Gemini 2.0 Flash Thinking is cheaper than Llama 3.1 405B at $0.25/M vs $2.7/M input tokens.
Sections that transition like Framer. Timing is the whole grade.
Which answer wins?
| Spec | ||
|---|---|---|
| Input price | $0.25/M tokens | $2.7/M tokens |
| Output price | $0.5/M tokens | $3.1/M tokens |
| Context window | 500K tokens | 128K tokens |
| Parameters | Not disclosed | 405B |
| Weights | — | Open |
| Free API (OpenRouter) | No | No |
| Released | Dec 2024 | Jul 2024 |
| MMLU | 82.3% | 88.6% |
| At 10M a month | $2.50 | $27.00 |
Input tokens at list price. No caching, no batch discount.
Gemini 2.0 Flash Thinking is developed by Google AI while Llama 3.1 405B is developed by Meta AI. Gemini 2.0 Flash Thinking has a 500K token context window vs Llama 3.1 405B's 128K. You can compare their actual outputs across 3 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemini 2.0 Flash Thinking and Llama 3.1 405B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 3 challenges so you can judge which fits your needs best.
Gemini 2.0 Flash Thinking costs $0.25/M input tokens and Llama 3.1 405B costs $2.7/M input tokens. Gemini 2.0 Flash Thinking is $2.45/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 Gemini 2.0 Flash Thinking and Llama 3.1 405B 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.