Gemini 2.5 Pro vs Llama 4 Scout
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | Gemini 2.5 Pro | Llama 4 Scout |
|---|---|---|
| Provider | Meta | |
| Input Price (1M) | $1.25 | $0.10 |
| Output Price (1M) | $10.00 | $0.30 |
| Context Window | 1,000,000 | 10,000,000 |
Verdict
Gemini 2.5 Pro costs $1.25 per 1M input tokens and $10.00 per 1M output tokens. Llama 4 Scout costs $0.10 per 1M input tokens and $0.30 per 1M output tokens. Llama 4 Scout is 92% cheaper on input tokens than Gemini 2.5 Pro. For output tokens, Llama 4 Scout is the more affordable option at $0.30/1M vs $10.00.
On context window, Llama 4 Scout supports 10,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose Gemini 2.5 Pro
- ✓ You are already integrated with Google
When to choose Llama 4 Scout
- ✓ You need the lowest input token cost ($ 0.10/1M)
- ✓ Your workload is output-heavy — Llama 4 Scout generates text cheaper
- ✓ You need a larger context window (10,000,000 tokens)
- ✓ You are already integrated with Meta
Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.
Frequently Asked Questions
Is Gemini 2.5 Pro cheaper than Llama 4 Scout? ▼
Llama 4 Scout is cheaper on input tokens at $0.10/1M vs $1.25/1M for Gemini 2.5 Pro — a 92% saving.
What is the context window of Gemini 2.5 Pro vs Llama 4 Scout? ▼
Gemini 2.5 Pro has a 1,000,000-token context window. Llama 4 Scout has a 10,000,000-token context window. Llama 4 Scout supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: Gemini 2.5 Pro or Llama 4 Scout? ▼
The best choice depends on your use case. For cost efficiency on input tokens, Llama 4 Scout is the cheaper option. For maximum context length, Llama 4 Scout supports 10,000,000 tokens. Use the comparison table above to find the right fit for your workload.