Agent Memory Leaderboard

Agent Memory Leaderboard

Agent Memory Leaderboard is an open public benchmark and evaluation platform for comparing agent memory systems (textual and coding) under a unified Add/Search evaluation flow, offering public leaderboards, an API contract, and tooling for academic and commercial submissions.

Agent Memory Leaderboard is ai agents software teams evaluate for education & research. Use this page to review pricing, integration signals, and the best alternatives before you commit.

Free API
#439 in AI Agents (439 tools)
Just launched
Data reviewed Aug 14, 2026

Profile facts come from the vendor source. AiMatch labels unknown pricing or API details instead of estimating them.

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Quick Overview

Best for: Education & Research

What it does

AI Agents software for decision-makers comparing workflow fit and alternatives.

Best fit

Education & Research

Pricing snapshot

Free from Free

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Agent Memory Leaderboard

Agent Memory Leaderboard is a public benchmark space for evaluating and ranking agent memory systems focused on textual and coding memory. It uses a unified end-to-end flow where participants provide Add and Search endpoints (or code for platform deployment) while the platform runs Answer, Eval, auditing, and public leaderboard publication. The platform locks the answering model, prompts, scoring rules, dataset bundles, Top K and aggregation to make leaderboard scores reflect the memory subsystem itself. The offering is aimed at researchers, open-source maintainers and commercial product teams and supports both hosted API and code-submission evaluation routes.

面向开发者、研究团队与商业公司的智能体长期记忆系统公开评测。统一 Add / Search 协议,由平台统一执行 Answer 与 Eval。

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Key Features

Public Leaderboard

Public ranking pages separated by track (Textual, Coding, Multimodal) with filterable tables, metric breakdowns, and public submission records.

Unified Add/Search Evaluation Flow

A standardized synchronous Add and Search API contract that participants must implement; the platform calls Add by sample and Search per question and preserves the response order and Top K semantics.

Evaluation Modes (smoke & full)

Separate compatibility smoke endpoint for integration checks (private) and a full formal evaluation mode (queued, audited, and eligible for public leaderboard).

Multiple Participation Routes

Support for hosted API submissions (participants host Add/Search and receive an Eval Key) and code submissions (public GitHub + Docker for platform deployment).

Detailed API Contract & Error Handling

A fixed Add/Search schema, success semantics (synchronous HTTP 200 with success=true), Top K limits, health checks, authentication schemes, and bounded retry/error behaviors.

Reproducibility & Auditability

Platform retains request/response evidence, timing, errors, and dataset/pipeline hashes for review; submissions must disclose original work and changes for repro and review.

Participation & Rewards Program

First-cycle challenge with deadlines, reward tiers for academic entries (ChatGPT Pro/Plus months) and a community contribution plan (Kimi Token), plus public/academic/commercial boards.

Pricing

Free Tier Available

Participation in the evaluation/challenge is free; participants are responsible for their own hosting costs.

Free Participation

Free
  • Submission to the challenge is free of charge
  • Participants cover their own API, database, bandwidth, and compute costs; the platform covers Answer/Eval orchestration

Use Cases

Academic method benchmarking

Researchers submit open GitHub repositories or hosted APIs to evaluate memory architectures on textual or coding benchmarks and appear on the Academic Methods board.

Commercial product evaluation

Product teams submit stable product API versions (without opening source) to be evaluated and ranked on the Commercial Products board.

Regression and integration testing

Teams can run private smoke tests and repeated eval runs to verify Add/Search compatibility and ensure stable behavior before public submission.

Reproducible comparison of memory systems

Compare different Add/Search implementations under a locked answering/scoring pipeline to isolate memory subsystem capabilities.

Integrations

Add/Search API

Synchronous HTTP(S) Add and Search endpoints (Token, Bearer, or X-Api-Key auth) that the platform calls for ingestion and retrieval.

GitHub / Docker

Code-submission integration where participants provide a public GitHub repo and Docker startup command for platform deployment and evaluation.

Platform Answer/Eval pipeline

Participant systems integrate with the platform's answer-generation and scoring pipelines via the declared contract to produce reproducible results.

Benefits

Standardized, reproducible evaluation that isolates memory system behavior by locking answer models, prompts, and scoring.
Public visibility via leaderboards for both academic and commercial submissions.
Clear, machine-readable Add/Search API contract with error handling and health checks to ease integration.
Support for both hosted APIs and platform-deployed Docker submissions, enabling flexible participation paths.
Audit trails and publication gates that enforce disclosure, originality, and anti-manipulation safeguards.

Limitations

Hosted endpoints must remain publicly reachable and stable for at least 30 days after submission to qualify for public leaderboard publication.
The platform only evaluates the Add/Search interface: answer models, scoring, Top K, and aggregation are fixed by the platform and cannot be changed by participants (scores reflect memory subsystem behavior only).

Frequently Asked Questions

Is participation paid or free?
Participation is free; participants cover their own API, database, bandwidth and compute costs while the platform covers unified Answer/Eval orchestration.
What is the difference between an Eval Key and a Memory System Key?
Eval Key is issued by the Agent Memory Leaderboard to verify participant access, start evaluations, and view private results (issued to hosted API submitters). Memory System Key is provided by the participant for the platform to call their Add/Search API (required when the submitted API uses authentication).
What counts as a valid submission?
A valid submission requires complete and verifiable materials, a passing smoke test, successful completion of the full evaluation with the declared version, and passing the platform review for publication.

Getting Started

  1. 1 Step 1: Choose an evaluation route — hosted Add/Search API (receive Eval Key) or code submission (public GitHub + Docker).
  2. 2 Step 2: Implement the synchronous Add/Search contract and verify endpoint reachability and health as described in the API Guide.
  3. 3 Step 3: Run a smoke test using the issued Eval Key to validate synchronous Add → Search → Answer → Evaluate flow, then submit a full evaluation when ready.

Support

email

Participation and evaluation questions can be sent to [email protected].

docs

User Documentation and API Guide available on the Agent Memory Leaderboard site (see the Evaluation / API Guide pages).

social

Official channels include an official WeChat account and X/Twitter handle @AgentMemoryL for releases and announcements.

API

Available: Yes
Documentation:

API Guide and user documentation available from the Agent Memory Leaderboard site (see the Evaluation / API Guide pages).

Rate Limits:

Standard quotas: smoke mode roughly 1 per hour; full mode roughly 1 every 3 months; platform-specified concurrency and Top K limits apply (Top K = 100 for formal evaluations).

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