NetMind.AI

Making AI accessible to more people and more organizations so they can participate in the AI economy on more equal terms.

[NetMind.AI @NetMindAI]

Top-tier AI models. Lower API costs. One simple platform.

With NetMind, developers and teams can access leading AI models — including Claude, GPT, DeepSeek, GLM and more — through one API key, one budget and one simple bill.

Now with NetMind Pro, you can save even more.

For $19/month, Pro includes:
- 190,000 Credits included
- 0% service fee
- 20% off the latest Anthropic & OpenAI models
- Up to 50% off selected latest model APIs
- 100 Global RPM
- Early access and free trials across all NetMind products

Your Pro plan effectively pays for itself in credits — and helps you get more premium model usage from the same budget.

NetMind Pro is now live.

Subscribe today:
https://t.co/9KFvkOWUqK

More coming soon 👀

[NetMind.AI @NetMindAI]

GLM-5.3 on NetMind API: https://t.co/02YB6CwQUD
NetMind Pro: https://t.co/2KMVSpJ0wO

[NetMind.AI @NetMindAI]

GLM-5.3 is on NetMind API: $1.4 per 1M input tokens, $4.4 per 1M output.

It sits behind the same endpoint as 100+ frontier models: one unified API, one key, one contract. Moving a workload to GLM-5.3 doesn't mean a new integration.

On NetMind Pro it gets cheaper: up to 50% off model API pricing, a 0% platform service fee and 100% credits back.

And if you'd rather not choose a model for every request, smart routing picks the cheapest qualified provider per request.

[NetMind.AI @NetMindAI]

A website, an internal tool, an AI assistant. Your idea shouldn’t sit in a backlog for months.

@manyfold_ai, part of NetMind, builds it with:
• A fixed price upfront
• Early previews you can test
• Most first versions live within two weeks

[Manyfold @manyfold_ai]

Got an idea for a website, an internal system or an AI assistant? Our engineers build it with our own AI platform. Fixed price before we start, a preview link early and often, and most first versions go live within two weeks.

[FluxA @FluxA_Official]

The FluxA × @NetMindAI Arena42 Challenge is live!

Have your agent call a verified FluxA AgentMarket API and complete a real task.

200 USDC prize pool. 40 winners.

Share your results with #FluxAxArena42 + your entry code, then submit:
https://t.co/TjDVpL6bJa

[NetMind.AI @NetMindAI]

Google's new flagship AI model just landed on NetMind.

Gemini 4 Argon is now live.

🧠 1M-token context window
🏆 #1 on the Vals Index
⚡ Built for complex coding, reasoning, and AI agents

Frontier intelligence. One API. No extra integrations.

Try it now 👇
https://t.co/PaDyZPbJAW

[NetMind.AI @NetMindAI]

Paper: https://t.co/hGFQQOFlqq
GPT-6 Astra on NetMind API: https://t.co/SqElDmbAeH

[NetMind.AI @NetMindAI]

GPT-6 Astra solved 49 of 50 unpublished physics problems. On NetMind API PRO: $8 in, $40 out per 1M tokens.

20% Cheaper than other providers.

The TheoPhysEval paper ran it in Codex: 98% accuracy at an average cost under $3 per problem. The authors put a typical problem at about a day or less for a world expert.

Price the task, not the token. Which one do you budget by?

[Manyfold @manyfold_ai]

Your agent is tied to your laptop. Close the lid and it stops. Six issues wait on one machine. A message from Slack can't reach it.

Agent hosting fixes that. Close the lid. It keeps running. One machine per agent. Same agent. Every surface.

[NetMind.AI @NetMindAI]

NetMind API: https://t.co/2KMVSpIsHg
NetMind Pro: https://t.co/2KMVSpIsHg
Manyfold: https://t.co/0vqP2ShhJN
NarraNexus: https://t.co/VeRM13so9T
Narra Messenger: https://t.co/jS9dQNP3so
Arena42: https://t.co/Y4UtQKjRRz

[NetMind.AI @NetMindAI]

100+ frontier models, one NetMind API endpoint. That's where the stack starts.

NetMind API: chat, vision, audio and embeddings through one API, one key, one contract. Smart routing picks the cheapest qualified provider per request. Smart Tools add code interpreter, PDF parsing and more.

NetMind Pro: up to 50% off model API pricing, 0% platform service fee, 100% credits back.

Compute: H100, A100 and RTX 4090, on demand or reserved. GPU clusters for training, dedicated endpoints for production.

AI agents built on it:
• @manyfold_ai: every coding agent you use, in one workspace
• @NarraNexus: agents with persistent memory, social identity and evolving relationships
• @NarraMessenger: for humans, AI agents and everything in between
• @AgentArena42: competitive games and leaderboards for AI agents

One ecosystem, from the model call to the agent team.

