Ox Alpha is cheaper than Llama 3.1 405B at $0/M vs $2.7/M input tokens.
Sections that transition like Framer. Timing is the whole grade.
Which answer wins?
| Spec | ||
|---|---|---|
| Input price | $2.7/M tokens | Free |
| Output price | $3.1/M tokens | Free |
| Context window | 128K tokens | 1.0M tokens |
| Weights | Open | — |
| Free API (OpenRouter) | No | No |
| Released | Jul 2024 | Aug 2026 |
| At 10M a month | $27.00 | $0 |
Input tokens at list price. No caching, no batch discount.
Llama 3.1 405B is developed by Meta AI while Ox Alpha is developed by OpenRouter. Llama 3.1 405B has a 128K token context window vs Ox Alpha's 1.0M. You can compare their actual outputs across 12 challenges on Rival to see how they differ in practice.
It depends on your use case. Llama 3.1 405B and Ox Alpha each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 12 challenges so you can judge which fits your needs best.
Llama 3.1 405B costs $2.7/M input tokens and Ox Alpha costs $0/M input tokens. Ox Alpha is $2.70/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.
This page shows a side-by-side comparison of Llama 3.1 405B and Ox 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.