
Battle-test AI coding models side by side
Battle-test AI coding models side by side
Future AGI records 121,741 monthly visits with -7.8% month-over-month growth and Freemium, Usage-based pricing. Multi-Agent Arena records 5,242 monthly visits with -78% growth and Free pricing.
| Dimension / Metric | ![]() | ![]() |
|---|---|---|
| Official Domain | futureagi.com | olamlabs.ai |
| Pricing Model | Freemium, Usage-based | Free |
| Monthly Visits | 121.74K (121,741) | 5.24K (5,242) |
| MoM Traffic Delta | -10.26K (-7.8%) | -18.53K (-78%) |
| Primary Market & Share | 🇮🇳 India (48%) | 🇺🇸 United States (100%) |
| Direct Visits / mo | 71.47K | 1.95K |
| User Rating | 4.4 | 4 |
| Supported Platforms | Website | Website |

Build, simulate, evaluate and monitor self-improving AI agents
Generate personas, scenarios and synthetic datasets to stress-test text and voice agents across many conversation branches before launch.
Combine always-free heuristic metrics, code evaluators and LLM-as-judge scoring, including agentic evaluators that localise errors in RAG and tool calls.
Route traffic across 15+ LLM providers with load balancing, failover and caching, plus 15 built-in rule-based guardrails and ML content moderation.
End-to-end traces, sessions, agent graphs, custom dashboards and alert monitors give real-time visibility into production behaviour.

Test how AI models cooperate, negotiate, and deceive in strategy games
Diplomacy, Poker, Risk, and other negotiation scenarios each create different pressures, so a model's social behaviour can be compared across contexts.
Matches generate measurable outcomes such as broken promise rates and share of spoils, turning vague impressions of model personality into comparable numbers.
Several models can be placed in the same scenario, making head-to-head differences in cooperation, deception, and negotiation visible.
The team documents findings, updates, and collaborations so results can be read alongside the arena itself.

Battle-test AI coding models side by side
Battle-test AI coding models side by side

Enterprise AI infrastructure where software and expert humans work together
Enterprise AI infrastructure where software and expert humans work together

Crowdsourced arena where AI models compete and humans crown the best design output
Crowdsourced arena where AI models compete and humans crown the best design output

Track, evaluate, and ship AI models and agents in one connected environment.
Track, evaluate, and ship AI models and agents in one connected environment.

Free / Open-sourceAgent observability, evaluation, and continuous improvement for production AI
Free / Open-sourceAgent observability, evaluation, and continuous improvement for production AI

Expert human data and evaluation for training frontier AI

Free / Open-sourceOpen-source database of AI models, prices and capabilities
Free / Open-sourceOpen-source database of AI models, prices and capabilities

Marketplace to find, hire, or build AI agents for real work
Marketplace to find, hire, or build AI agents for real work

Free / Open-sourceEvaluate, monitor, and govern your AI applications in production
Free / Open-sourceEvaluate, monitor, and govern your AI applications in production

Standardize LLM evaluation, observability, and red teaming across your whole org
Standardize LLM evaluation, observability, and red teaming across your whole org

Automated QA, simulation and observability for voice and chat AI agents

Benchmark computer- and phone-use AI agents with blind head-to-head battles
Benchmark computer- and phone-use AI agents with blind head-to-head battles