General Agents Benchmark

LiveClaw

Agentic benchmark reported on the LFM2.5-24B-A2B model card for live agent workflows. As evaluated: vLLM with temperature = 1.0 (vLLM default; the agent sets no temperature), max output tokens = 8192.

Category

General Agents

Score type

percent

Scale

100%

higher is better

Models tested

1

What is LiveClaw?

LiveClaw is a benchmark for how well a model acts as a general-purpose agent. The official description says: "Agentic benchmark reported on the LFM2.5-24B-A2B model card for live agent workflows". Below we describe in simple words what benchmarks of this type generally examine.

What does it test?

LiveClaw measures how well a model acts as a general-purpose agent. In detail, it checks:

  • solving long, multi-step tasks with many intermediate decisions
  • using tools correctly (browsers, terminals, APIs, calendars, other apps)
  • adapting when something unexpected happens mid-task
  • staying on goal over long task horizons instead of wandering off

How to read the score

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.

Official methodology note: Agentic benchmark reported on the LFM2.5-24B-A2B model card for live agent workflows. As evaluated: vLLM with temperature = 1.0 (vLLM default; the agent sets no temperature), max output tokens = 8192.

Frequently asked questions

What is the LiveClaw benchmark?

LiveClaw is a benchmark for how well a model acts as a general-purpose agent. The official description says: 'Agentic benchmark reported on the LFM2.5-24B-A2B model card for live agent workflows'. Below we describe in simple words what benchmarks of this type generally examine.

What does LiveClaw test?

LiveClaw mainly measures how well a model acts as a general-purpose agent. Concretely, it checks: solving long, multi-step tasks with many intermediate decisions; using tools correctly (browsers, terminals, APIs, calendars, other apps); adapting when something unexpected happens mid-task.

How is the LiveClaw score calculated?

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.

Where do I get LiveClaw data and scores?

The official source is https://huggingface.co/LiquidAI/LFM2.5-24B-A2B. The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/liveclaw/scores) or pull it directly from the Open LLM Radar API with any HTTP client.

Model scores 1 model tested

Reset
# Model Score Date Source Verified
1 LFM2.5-24B-A2B
LiquidAI
48.09%
13.10.2026 Report Verified