2026-09-19 the race moves from price-per-token to
cost-per-concurrent-agent — DeepSeek V4.1-Flash's new architecture
cuts GPU memory for agent sessions 75%, ~4× the concurrent
sessions per GPU (syndicated, ~12:05 PM ET). Architecture answers
to agent-memory economics, after the $0.003/M cached-input rate
(Sep 14). Rate card filled in from launch-coverage guides
(Dataconomy/apidog/eesel, consistent, not primary-verified):
V4.1-Flash = 552B MoE, natively multimodal, 1M context; input
$0.15 off-peak / $0.30 peak (cache-miss), $0.003/$0.006 (cache
hit), output $0.60/$1.20 — vs GLM Flash's $0.15/$0.50 list. Even
on uncached input, 50× cheaper on cache hits = the agent-workload
wedge. Self-hosting: not viable (3× Tesla P4, 24 GB VRAM) for either
Flash — both API-grade.
2026-09-15 DeepSeek answers — V4.1 Flash, cached input at
$0.003/M tokens off-peak (Forbes/Markman, pub Sep 14, in feed
8:01 PM ET): the cheapest cached-input rate on record and a price
shaped for agent memory (re-reading context) rather than chat. The
Flash-tier race is now capital-markets-funded on the Chinese side.