Product updates, model releases, and platform improvements.
March 2026
Add MiniMax M2.7
MiniMax M2.7
MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. It incorporates advanced multi-agent collaboration, enabling the model to plan, execute, and iteratively refine complex tasks across dynamic environments.
Built for production-grade workflows, M2.7 supports tasks such as live debugging, root cause analysis, financial modeling, and full document generation across Word, Excel, and PowerPoint. With strong benchmark performance—including 56.2% on SWE-Pro, 57.0% on Terminal Bench 2, and 1495 ELO on GDPval-AA—it sets a new standard for multi-agent systems in real-world digital workflows.
🚀 Apertis SDK v2.1 — Better compatible with OpenCode, Kilo Code & all AI coding tools
What changed?
In v1.x, our SDK used a custom implementation that caused compatibility issues with some tools — most notably Zod parsing errors and empty responses in OpenCode. We've completely rewritten the SDK as a thin wrapper over the official @ai-sdk/openai-compatible package, guaranteeing compatibility across the ecosystem.
What you need to do
Nothing — the API is unchanged. Just update:
npm install @apertis/ai-sdk-provider@latest
OpenCode users
You can now use our SDK directly in your OpenCode config:
GPT-5.4 mini brings the core capabilities of GPT-5.4 into a faster, more efficient model optimized for high-throughput workloads. It supports text and image inputs and delivers strong performance across reasoning, coding, and tool use, while reducing latency and cost for large-scale deployments.
Designed for production environments, GPT-5.4 mini balances capability and efficiency, making it well suited for chat applications, coding assistants, and scalable agent workflows. It provides reliable instruction following, solid multi-step reasoning, and consistent performance across diverse tasks with improved cost efficiency.
GPT-5.4 Nano
GPT-5.4 nano is the most lightweight and cost-efficient variant of the GPT-5.4 family, optimized for speed-critical and high-volume workloads. It supports text and image inputs and is designed for low-latency tasks such as classification, data extraction, ranking, and sub-agent execution. Prioritizing responsiveness and efficiency over deep reasoning, GPT-5.4 nano is ideal for real-time systems, background processing, and distributed agent pipelines where minimizing cost and latency is essential.
Our new "Stacked A" mark features a dual-layer geometric design with metallic teal gradients, replacing the previous rainbow-arc logo. The layered depth effect represents the multiple AI providers unified behind a single API.
What Changed
Logo: Geometric Stacked A with Apertis Teal (#2dd4bf → #0d9488)
Favicon: Full icon set across 25 sizes (16px–512px) for crisp rendering on every device - OG Images: All social preview images updated with new branding
✨ Billing Credits API — Check Your Balance Programmatically
We've launched a new API endpoint that lets you query your remaining credits and subscription quota using your API key — no dashboard login required.
Endpoint: GET /v1/dashboard/billing/credits
The Problem
Until now, checking your Apertis balance meant opening the dashboard in a browser. This creates friction in several real-world scenarios:
Coding agents running overnight — Claude Code, Cursor, or Kilo Code sessions can burn through credits while you sleep. By the time you notice, the session
has already failed mid-task with an insufficient balance error.
Team automation pipelines — CI/CD workflows that call AI APIs have no way to pre-check if there's enough budget before kicking off an expensive batch job.
Multi-key management — If you distribute API keys across projects or team members, there's no programmatic way to monitor which keys are running low.
Subscription cycle awareness — Subscription users couldn't check how much cycle quota remains without visiting the dashboard. Easy to accidentally exhaust
your monthly allocation without realizing it.
We looked at what other providers offer: OpenAI has no balance endpoint (this is one of the most requested features on their community forum). Anthropic's Admin API can query cost reports but not remaining credits, and requires a separate admin key. Neither provides a simple "how much do I have left?" API call.
1. Pre-flight budget check before expensive operations
Before kicking off a large batch job or a long coding agent session, check if you have enough credits:
import requests
credits = requests.get(
"https://api.apertis.ai/v1/dashboard/billing/credits",
headers={"Authorization": "Bearer sk-your-key"}
).json()
if credits["is_subscriber"]:
remaining = credits["subscription"]["cycle_quota_remaining"]
if remaining < 100:
print(f"Warning: only {remaining} quota remaining in this cycle")
else:
remaining = credits["payg"]["remaining_usd"]
if remaining < 1.0:
print(f"Warning: only ${remaining:.2f} credits left")
2. Automated low-balance alerts
Set up a cron job or monitoring script that pings you when credits drop below a threshold:
#!/bin/bash
BALANCE=$(curl -s https://api.apertis.ai/v1/dashboard/billing/credits \
-H "Authorization: Bearer $APERTIS_KEY" | jq '.payg.remaining_usd')
if (( $(echo "$BALANCE < 5.0" | bc -l) )); then
echo "Low balance alert: $BALANCE USD remaining" | \
mail -s "Apertis Low Balance" you@example.com
fi
What Makes This Different
This is an Apertis exclusive. We surveyed every major AI API provider:
OpenAI: No balance endpoint. The most upvoted feature request on their developer forum for over two years. Their Usage API shows historical spending but not remaining credits.
Anthropic: Admin API provides cost reports, but requires a separate admin key and doesn't return remaining balance.
Together AI, OpenRouter: No programmatic balance check.
We believe knowing your balance should be as simple as making one API call. No special keys, no dashboard login, no scraping.