Gemini 2.5 Pro vs Llama 4 Scout — Side-by-side pricing
Side-by-side API pricing and tokenizer details for Gemini 2.5 Pro (Google) and Llama 4 Scout (Meta).
Side-by-side pricing
| Feature | Gemini 2.5 Pro | Llama 4 Scout |
|---|---|---|
| Provider | Meta | |
| Input (per 1M tokens) | $1.25 | $0.100 |
| Output (per 1M tokens) | $10.00 | $0.300 |
| Long-context pricing | Over 200K tokens: $2.50 in / $15.00 out | Flat rate at any prompt size |
| Context caching | No | No |
| Batch API discount | Not available | Not available |
| Context window | 1M tokens | 1M tokens |
| Tokenizer | Gemini tokenizer | Heuristic (~chars/4) |
ⓘ Llama 4 Scout: Meta retired the Llama API on 2026-07-06, so there is no vendor price. Figures and context window reflect OpenRouter; other hosts differ.
Real-world cost example
1,000 API requests per month, each with 500 input tokens and 200 output tokens (500K input + 200K output total).
Gemini 2.5 Pro
$2.6250
Input: $0.6250 +Output: $2.0000
Llama 4 Scout
$0.1100
Input: $0.0500 +Output: $0.0600
Llama 4 Scout is 96% cheaper for this workload — saving $2.5150 per month at this volume.
Frequently asked questions
No, Llama 4 Scout is cheaper for the typical workload above. At $0.100/1M input and $0.300/1M output tokens, it costs $0.1100 versus $2.6250 for Gemini 2.5 Pro — a 96% difference. Note that Gemini 2.5 Pro switches to long-context pricing above 200K prompt tokens, so for very long prompts this gap does not scale linearly.
Gemini 2.5 Pro supports a 1M token context window. Llama 4 Scout supports a 1M token context window. A larger context window lets you include more text — documents, conversation history, or code — in a single API call.
Gemini 2.5 Pro does not support context caching. It does not offer a batch API discount. Llama 4 Scout does not support context caching. It does not offer a batch API discount.
No, they use different tokenizers. Gemini 2.5 Pro uses the Gemini tokenizer, while Llama 4 Scout uses Heuristic (~chars/4). Different tokenizers split text differently, so the same prompt will produce different token counts on each model — the effective cost difference may be larger or smaller than the per-token price difference alone suggests.
Gemini 2.5 Pro (Google): $1.25 input / $10 output per 1M tokens. Llama 4 Scout (Meta): $0.1 input / $0.3 output per 1M tokens. Rates shown before caching or batch discounts.
For an 80% output / 20% input workload — typical for code generation or long-form writing — Gemini 2.5 Pro costs $8.2500 per 1M total tokens and Llama 4 Scout costs $0.2600. Llama 4 Scout is 97% cheaper for this pattern. For your exact ratio, paste a real prompt into the calculator above.
Gemini 2.5 Pro has a 1M-token context window — approximately 750K words or ~3K pages of standard text. Llama 4 Scout has a 1M-token context window — approximately 750K words or ~3K pages. (Estimates assume ~0.75 words per token.)
Calculate costs for your actual prompt
Paste your prompt into the calculator and get exact token counts using each model's real tokenizer — all in your browser.
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