Model comparison · 2026-09-22
Apertus 70B Instruct: which to choose at the same price as v1.5 70B
Covers that publicai/apertus-70b-instruct carries the exact same price as v1.5 70B but comes without its wider context window and image input support, and the cases where this model is still a sensible choice.
An honest observation: v1.5 70B's capability set is a superset
Comparing publicai/apertus-70b-instruct's catalog data against publicai/apertus-v1.5-70b's shows both carry the same price ($0.82 input / $2.92 output per million tokens), but v1.5 70B adds a wider context (262,144 versus 65,536 tokens) and image input on top of everything 70B Instruct has (function calling, JSON mode). So looking at the capability list alone, v1.5 70B is technically a superset of 70B Instruct.
This article's goal isn't to hide that, but to show, with that clear picture in hand, the concrete cases where choosing 70B Instruct can still make sense.
A narrower context window is sometimes an advantage
A 65,536-token context ceiling acts as a natural guard against a request accidentally sending far too much input; in a production flow working with short, predictable requests, that's a kind of safety belt against an unexpected cost spike. On v1.5 70B, you'd need to implement the same protection yourself on the client side (setting your own token limit on the request, for example).
Also, if your integration is already tested and verified against this identifier (swiss-ai/apertus-70b-instruct), moving to v1.5 without a functional need adds an unnecessary regression-testing burden; for an integration that values version stability, staying on the current identifier is a reasonable choice.
- A narrow context ceiling: a natural guard against accidentally sending an oversized request.
- An integration already tested against this identifier: don't switch without a reason.
- If you don't need image input, there's no functional difference between the two models.
If you're building a new integration, consider v1.5
If you're building an integration from scratch and there's a chance you'll need image input or wider context in the future, starting with v1.5 70B at the same price removes the need for a model change later.
Frequently asked questions
Does 70B Instruct have no advantage at all over v1.5?
There's no direct capability advantage (same price, v1.5 strictly offers more); the advantage is indirect — a narrower context ceiling can act as a safety boundary, and not changing an existing integration reduces regression risk.
Does switching between the two require a code change?
Changing the model identifier is enough; both models share the same Chat Completions interface, function calling, and JSON mode. If you want to add image input, you'll need to add an image part to your request.