EvolMem - Learning: leaderboard
Long-context LLM backbones on multi-session conversational memory, paper v1 Table 2. Seven memory abilities are scored independently; the memory-system ablation table is a separate protocol. Mistral-Large has no pinned endpoint in the paper or released evaluator and retains an explicitly unspecified identity. This series reports Learning (%). Source: https://arxiv.org/html/2601.03543v1.
Metric: Learning (%). Source: arxiv.org. Saturation forecast: Around February 2027. 7 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | MiniMax-M2 | 51.35 | #327 |
| 2 | DeepSeek V3.2 | 50.96 | #210 |
| 3 | GPT-5.1 | 50.86 | #145 |
| 4 | Gemini 3 Pro | 47.37 | #82 |
| 5 | Kimi K2 | 44.46 | #252 |
| 6 | Llama 4 Maverick | 25.01 | #486 |
No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.
Interactive version: theaggregate.ai/benchmark?slug=evolmem-learning · How It Works · Data refreshed daily, snapshot 2026-11-05.