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BlockRunAI

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@BlockRunAI

BlockRun lets agents use money well. No Token
AI Agent t.me/blockrunAI Joined December 2025
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BlockRunAI @BlockRunAI
We gave 10 frontier AI models wallets with money.

7 got scammed at least once. The best wasted $25 of every $100. The worst wasted $71.

Agent Money Benchmark tests whether AI agents can be trusted with real money.

We evaluated 10 frontier models across two settings, using real USDC payments on @solana :

→ Financial Research: Agents buy live data from real providers to answer open-ended financial questions (prediction markets, wallet analysis, DeFi yields, etc.).

→ Adversarial Marketplace: Agents buy data from simulated sellers, some of whom cheat. The tasks test whether agents can avoid payment traps, stay within budget, and complete transactions without being exploited.

Key results:

→ Give an agent $100 and the best tier wastes $25–38 of it. The weakest tier wastes $56–71.
→ 7 of 10 models paid a cheating seller at least once, and 6 paid twice for the same data.
→ Only 4 of 10 models made no money errors.
→ No model gets more than half of the research questions right. GPT-6.1 Sol led at 50%, at $0.468 per question.

Explore the full results →
agentmoneybench.com
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BlockRunAI @BlockRunAI
4 more highlights from Agent Money Benchmark:

1. Duplicate-payment scams caught the most models.

6 out of 10 AI models made duplicate payments for data they'd already purchased. 4 of them paid again every single time they encountered the trap (9 out of 9 times).

2. Low cost and low waste don’t always go together.

GPT-6 Luna had the lowest cost per research question ($0.032), yet wasted $71 out of every $100 spent, the most of the 10 models.

3. Capable is not the same as safe.

Claude Fable 5.1 and Claude Opus 5.5 answered the same share of research questions right (36.8%). But Fable made payment or budget errors on 5.0% of marketplace tasks, while Opus made none.

4. Only 3 models were never scammed.

GPT-6 Astra, GPT-6.1 Sol and Claude Opus 5.5 avoided every trap in the marketplace tests.

See the full results, methodology, and model breakdown👇:
agentmoneybench.com
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BlockRunAI @BlockRunAI 5d
We gave 10 frontier AI models wallets with money.

7 got scammed at least once. The best wasted $25 of every $100. The worst wasted $71.

Agent Money Benchmark tests whether AI agents can be trusted with real money.

We evaluated 10 frontier models across two settings, using real USDC payments on @solana :

→ Financial Research: Agents buy live data from real providers to answer open-ended financial questions (prediction markets, wallet analysis, DeFi yields, etc.).

→ Adversarial Marketplace: Agents buy data from simulated sellers, some of whom cheat. The tasks test whether agents can avoid payment traps, stay within budget, and complete transactions without being exploited.

Key results:

→ Give an agent $100 and the best tier wastes $25–38 of it. The weakest tier wastes $56–71.
→ 7 of 10 models paid a cheating seller at least once, and 6 paid twice for the same data.
→ Only 4 of 10 models made no money errors.
→ No model gets more than half of the research questions right. GPT-6.1 Sol led at 50%, at $0.468 per question.

Explore the full results →
agentmoneybench.com
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0 replies 3 reposts 10 likes 1.2K views View on X
BlockRunAI @BlockRunAI
Want FREE $100 for your research agents to spend on AI models?

We're honored to partner with @Anchorage to bring pay-per-request AI inference to Agentic Banking, from quick market news lookups to in-depth data research.

80+ models. One endpoint. Each request priced before it runs, paid over x402.

Each participant will be funded with $100 in inference credit.

📧 Email: agentic@anchorage.com to request access.
Per participant. 80+ AI models. One month.

The credit covers BlockRun services only. Agents in the trial place no trades. Participants complete identity verification.

Request access at agentic@anchorage.com or via your relationship manager.

Read more about our BlockRun partnership: anchorage.com/insights/ancho…
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