Quasar Alpha has a larger context window than Gemma 4 31B (1.0M tokens vs 262K tokens).
Rebuild the Linear UI in Tailwind. The animations are where it shows.
Which answer wins?
Not enough votes to call it. On the specs, Gemma 4 31B has the edge: bigger model tier, newer, major provider backing.
| Spec | ||
|---|---|---|
| Input price | $0.14/M tokens | — |
| Output price | $0.4/M tokens | — |
| Context window | 262K tokens | 1.0M tokens |
| Weights | Open | — |
| Free API (OpenRouter) | Yes (1 provider) | — |
| Released | Apr 2026 | Apr 2025 |
| At 10M a month | $1.40 | not listed |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Gemma 4 31B is developed by Google AI while Quasar Alpha is developed by OpenRouter. Gemma 4 31B has a 262K token context window vs Quasar Alpha's 1.0M. You can compare their actual outputs across 4 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemma 4 31B and Quasar Alpha each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 4 challenges so you can judge which fits your needs best.
This page shows a side-by-side comparison of Gemma 4 31B and Quasar Alpha across shared challenges. You can vote on which model produced the better output in a blind duel. Browsing and voting are free. No account is needed to look; signing in only saves your votes and likes.