Changelog

The Apertis MCP server now ships a delegate coworker tool. Connect it to Claude Code (or any MCP client) and Claude can hand off routine, high-volume subtasks — bulk edits, boilerplate, repetitive lookups — to a cheaper model through your Apertis API key, while staying in control as the "manager."

What's new

• `delegate` tool — Claude calls a single MCP tool to run a subtask on a

lower-cost model, then reviews the result. You keep premium models for reasoning and spend cheap tokens on the busywork.

• Works with any MCP client — Claude Code, Claude Desktop, and other

MCP-compatible agents.

• One install — available on npm as @apertis/mcp-server.

Get started

  npx @apertis/mcp-server

Add it to your MCP client config with your Apertis API key, and Claude can start delegating immediately.

See the official documentation here and source code.

New in Settings → Usage

Switch Advisor estimates what your recent usage would cost on a different model — projected from your own pay-as-you-go activity, not a generic price list.

How it works

• Pick a From model — your recently used models, highest-spend preselected
• Search any platform model as the Candidate
• Get an instant projection: current cost, projected cost, and savings (absolute + %)

The projection replays your real input/output token volumes from the selected time range on the candidate model's pricing — so the figure reflects how you actually use the model, not a marketing average.

Example: a workload on claude-opus-4-6 costing $36.00 over 30 days projects to $2.61 on deepseek-v4-pro — a 92.75% reduction.

Available now in Settings → Usage, right below the per-model usage table. No setup required.

▎ Cost estimate only — it does not compare output quality or response speed.

Gemini 3.5 Flash

Gemini 3.5 Flash is Google's high-efficiency multimodal model, delivering near-Pro level performance in coding and reasoning at Flash-tier speed and cost. It supports text, image, video, audio, and PDF inputs, making it well suited for diverse multimodal workflows.

Optimized for coding proficiency and parallel agentic execution, the model defaults to medium thinking effort for faster, cost-efficient responses while supporting configurable thinking levels (minimal, low, medium, high) for fine-grained cost–performance control.

Enjoy it.

Claude Opus 4.7 (Fast)

Fast version of Claude Opus 4.7 is live.

Enjoy it.

What changed

• Added a Recent Availability card to model detail pages.
• Added heartbeat bars for the recent delivery window.
• Added hover and keyboard-focus tooltips with date, time, availability percentage, and status.
• Counted retried or fallback-routed requests as healthy when the request ultimately succeeds.

How to read it

The card reports observed delivery, not a synthetic uptime probe.

If Apertis has recent successful delivery for a model, the relevant heartbeat bucket is green. If an actual delivery failure is observed, the bucket can move to degraded or unavailable based on the observed success rate.

When there is no recent traffic for a bucket, Apertis treats that silence as no observed anomaly and displays it as green 100%. This keeps the signal aligned with the rule that a model should not look unhealthy just because no one called it during that interval.

Why this matters

You can now check model-level health from the same page where you review pricing, context, endpoints, and examples. Teams choosing between models can see recent delivery quality without waiting for a separate status page or paying for active probes.

The implementation stays cost-aware by using delivery results Apertis already sees during normal routing.

Enjoy it.