$NMT

[Narra Nexus @NarraNexus]

Running one agent is easy. Coordinating a few is the hard part.

Munder Difflin, a new open-source desktop harness, runs Claude Code, Codex, Gemini CLI and OpenCode under a central orchestrator that routes work between them, each agent with its own mailbox.

NarraNexus teams coordinate another way: agents are peers on a shared message bus with DMs, group chat, hand-offs and shared context across the whole team.

Orchestrator on top, or peers on a bus. Which one breaks first when you add the fifth agent?

[NetMind.AI @NetMindAI]

Jev 1.13 on NetMind: https://t.co/TJX5SjhwzV
Opus 5.5 on NetMind: https://t.co/AYAZj7nrjr

[NetMind.AI @NetMindAI]

Opus 5.5 output: $20 per 1M tokens on NetMind.
Jev 1.13 output: $0. Input: $0.042 per 1M.

Most of an agent loop is not writing. It is deciding: is this done, is this safe, which route.

Jev returns a typed decision with a probability attached, so plain code can act on it, and Opus gets called when Jev is unsure.

Opus writes. Jev decides. Both on one NetMind API key, 100+ models.

What is the first yes/no question in your agent loop you would stop paying Opus for?

[NetMind.AI @NetMindAI]

Benchmarks are Anthropic-reported, from the Haiku 5.5 launch page

Smart Model: https://t.co/z9cUw9NK3r

[NetMind.AI @NetMindAI]

On computer use, Claude Haiku 5.5 reaches 86% of Sonnet 5.5's score at 1/20 the per-token price. On terminal coding, it reaches 56%.

OSWorld 2.1: 72.4% vs 83.9%
Terminal-Bench 4.0: 39.2% vs 70.6%
Per 1M tokens (prompts up to 100K): $0.10 / $0.50 vs $2 / $10
One model for every request overpays on the easy steps or underperforms on the hard ones.

Smart Model on the NetMind API routes each request to the most suitable frontier model. Pick the GPT-based or Claude-based route and switch with one string. 1M context, OpenAI-compatible. Link below.

[NetMind.AI @NetMindAI]

Explore the NetMind API Model Library: https://t.co/e4rxHCkvub

[NetMind.AI @NetMindAI]

75% cheaper than Haiku 4.5.
That's Claude Haiku 5.5, just released. Anthropic's own advice: pair it with Opus 5.5 or Sonnet 5.5 as a subagent for high-volume work like summaries and database queries.

Big model plans. Small model does the volume. That's routing, and it's how you scale an agent without scaling the bill.

Routing needs every tier behind one key. The NetMind API has 100+ models, Opus 5.5 and GPT-6 Astra included.

Which steps in your agent still run on your most expensive model?

[NetMind.AI @NetMindAI]

Connecting your Manyfold agent is easier now.
One Click. One Paste.

[Manyfold @manyfold_ai]

Give your agent Manyfold in one click. The button on https://t.co/pAsmmm1ei3 copies a prompt. Paste it into Claude Code, Codex or any agent that runs shell commands. It installs the mf CLI, opens your browser once to sign in, and connects. No sign-up first.

[NetMind.AI @NetMindAI]

Automation that forgets you isn't help, it's homework. Narra is the memory that makes an agent feel like it actually knows you.

[Narra Nexus @NarraNexus]

An agent that forgets everything when you close the file isn't a coworker. It's a sidebar.
Claude now lives inside Google Docs, Sheets and Slides: it reads what you have open and edits in place, with each edit approved by you.

Agents are moving into the apps where work happens. Memory decides whether they stay useful there.

NarraNexus agents keep it:
• Memory organized by topic, not timestamp: Tuesday's thread picks up Monday with no recap
• A graph of the people, teams and channels your agent meets
• Runs locally, with your own keys

What should your agent still know next week?

[NetMind.AI @NetMindAI]

Would you let AI negotiate a deal for you?

We put Claude Code and Codex to the test in eight negotiation runs. Claude Code won seven, but the results only tell part of the story.

In several runs, Codex gave up something without being asked, went along with the other side’s explanation for its pricing, or accepted the worst deal it was allowed to take even though there was still time to negotiate.

Each decision could sound reasonable on its own. Together, they meant leaving value on the table.

Dana Forfa, the Founder & CEO of Procure and Prosper, picked up our research in her latest article (https://t.co/keiLN3b4WG) and brought it into the world of procurement. She looks at the difference between asking AI to help you prepare for a negotiation and letting it speak for your business.

Her advice is practical: get something back when you make a concession, question the supplier’s pricing claims, and remember that your minimum acceptable deal shouldn’t become your goal.

It’s a small study, and there’s more to test. But it raises a question worth asking before handing over the conversation: will your AI push for a better deal, or just get a deal done?

[NetMind.AI @NetMindAI]

https://t.co/JHTq34ZwFc