H2O
Heavy-hitter oracle for efficient generative inference. NeurIPS 2023.
Active · Verified 2026-10-28 · fresh as of 2026-10-28 · 22 cited facts, 0 with a third-party source · Suggest a correction
At a glance
- Type
- Heavy-hitter oracle KV eviction paper fix
- Tier
- T3
- Latest release
- not applicable — not OSS fix
- License
- not applicable — not OSS fix
- GitHub
- not applicable — no GitHub repo fix
- Pricing
- not applicable — not commercial fix
- Funding
- not applicable — not commercial fix
- Freshness
- 2026-10-28 fix
- Layer
- agent-infra repo fix
Memory taxonomy
- storage
- kv-cache
- retrieval
- attention
- persistence
- session
- update
- evict-oldest
- unit
- kv-token
- governance
- deterministic
- conflict
- n/a
When to use
Optimised for: not applicable - research paper
Anti-fit: not applicable - research paper
Pros & cons
Pros
Heavy-hitter oracle KV eviction — keeps tokens with high attention scores, evicts the rest; NeurIPS 2023.
Cons
Heavy-hitter heuristic can miss tokens that become important later; eviction is irreversible.
Claims & capabilities
Heavy-Hitter Oracle for KV-cache eviction balancing recent and high-impact tokens. Headline: up to 29x throughput on OPT-6.7B/OPT-30B with 20% heavy hitters retained, 1.9x latency reduction; baselines: DeepSpeed Zero-Inference, Hugging Face Accelerate, FlexGen; primary datasets: OPT/LLaMA/GPT-NeoX evaluated on HELM and lm-eval-harness (COPA, MathQA, OpenBookQA, PiQA, RTE, Winogrande, XSUM, CNN/Daily Mail), AlpacaEval, MT-Bench.
Technical surface
- API surface
- not applicable — research paper
- Backend storage
- not applicable — research paper
- Deployment
- not applicable — not a deployable product
- Embedding model
- not applicable — research paper
- Multi-tenancy
- not applicable — research paper
- MCP
- not applicable — research paper, no deployed product
- A2A
- not applicable — research paper, no deployed product
- OpenTelemetry
- not applicable — research paper, no deployed product
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- MemoryBank T3
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- Reflexion T3
Language agents with verbal reinforcement learning.
Sources (21 cited facts, 0 third-party)
Each fact links to the page it came from; the badge says who published it (how to read sources).
- What it is Heavy-hitter oracle KV eviction paper
- What it does & what's distinct Heavy-hitter oracle for efficient generative inference. NeurIPS 2023. paper
- Claims / benefits Heavy-Hitter Oracle for KV-cache eviction balancing recent and high-impact tokens. Headl… paper
- Modalities text paper
- Created 2023-06-24 (arxiv 2306.14048 submitted June 24 2023; NeurIPS 2023) paper
- Mindshare 654 cites · 19.0/mo · 516* / 80 forks · 92 influential SS cites paper
- Founders / pedigree no data — no URL in landscape HTML; searched NeurIPS 2023 H2O heavy-hitter oracle paper
- Memory volume / scale no scale claim — research (NeurIPS 2023) paper
- Performance 29x OPT-6.7B/30B throughput (20% heavy hitters) 1.9x latency reduction paper
- Reproducibility Independently reproduced: integrated into vLLM and HuggingFace transformers; widely cite… repo
- Code/weights release Code public + weights closed — https://github.com/FMInference/H2O · stale (last commit 2… repo
- Consistency strong paper
- Versioning none paper
- Tombstoning hard-delete supported paper
- Schema evolution schema locked paper
- Forgetting policy LRU eviction paper
- Pros Heavy-hitter oracle KV eviction — keeps tokens with high attention scores, evicts the re… paper
- Cons Heavy-hitter heuristic can miss tokens that become important later; eviction is irrevers… paper
- Project & sources NeurIPS 2023 paper
- citation-trajectory [{"year":2024,"cum":7,"infl":1},{"year":2025,"cum":11,"infl":1}] paper
- taxonomy-three-layer-rollup agent-infra repo
Related systems
Referenced by (1)
- NAMMs cites — S2 isInfluential citation