Alem (Easy): leaderboard

Alem (2026) tests open-ended multi-agent coordination: a team of LLM agents shares a Craftax-like survival and crafting world with procedurally generated tasks that need synchronised action, handovers and communication. This board is the easy difficulty, scored by the team total return as a percent of the maximum achievable reward; higher is better.

Metric: Total return (%): each agent's cumulative reward divided by the maximum achievable total reward (376) and averaged across agents on the Easy difficulty, zero-shot homogeneous team (every agent driven by the same LLM) in alem, a JAX Craftax-like open-ended multi-agent world with procedurally generated coordination tasks (synchronous, all-agent and handover) and soft role specialisation; text interface with the rules, local observation and legal actions each step, scratchpad memory, broadcast communication and the last eight observations; reasoning enabled where available, proprietary models at high reasoning; mean over 20 seeds (10 for the API models); higher is better. Source: arxiv.org. Saturation forecast: Around June 2028. 13 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3.1 Pro (Preview) (High)18.1#94 (Gemini 3.1 Pro (Preview))
2GPT-5.4 (High)11.1#123 (GPT-5.4)
3Gemma 4 31B (IT) (Thinking)9.2#342 (Gemma 4 31B (IT))
4Qwen 3.5 122B A10B6.6#331
5Qwen 3.5 27B5.7#359
6gemma-4-26B-A4B-it (Thinking)5.6
7Qwen 3.6 27B4.9#341
8Qwen 3.5 9B4.6#803
9Qwen 3.6 35B A3B3.5#462
10Gemma 4 E4B (IT) (Thinking)3.3
11Llama 3.3 70B Instruct3.1#1357
12Qwen 3.5 35B A3B2.9#482
13Llama 3.1 8B Instruct0.8#4246

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=alem-easy · How It Works · Data refreshed daily, snapshot 2026-11-13.