token-optimization

Tag

Cards List
#token-optimization

@simplifyinAI: Tencent just open-sourced Hy-Memory. A memory plugin that gives Al agents real long-term memory using a 6-layer framewo…

X AI KOLs Timeline · 2026-06-12 Cached

Tencent open-sourced Hy-Memory, a memory plugin for AI agents that provides long-term memory with a 6-layer dual-reasoning framework, reducing token usage by 35% and memory bloat by 70%.

0 favorites 0 likes
#token-optimization

Use context profiler to optimize your LLM calls and reduce token use

Reddit r/LocalLLaMA · 2026-06-12

ContextSpy is a local proxy tool that profiles how LLM applications use their context window, breaking down token usage by category to help developers optimize and reduce costs.

0 favorites 0 likes
#token-optimization

@avyvar: Token-maxxing is getting out of hand. Most AI apps send every request to the biggest model, even when a smaller model w…

X AI KOLs Following · 2026-06-11 Cached

The tweet criticizes AI apps for overusing large models and introduces Dari Router, a tool designed to route requests to appropriate model sizes for efficiency.

0 favorites 0 likes
#token-optimization

@_avichawla: I cut Fable 5 token usage 2.5x with just one change! - Before: 5.5 M tokens · 7 errors · $8.94 - After: 2.3 M tokens · …

X AI KOLs Timeline · 2026-06-10 Cached

The author reduced token usage for an AI agent by 2.5x by switching from Firebase to InsForge, an open-source backend platform for agentic coding, cutting tokens from 5.5M to 2.3M and eliminating manual interventions.

0 favorites 0 likes
#token-optimization

Token maxxing

Reddit r/singularity · 2026-06-06

Discusses strategies and techniques for maximizing token usage in large language models to improve efficiency and output quality.

0 favorites 0 likes
#token-optimization

n8n-style tool chains for AI agents – custom designed, or reinforced by what works

Reddit r/AI_Agents · 2026-06-05

This article suggests an approach inspired by ant colonies to optimize token usage and create efficient tool chains for AI agents, similar to n8n workflows.

0 favorites 0 likes
#token-optimization

@wsl8297: When running complex tasks with AI agents, the most painful thing is often not that the model isn't strong enough, but that as the conversation gets longer, the context starts to overflow. You have to keep filling in background details, re-explaining the process, plus the redundant logs from tool calls — tokens just gush out like a broken pipe. Recently, I saw TencentDB Agent Memory open-sourced by Tencent...

X AI KOLs Timeline · 2026-06-03 Cached

Tencent has open-sourced TencentDB Agent Memory, which solves the AI agent long-context overflow problem through hierarchical memory management (symbolic short-term memory + hierarchical long-term memory). Benchmarks show token consumption reduced by up to 61% and task success rate improved by over 50%.

0 favorites 0 likes
#token-optimization

AI agents are wasting tokens on repeated work. I built something to fix it and need testers.

Reddit r/AI_Agents · 2026-06-02

A developer built a system to reduce token waste in AI agent workflows by reusing information across tasks, and is seeking testers for feedback.

0 favorites 0 likes
#token-optimization

MeshFlow: production-safe multi-agent orchestration — SHA-256 audit chain, HIPAA/SOX/GDPR built in, 70-85% token cost reduction [Open Source][D]

Reddit r/MachineLearning · 2026-06-02

MeshFlow is an open-source framework for production-safe multi-agent orchestration with built-in HIPAA/SOX/GDPR compliance, a SHA-256 audit chain, token cost reduction of 70-85%, and durable execution, treating governance as infrastructure.

0 favorites 0 likes
#token-optimization

How I easily cut my input token burn ~90% on long agent runs

Reddit r/AI_Agents · 2026-06-01

The author shares a practical tip to reduce input token costs by ~90% on long agent runs using prompt caching: placing unchanged text (system prompt, tool definitions, context) at the start of every prompt to leverage cached prefixes from LLM providers.

0 favorites 0 likes
#token-optimization

I benchmarked when an email agent should wake up vs polling everything. 91% fewer downstream tokens on the first slice.

