Models
The model catalog — how models are added, priced and routed.
Perspective AI is model-agnostic by design. Rather than locking you into one lab, the platform curates a catalog of the strongest models available — proprietary frontier models and open-weight models side by side — and lets you move between them freely inside a single interface.
The catalog
The catalog spans the major labs and every modality:
- Text & reasoning — flagship models from Anthropic (Claude), OpenAI (GPT), Google (Gemini), xAI (Grok), GLM, Qwen, Mistral, Kimi and more.
- Image — text-to-image and image-editing models.
- Video — text-to-video and image-to-video models.
- Search-native — models that answer from live web results with citations.
Each model has a card describing what it is best at, who built it, its context window, and what it costs to run. Models are labelled foundational (proprietary frontier models) or open source (open-weight models the network can ultimately serve itself).
Working across models
The interface is built around switching, not committing:
- Switch models mid-conversation without losing context.
- Compare two or more models on the same prompt, side by side.
- Combine several models in one thread, so each answer can come from the model best suited to it.
- Tune each request with a reasoning-effort control — spend more thinking on hard problems — and an optional web-search toggle.
Routing modes
You decide how much of the model choice to hand off:
| Mode | Who picks the model | Best for |
|---|---|---|
| Custom | You | You already know which model you want |
| Auto | The platform | You want the right model chosen for you per request |
Additional modes — optimising for reasoning depth, research, or credit efficiency — are on the roadmap.
Pricing
Model pricing is cost-plus-margin: the platform pays the underlying provider (or the network) for each request and adds a thin margin on top. There is no per-model markup game — value comes from usage volume, not from squeezing each call. See Tokenomics §4 for how that margin funds buyback-and-burn.
- Text models are metered by tokens — the input you send plus the output you receive — at a per-model rate.
- Image, video and other media models are metered per generation.
- Every price is shown to you in stable, dollar-legible credits, whatever the model charges underneath.
Rates track real provider costs and are refreshed as those costs move, so the price you see reflects what a model actually costs to run rather than a fixed sticker.
How models get added
Today the catalog is curated: the team adds and maintains models, prioritising capability, coverage across labs, and genuine open-weight options. New flagship models are typically live within days of release.
The longer-term direction, set out in Tokenomics §5, is permissionless listing — anyone can publish a model, and protocol incentives flow to it by measured demand (credits burned, uptime, completion rate) rather than by popularity vote. Governance sets only the guardrails a model must meet; the market decides which models win.
Perspective AI does not try to be the cheapest way to call a model. It competes on breadth, privacy, uncensored access to open models, and freedom from being repriced or deplatformed.