBTCpNihWDOEibcCkNerVHRv5HPbtV56YflMjzP1LS4p9Wxfe7w_aem_rfnVBAxmIPNX12ZEIy2WRQ
Model weights: huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash
API release and migration notice: api-docs.deepseek.com/news/news260910
Reasoning settings: api-docs.deepseek.com/guides/thinking_mode
Our Context Engineering workshop at @aiDotEngineer : youtu.be/WP3hjUXd918
How to start in AI/ML - A Complete Guide:
►louisbouchard.ai/learnai
Become a member of the YouTube community, support my work and get a cool Discord role :
youtube.com/channel/UCUzGQrN-lyyc0BWTYoJM_Sg/join
DeepSeek V4.1 Flash review for AI engineers: what changed over V4 Flash, how its causal encoder-decoder architecture and CSA2 reduce KV cache memory, and what our writing benchmark says about cost, quality, and high versus max effort. I walk through the paper’s results and limits before sharing where I’d use this open-weight model.
Writing results shown are from our September 10, 2026 snapshot: 148 configurations, 10 tasks, 5 drafts per configuration per task, and 3 blind model judges. We’ll share more about the benchmark soon.
Cache figures refer to global or persistent KV state as labeled. Writing costs are token-based averages for the tested routes and rates; Claude Code costs use API-equivalent accounting. Results and timing depend on the task and provider.
Chapters:
00:00 - Introduction: DeepSeek Flash V4.1
02:04 - Why KV Cache Matters for Agent Costs
03:23 - DeepSeek V4.1 Flash Overview & Specs
04:50 - Optimization 1: Split Architecture & Causal Encoder
06:04 - Optimization 2: Compressed Sparse Attention (CSA2)
07:53 - Optimization 3: Deployment & Cache Replay
09:25 - Performance, Benchmarks & Agentic Tasks
10:31 - The Reasoning Effort Dial
10:56 - Writing Benchmark Results
13:11 - Final Takeaways & Upcoming Book Announcement
#llm #deepseek #deepseekflash
