token-cost

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#token-cost

@a1zhang: Good harness designs can get around extreme token costs when information is structured. There's really no need to feed …

X AI KOLs Following · 2026-06-15 Cached

A discussion on how harness designs can reduce token costs by structuring information instead of feeding everything into a language model's context, citing an example of an RLM agent processing many lines of logs with few active tokens.

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#token-cost

Try this tool to reduce Claude costs by changing Effort/Thinking parameters based on prompt complexity

Reddit r/openclaw · 2026-05-31

A GitHub tool that reduces Claude API costs by dynamically adjusting effort/thinking parameters based on prompt complexity.

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#token-cost

@vintcessun: Actually, large language models' context windows are getting larger and larger, but costs are also skyrocketing. This paper simply treats context management as a deployment optimization problem and develops a unified framework called Efficiency Frontier. Simply put, they no longer look at performance or cost separately, but jointly model task performance, token overhead, and preprocessing reuse...

X AI KOLs Timeline · 2026-05-26 Cached

This paper proposes a unified framework called Efficiency Frontier, which treats large model context management as a deployment optimization problem, jointly modeling task performance, token overhead, and preprocessing reuse. On 5,000 HotpotQA instances, deployment optimization saves 25% of token usage, while memory compression is more than half the cost of full context in high-precision scenarios.

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#token-cost

@nateherk: https://x.com/nateherk/status/2057450555212013627

X AI KOLs Timeline · 2026-05-21 Cached

A practical guide explaining how prompt caching works in Claude Code, how it reduces token costs by 90%, and common habits that break the cache, helping developers extend session length and reduce costs.

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#token-cost

OpenSquilla launches open-source AI agent to cut token costs (4 minute read)

TLDR AI · 2026-05-15 Cached

OpenSquilla has launched an open-source AI agent runtime designed to reduce token costs through intelligent routing, caching, and a four-tier memory architecture, claiming 60-80% cost savings.

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