@jakevin7: DeepSeek Flash is indeed powerful—come feel this long-horizon capability. Agentic abilities are now far stronger. It even discovered the agent swarm tool call in the harness on its own and handled the splitting and orchestration well. This wasn't in the prompt; it discovered it by itself…
Summary
The author praises DeepSeek Flash's greatly enhanced long-horizon and agentic abilities, which can automatically discover and combine subagent swarm tool calls in the harness.
View Cached Full Text
Cached at: 07/31/26, 10:49 AM
DeepSeek Flash is genuinely impressive — check out this long-horizon capability. The agentic abilities are so much stronger now.
It even discovered the agent swarm tool calls in the harness on its own, and handled the splitting and orchestration properly. None of this was in the prompt — it discovered and combined the subagent swarm pattern by itself.
When I tested Flash before, it was too dumb. Forget about splitting and orchestrating complex tool chains — even plain tool calls were error-prone.
The screenshot is DeepSeek + maka, https://github.com/maka-agent
Similar Articles
@jakevin7: Using Maka to fetch your own context in the WeChat group / Maka Builder is truly powerful. Maka + DeepSeek Flash is really great. Especially Maka's swarm mode — it feels amazing. https://github.com/maka-ag…
The author shares on Twitter their experience using Maka combined with DeepSeek Flash, saying its swarm mode is very useful; the attached GitHub README describes Maka as a local-first Agent workspace that supports desktop, TUI, CLI, and headless operation, with capabilities such as event logging, tool calling, and persistent tasks.
@LinearUncle: Liang Ge's DeepSeek V4 series is really easy to use; the cheap, high-volume, satisfying Flash can restore a TypeScript-written agent to the source code level. I used this skill from a Twitter friend and no other techniques.
Recommend the DeepSeek V4 model paired with the reverse-skill tool, which can restore TypeScript-written AI agents to the source code level for cybersecurity reverse engineering.
@jakevin7: Maka's Harness project brings DeepSeek Flash's test set results close to GLM-5.2 level ----------------------------------- maka + DeepSeek Flash V4, te…
Maka's Harness project improved the self-check mechanism, enabling DeepSeek Flash V4 to achieve evaluation results close to GLM-5.2 on the terminal-bench sample set, completing 10 programming agent tasks with only 4 RMB and a 97.5% cache hit rate.
DeepSeek-V4-Flash-0731
DeepSeek announces DeepSeek-V4-Flash-0731, a frontier agent intelligence model positioned as offering advanced capabilities at Flash-level pricing.
DeepSeek v4 Flash has a nice bump in Capability
DeepSeek V4 Flash shows significant benchmark gains in preview updates, trading blows with GPT-5.6 Terra on agentic coding tasks.