Reddit r/AI_Agents · 2026-05-25

Benchmarks an event-routing approach for email agents that wakes only on relevant triggers, reducing downstream token usage by 91% compared to polling.

0 favorites 0 likes
#token-optimization

Gemini 3.5 Flash (Low) (1 minute read)

TLDR AI · 2026-05-25 Cached

Google introduces Gemini 3.5 Flash (Low), a new model variant that uses about 45% fewer tokens than the Medium version while outperforming the older Gemini 3 Flash (High) on SWE tasks. They have also reset quotas for all paid plans.

0 favorites 0 likes
#token-optimization

@AYi_AInotes: https://x.com/AYi_AInotes/status/2058536443174158504

X AI KOLs Timeline · 2026-05-24 Cached

The author shares their three-year experience of feeding PDFs to AI, pointing out that Markdown is a better input format for AI than PDF, because PDF is essentially a mix of coordinates and characters. AI needs to parse the structure first, which is error-prone and consumes more tokens. The article provides specific cases and recommended tools (markitdown, pandoc, LlamaParse), and teases a new series called 'The Art of Feeding AI'.

0 favorites 0 likes
#token-optimization

@VincentLogic: AI coding assistants scan the entire project every time they modify code, and the token consumption breaks my heart. After installing CodeGraph, it no longer fumbles around like a headless fly using grep to search files. It first builds a local index graph, organizing function definitions, variable references, and call relationships. When AI needs to work, it directly queries…

X AI KOLs Timeline · 2026-05-23 Cached

CodeGraph reduces the number of times an AI coding assistant scans the entire project by building a local index graph, significantly lowering token consumption and improving speed, compatible with VS Code, Claude Code, and Cursor.

0 favorites 0 likes
#token-optimization

A comprehensive method to brutally reduce your Agentic AI token cost by at least 95%, aka a summary of current token reduction method

Reddit r/openclaw · 2026-05-19

This article presents a comprehensive guide to reduce token costs in Agentic AI systems by 95%, detailing seven core techniques including tree-structured document architecture, AI auto-compression, local model management, and script-to-API calls.

0 favorites 0 likes
#token-optimization

Process Rewards with Learned Reliability

arXiv cs.CL · 2026-05-18 Cached

BetaPRM is a process reward model that predicts both a step-level success probability and the reliability of that prediction using a Beta belief from Monte Carlo continuations, enabling adaptive computation allocation that reduces token usage by up to 33.57% while improving accuracy.

0 favorites 0 likes
#token-optimization

@DataChaz: STOP BURNING YOUR TOKENS! If you use Claude Code, you are probably wasting 80% of your context window. I found 10 ace t…

X AI KOLs Timeline · 2026-05-17 Cached

A tweet thread by @DataChaz lists 10 open-source tools to drastically reduce token usage in Claude Code and similar AI coding assistants, potentially cutting API bills by 75-98% through various optimizations.

0 favorites 0 likes
#token-optimization

@billtheinvestor: Give Claude Code and Codex infinite memory, programming efficiency improved by 92%! The Agentmemory tool has quickly gained 4000+ stars on GitHub and is completely free. It saves all information from your coding sessions through smart compression, and automatically extracts relevant context in future sessions, avoiding re...

X AI KOLs Timeline · 2026-05-17

Agentmemory is an open-source tool that provides infinite memory for Claude Code and Codex, reducing token usage through intelligent compression, improving programming efficiency, and has gained 4000+ stars on GitHub.

0 favorites 0 likes
#token-optimization

@levelsio: How do I tokenmax my Claude Code?

X AI KOLs Following · 2026-05-16 Cached

A tweet from @levelsio asking about tokenmaxing Claude Code, quoting Garry Tan's advice on using OpenClaw/Hermes + GBrain for a competitive AI advantage.

0 favorites 0 likes
#token-optimization

If you’re bleeding tokens on data grids, here is a Skill that 10x’d my dev speed and cut my token usage by 85%!

Reddit r/AI_Agents · 2026-05-14

LyteNyte Grid AI Skills is a free open-source tool that leverages a declarative, stateless architecture to help AI agents build data grids efficiently, cutting token usage by 85% and boosting developer speed.

0 favorites 0 likes
Next →
← Back to home

Submit Feedback