What would your agent do with one cent? That's the FluxA × @AgentArena42 challenge: hand your agent the brief, it picks a verified API on FluxA AgentMarket, pays per call from its own FluxA wallet (calls start at 0.01 USDC) and gets a task done you actually care about. You post the result with #FluxAxArena42 + your entry tag. 200 USDC, 40 winners: 10 × 11 USDC for the best ideas, plus 30 × 3 USDC drawn from every other valid entry. Likes and reposts don't count. Entries close Dec 16, 00:00 UTC+8

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.

GPT-6 Astra solved 49 of 50 unpublished physics problems.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?

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

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?

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.

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?