One chat workspace, many models

Most people who use AI seriously end up with a tab problem. One subscription for reasoning, another for writing, a third for cheap high-volume work, and a fourth because a colleague swears by it. Each has its own history, its own billing date, and no idea what you asked the others.
Melsun Chat removes that split. You switch models inside the same conversation, and the history follows you.
Why switching models mid-thread matters
Model choice is not a one-time preference — it changes per message. A single piece of work often wants two or three different models:
- Draft a first pass with a fast, cheap model, then hand the same thread to a frontier model to tighten the argument.
- Ask a reasoning model to plan an approach, then let a coding-focused model implement it with the plan already in context.
- Get an answer, then ask a different model to check it. Disagreement between two models is a useful signal that you are on shaky ground.
That last pattern is the real argument for multi-model chat. A second opinion costs you one click instead of a re-explanation in another product.
What's included
| Capability | What it does |
|---|---|
| Multi-provider models | NVIDIA, OpenAI, Anthropic, Google, xAI, DeepSeek, Mistral, and Z.AI in one selector |
| Auto routing | Classifies your request and picks a suitable model automatically |
| Browse | Live web results with citations for anything time-sensitive |
| Document Q&A | Attach PDFs, spreadsheets, and images and ask about their contents |
| Connectors | Optional Google Drive, Gmail, Calendar, and Sheets access from Chat |
| Persistent history | Every thread is saved and searchable, whichever model wrote it |
| Shared credits | One balance across chat and the creative studios |
Free models, and when to spend credits
Melsun keeps a tier of unlimited free chat models, subject to fair use, so everyday questions never touch your balance:
- GPT-5.6 Luna and GPT-4o mini — general-purpose workhorses
- DeepSeek V4 Flash — fast drafting and code
- Nemotron 3.5 Lightning — quick everyday answers and Auto routing
- Ministral 3 8B — image reading and a fallback when Nemotron is unavailable
- GLM 4.7 Flash and Gemma 4 — additional free capacity
Premium frontier models draw from credits. Free accounts get 200 credits every 30 days (unused credits do not roll over), and a $20/month plan adds 2,000 credits — the same balance also covers Image, Video, and Audio Studio, so you are not choosing between chat and generation.
Let Auto decide
If picking a model for every message sounds like work, use Auto. It reads the request, classifies the intent — casual question, writing task, coding problem, deep analysis, live web lookup — and routes to a model suited to that shape of work, falling back automatically if a provider is slow.
We wrote about how that routing works in AI orchestration on Melsun.
A practical model-picking guide
- Everyday questions and drafting — stay on a free model. Speed matters more than depth here.
- Hard reasoning, math, long analysis — switch to a frontier model. This is where credits earn their keep.
- Anything time-sensitive — turn on Browse. Prices, flight status, company details, and this week's news all need live sources rather than training data.
- Code — reach for a coding-strong model and paste the actual error, not a paraphrase of it.
- Documents — attach the file instead of describing it. Melsun reads PDFs, spreadsheets, and images directly.
How it compares to a single-provider chatbot
A chat-only product locks you to one lab's model family and one release cadence. When that lab ships a weak update, you absorb it. Melsun's selector means a disappointing release is a different dropdown choice, not a migration.
The other difference is scope: chat is one app of several here. The same login and credit balance also open Image Studio, Video Studio, and Audio Studio. See the full breakdown on the ChatGPT alternative comparison.
Get started
Sign in and open Melsun Chat. Start on a free model, turn on Browse when the question needs current facts, and switch to a frontier model when the work gets hard.
Your conversations stay organized so you can build on previous work instead of starting over.