Nebula Block

Affordable AI and GPU cloud computing for everyone.

[Nebula Block @nebulablockdata]

Kimi K3 is now live on Nebula Block 🤝

Moonshot AI's flagship model with a 1M-token context window, built for long-horizon agentic coding and tool use, with native vision input and always-on reasoning

Pricing
💲 $3.00/M input
💲 $15.00/M output
💾 $0.30/M cache read

Find your at: https://t.co/UmCCL79ZZX

[Nebula Block @nebulablockdata]

The next generation of AI infrastructure is being built now — and Nebula Block is setting the pace. ✅

Read why organizations are turning to NebulaBlock for scalable, sovereign, cost-efficient AI infrastructure.

🔗 https://t.co/jbE1hVeYpf
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#AIInfrastructure #NebulaBlock #AISovereign

[Nebula Block @nebulablockdata]

🎉 Nebula Block is heading to Venture Day 2026! 🎉

We’re excited to share that Nebula Block has been selected to showcase our work at a dedicated booth at Venture Day, recognizing the strong progress and momentum we’ve built throughout the program.

We’re incredibly grateful for this opportunity and can’t wait to connect with the community, share what we’ve been building, and meet fellow innovators in AI.

📍 Come find us at Venture Day and say hi!

👉 Share & register: VENTURE DAY 2026 | NEXT AI MONTRÉAL · Luma
https://t.co/BdcoQfO0pB

See you all on September 15! 🚀

[Nebula Block @nebulablockdata]

🚀 New models are now live on Nebula Block. 🚀

We’ve expanded our model lineup with:
• Claude Fable 5.1: https://t.co/eAL9g81FSI

• GLM-5.3 Flash:
https://t.co/JNDfAr9vzh

• GLM-5.3:
https://t.co/UA0MLyOsa5

• Qwen3.8-27B:
https://t.co/m7uwbGOZ90

• Gemini-3.8-Flash:
https://t.co/LPzzhP85rF

Built for teams looking for flexible access to the latest AI models with reliable infrastructure.

Explore the new models and capabilities on Nebula Block today!
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#AI #LLM #AIInfrastructure #NebulaBlock #GenerativeAI

[Nebula Block @nebulablockdata]

Unvetted training data in your RAG pipeline isn't just technical debt — it's legal exposure. Here's what enterprises need to audit now. ⏳

🔗https://t.co/Q8crWWneUa
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#RAG #LegalRisk #AIGovernance #NebulaBlock

[Nebula Block @nebulablockdata]

Your context architecture is bleeding cloud spend. Here's where the waste actually hides. 👇👇

🔗https://t.co/feyWHjVjQ3

[Nebula Block @nebulablockdata]

Open-source LLMs: cheaper upfront, complicated later. The real TCO breakdown.🫴
🔗https://t.co/pB3T2ucTSp
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#MultiAgent #RealTime #Architecture #NebulaBlock

[Nebula Block @nebulablockdata]

How real-time streaming actually works in multi-agent AI systems at scale 🧵

Find the full answer here:👇👇
https://t.co/sEvNR8xqOr

[Nebula Block @nebulablockdata]

PII masking isn't as safe as you think. Synthetic data vs. masking in LLM pipelines, compared.
👇👇
🔗https://t.co/jGHCuLb8E7

[Nebula Block @nebulablockdata]

Ran the numbers: 5 point solutions vs. 1 AI operating system. The ROI gap is bigger than expected.✅

We ran the numbers on consolidating into a single AI operating system — the ROI case is compelling.👇

🔗 https://t.co/zp58FOnJqD
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#ROI #AIOperatingSystem #NebulaBlock

[Nebula Block @nebulablockdata]

Point solutions are having their Blockbuster moment. Agentic AI is the streaming service. 😌

Read more: https://t.co/iXvca7Fhqs

[Nebula Block @nebulablockdata]

The state of enterprise AI, 2026: less hype, more infrastructure. Here's what actually changed.

https://t.co/qLqYdJJpGc
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#EnterpriseAI #StateOfAI #NebulaBlock

[Nebula Block @nebulablockdata]

We tested 10 open-source agent frameworks so you don't have to. 😎🧐

From orchestration to tooling to production-readiness — here's how they really stack up in 2026. Full comparison in the article.

🔗https://t.co/8WG4wm9ecJ

#AIAgents #OpenSource #EnterpriseAI #NebulaBlock

[Nebula Block @nebulablockdata]

We benchmarked every major enterprise AI platform on the metrics that actually matter — reasoning, coding, agentic workflows, cost, latency, and safety.

