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agentic-kv-cache

Reproducing agentic KV-cache policy claims on real traces. 68k requests from 393 Claude Code sessions. LRU is harder to beat than the papers suggest.

Details

External ID
1363812952
Source
GITHUB
Company
—
Product
agentic-kv-cache
Website domain
github.com
Launched
Sept. 10, 2026
Cohort
—
Upvotes
22
Upvotes percentile
0.6369459390212657
Tags
kv-cache, llm-agents, llm-inference, prefix-caching, reproducibility, sglang, vllm
Fetched at
Sept. 14, 2026, 5:28 p.m.
Updated at
Sept. 14, 2026, 5:28 p.m.

Enrichment

Theme
low-level systems and developer tools
Vertical
Horizontal
Function
Observability & eval
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
kv-cache benchmark for llm agents
Manually corrected
False

Could you build this?

No This is an advanced systems research benchmark measuring KV-cache eviction policies using extensive real-world execution traces across complex LLM context windows.

What it would actually take: Requires building an accurate discrete-event KV-cache memory simulator replicating vLLM/PagedAttention internals, prefix caching trees, and hardware memory tiering. It requires specialized expertise in LLM serving memory hierarchies and access to large proprietary token/session traces from real production agents to benchmark eviction policies.

Competitors

Other products that read as similar to this one — 608 launches clear the similarity bar, closest 8 shown.

Attention rank: #178 of 609 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 314 days after the earliest competitor.

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