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@NVIDIAAI: Most agentic stacks run into the same problems pretty quickly: reasoning and tool parsing drift across turns, KV cache reuse falls apart, or...

@NVIDIAAI 3 信息等级 3 1 噪音/剔除;2 较弱;3 普通事实;4 重要行业动态;5 极重大事件。该分数是信息显著性,不是投资建议。 发布:2026-05-08T19:36 抓取:2026-05-09 04:02
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摘要

NVIDIA通过Dynamo强化harness路径,支持Claude Code、OpenClaw和OpenAI Codex等agent模式,实现稳定提示词、交错推理与工具调用、流式工具调度等改进。

客观事实
  • NVIDIA Dynamo强化harness路径以支持agent模式
  • 改进包括流式工具调度和交错推理
  • 针对Claude Code、OpenClaw、OpenAI Codex等工具
NVIDIA Dynamo Claude AI OpenClaw OpenAI Codex

原文

Most agentic stacks run into the same problems pretty quickly: reasoning and tool parsing drift across turns, KV cache reuse falls apart, or tools fire too late.

We’ve been hardening Dynamo’s harness-facing path so @Claudeai Code, @OpenClaw, and @openai Codex-style agent patterns behave reliably on custom stacks and inference endpoints:

• Stable prompts for KV reuse and lower TTFT
• Interleaved reasoning + tool calls preserved across turns
• Streaming tool dispatch instead of end-of-turn buffering
• Harness behavior aligned with real multi-turn agent runtimes

If you’re building your own agent stack or serving endpoint, this blog goes through the infrastructure issues that tend to show up in practice and the patterns we’ve been using to fix them.

Tech blog ➡️https://t.co/dCWgk4OmyL

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