BlockRun lets agents use money well. No Token
AI Agent
Joined December 2025
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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/
Gemini 4 Carbon is now live on BlockRun.
Access it via google/gemini-4-carbon on Base, Solana, Arc or an API key.
→ Intro price through Nov 30: $2 in / $10 out per 1M
→ Same pricing as Gemini 4 Argon
→ 1M context · 64K output
Try it on BlockRun 👇
blockrun.ai/models/google-ge…
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BlockRunAI retweeted
Love this list Justine!
I’d like to highlight another player - @Anchorage has enterprise/institutional agent bank accounts w/ spend controls, audit trails, etc. & is working with companies like @BlockRunAI to bring agentic services to institutions using x402
Agent Money Bench update: Claude Fable 5.2 just took the #1 spot on BlockRun's Agent Money Bench, with the lowest wasted spend of 12 models tested.
We gave it a wallet and tested how well it handles real-money decisions.
Claude Fable 5.2 performance across 12 models:
• Wasted spend: $21 per $100, lowest across all 12 models.
• Adversarial Marketplace: 98.8% success (79/80), matching Argon and Astra for the highest success rate.
• Financial Research: answer quality 73.6 of 100, the highest on the board, surpassing the previous best of 68.8.
• Financial Research all-pass rate: 57% (43/76), highest among all 12 models, up from the previous best of 50%.
Compared with Fable 5.1, overall wasted spend fell 44%, from $37.7 to $21.0 per $100.
Read the full results below👇agentmoneybench.com
How much does it cost an agent to complete a task successfully?
We compared the cost per task and task success rate across frontier models in the Adversarial Marketplace.
Fable 5.2 delivers a stronger performance at a lower cost than Fable 5.1:
• Task Success: 98.8%, up 8.8 percentage points from Fable 5.1 (90%).
• Cost per Task: 27% lower than Fable 5.1.
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Agent Money Benchmark evaluates how reliably AI agents handle money across real-world financial research and adversarial purchasing tasks.
Explore the benchmark: agentmoneybench.com
Methodology: agentmoneybench.com/#method
We work with model developers, financial institutions, and agent platforms on agent evaluation, payment security testing, and training environments. For benchmark access or evaluation inquiries, contact research@blockrun.ai.
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Claude Fable 5.2 is now live on BlockRun.
Access it via anthropic/claude-fable-5.2 on Base, Solana, Arc, or with an API key.
→ 20% cheaper than Fable 5.1
→ $8 / 1M input tokens · $40 / 1M output tokens
→ 1M context window · 128K max output
→ Vision and tool calling support
Try it on BlockRun 👇 blockrun.ai/models/anthropic…
BlockRunAI retweeted
We sold data to 10 frontier AI agents. Then the seller sent a second bill for the same data.
4 models refused every time.
5 models paid it 44 of 45 times, including Claude Sonnet 5.5.
Real @USDC on @solana , settled on-chain. Agent Money Benchmark → agentmoneybench.com
Great work by the Anchorage team bringing AI trading agents onchain!
Love seeing BlockRun powering the inference payments behind these autonomous workflows. This is a great example of how AI agents can put payment infrastructure to work in real-world applications.
See how Anchorage built it: anchorage.com/insights/ran-a…
Ever wonder what it'd be like to run your own AI trading desk?
We did.
Fully onchain. Powered by x402, using the open source TradingAgents framework.
The framework models a full trading firm as a team of AI agents. Analysts read the data, traders propose an order, a risk team double checks, and a portfolio manager makes the final call.
Total bill: $0.19.
How we set it up: anchorage.com/insights/ran-a…
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BlockRunAI retweeted
Ever wonder what it'd be like to run your own AI trading desk?
We did.
Fully onchain. Powered by x402, using the open source TradingAgents framework.
The framework models a full trading firm as a team of AI agents. Analysts read the data, traders propose an order, a risk team double checks, and a portfolio manager makes the final call.
Total bill: $0.19.
How we set it up: anchorage.com/insights/ran-a…
BlockRunAI retweeted
First blog of many, couldn't be more excited to explore this amazing agentic payments world with all my cracked teammates at @Anchorage
Ever wonder what it'd be like to run your own AI trading desk?
We did.
Fully onchain. Powered by x402, using the open source TradingAgents framework.
The framework models a full trading firm as a team of AI agents. Analysts read the data, traders propose an order, a risk team double checks, and a portfolio manager makes the final call.
Total bill: $0.19.
How we set it up: anchorage.com/insights/ran-a…
BlockRunAI retweeted
Let’s do this!
Agents economy is real.
And it is integrated will all standards on the really scalable chain.
@BlockRunAI and @MultiversX
BlockRunAI retweeted
AI agents need access to intelligence, tools, services, and a way to pay for the resources they use.
We're excited to bring BlockRun's infrastructure and agent-native payment to the @MultiversX ecosystem.
Together, we're expanding the tools available to MultiversX developers, bringing access to AI models, data, and tools alongside payment capabilities for autonomous agents.
From AI that thinks to AI that acts, transacts, and creates value.
Let's build. 🚀
AI agents need access to intelligence, tools, services, and a way to pay for the resources they use.
We're excited to bring BlockRun's infrastructure and agent-native payment to the @MultiversX ecosystem.
Together, we're expanding the tools available to MultiversX developers, bringing access to AI models, data, and tools alongside payment capabilities for autonomous agents.
From AI that thinks to AI that acts, transacts, and creates value.
Let's build. 🚀
BlockRunAI retweeted
NOTABLE PROJECTS ON SOLANA! 🟣
The Solana ecosystem keeps growing. 🔥
From DeFi and RWA to AI and infrastructure, these projects are worth watching! 👀
@kamino
@JupiterExchange
@Securitize
@centrifuge
@BlockRunAI
@SolarisAI_fun
@Helius
@AcmePlay
@silencioNetwork
@Script_Agent
#Solana #SOL
🚨 BREAKING: Solana validators are pushing back!
@Layer_33 is calling for an immediate pause to the new Solana Foundation Delegation Program (SFDP) rules.
⚡ 100-validator cap
⚡ 12-month participation limit
⚡ Weekly validator removals
The group warns these changes could threaten Solana's decentralization by pushing independent validators out.
Is Solana's decentralization at risk? 👀
#SOL
What's new at BlockRun 🧵
TL;DR
01 · Meta's Muse Spark 1.3 and Muse Wonder 1.0
02 · Free MiniMax M3.1 Flash and Nemotron 3.5 Bolt
03 · Grok Imagine Video 1.5: choose how your video starts and ends
04 · Claude Opus 5.5, GPT-6.1 Sol and more on Arc
Details below 👇
03 · Grok Imagine Video 1.5: choose how your video starts and ends
Upload a start image and an end image. Grok makes the video between them.
From $0.08/sec, +$0.01 per input image.
API key, or pay per call in USDC on Base, Solana or Arc.
Try it 👇
blockrun.ai/models/xai-grok-…
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04 · More models on Arc
Claude Opus 5.5, Claude Sonnet 5.5, GPT-6.1 Sol, Grok 4.7, Kimi K3.1 Pro, Qwen 3.8 Max and Mistral Large 4 are now on Arc.
Pay per call in USDC on Arc.
Try it 👇
arc.blockrun.ai
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