See where the leaders separate from the pack.
🔗 https://t.co/bki7zHgPV0

[Nebula Block @nebulablockdata]

LLM vs. RAG vs. Agent Evals: What Are You Actually Measuring? 🧐
Not all AI systems should be evaluated the same way.

- An LLM eval may focus on safety, instruction following, and accuracy.
- A RAG system needs to prove retrieval quality and answer faithfulness.
- A coding agent must be evaluated on tool calling, planning, retries, and whether it actually resolves the task.
- A multi-agent system adds another layer: coordination, role adherence, hand-offs, and overall task success.

The key takeaway: as AI systems become more autonomous, evaluation needs to move beyond “Is the answer correct?” to “Did the system complete the task reliably?”

#AI #AIAgents #RAG #LLM #AgenticAI #AIEvaluation #EnterpriseAI #NebulaBlock

[Nebula Block @nebulablockdata]

Moving AI inference from the public cloud isn’t just an infrastructure decision. It’s an architecture decision.

For enterprise teams, the question is no longer simply:
“Can we run this model locally?”
It’s:
Can we run it securely, reliably, cost-effectively, and at production scale?

Moving toward localized or sovereign inference means thinking through much more than GPUs:

→ Data residency & regulatory requirements
→ Model selection & licensing
→ GPU capacity, VRAM & throughput
→ Inference serving and caching
→ Network isolation & zero-trust security
→ Observability & auditability
→ TCO and infrastructure utilization
→ Migration, rollback & ongoing governance

And full sovereignty doesn't have to mean moving everything on-prem.
For many enterprises, a hybrid architecture - keeping sensitive workloads on sovereign infrastructure while using public-cloud models for less sensitive workloads - may be the more practical path.

We put together a 12-point Sovereign Infrastructure Checklist to help engineering, security, and IT teams evaluate the migration from public-cloud inference to localized infrastructure.

If your organization is considering sovereign AI, this is a good place to start.
👉 Read the full checklist: https://t.co/dxEBW95Oy7
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#SovereignAI #AIInfrastructure #EnterpriseAI #AIEngineering #DataSovereignty #CloudInfrastructure #MLOps

[Nebula Block @nebulablockdata]

🇨🇦 3 New AI Models Are Now Live on Nebula Block

Nebula Block now supports three new models:

⚡ Grok 4.6: https://t.co/4VHz9r4eQm
🧠 DeepSeek-V4-Pro-0813: https://t.co/025ReHl6Pd
✨ Gemini 3.7 Flash: https://t.co/YxrO1KgojK

Whether you're evaluating models, building AI applications, or running production workloads, you can now choose from even more capable models on Nebula Block.

More models. More choice. Sovereign AI infrastructure.

[Nebula Block @nebulablockdata]

🚨 Shadow AI: The Security Blind Spot You Can’t Ignore

Simply banning AI tools in the enterprise doesn’t stop their use it just pushes employees to use unsanctioned, personal accounts. When sensitive data, source code, or customer records flow through untracked LLM API calls, the risks become real.

In this latest post, NebulaBlock breaks down:
🔍 Why Shadow AI is exploding across enterprise workflows.
🛠️ 5 layers to detect rogue LLM API calls (from DNS logs to secret scanning).
🛡️ How to build a sustainable governance program that enables productivity without compromising security.

📌 Read the full article on Nebula Block: https://t.co/eFVlEVwRiI

How is your team handling the balance between AI adoption and data security? Let’s connect in the comments! 👇
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#ShadowAI #EnterpriseAI #Cybersecurity #DataGovernance #NebulaBlock #LLM #API #CISO

[Nebula Block @nebulablockdata]

Task decomposition is the key to helping AI agents handle complex problems effectively. ✅

Learn how it works — and why it's reshaping how we build AI systems. 👇

🔗 https://t.co/lg2hjIU0ud
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#AIAgents #AgenticAI #AIInfrastructure #EnterpriseAI #ResponsibleAI #AI #NebulaBlock

[Nebula Block @nebulablockdata]

Many workflows look simple on the surface but actually require complex multi-agent coordination behind the scenes.

We break down 12 real-world examples from enterprise environments. 👇👇

🔗https://t.co/h4lgTDJqeb
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#AIAgents #AgenticAI #AIInfrastructure #EnterpriseAI #ResponsibleAI #AI #Automation #NebulaBlock