GPT-5.5 vs Llama 4 Scout — Side-by-side pricing
Side-by-side API pricing and tokenizer details for GPT-5.5 (OpenAI) and Llama 4 Scout (Meta).
Side-by-side pricing
| Feature | GPT-5.5 | Llama 4 Scout |
|---|---|---|
| Provider | OpenAI | Meta |
| Input (per 1M tokens) | $5.00 | $0.100 |
| Output (per 1M tokens) | $30.00 | $0.300 |
| Long-context pricing | Over 272K tokens: $10.00 in / $45.00 out | Flat rate at any prompt size |
| Context caching | Yes — 90% off cached tokens | No |
| Batch API discount | 50% off | Not available |
| Context window | 1.1M tokens | 1M tokens |
| Tokenizer | o200k_base (tiktoken) | 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).
GPT-5.5
$8.5000
Input: $2.5000 +Output: $6.0000
Llama 4 Scout
$0.1100
Input: $0.0500 +Output: $0.0600
Llama 4 Scout is 99% cheaper for this workload — saving $8.3900 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 $8.5000 for GPT-5.5 — a 99% difference. Note that GPT-5.5 switches to long-context pricing above 272K prompt tokens, so for very long prompts this gap does not scale linearly.
GPT-5.5 supports a 1.1M 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.
GPT-5.5 supports context caching (90% off repeated tokens). It offers a 50% Batch API discount. Llama 4 Scout does not support context caching. It does not offer a batch API discount.
No, they use different tokenizers. GPT-5.5 uses the o200k_base (tiktoken), 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.
GPT-5.5 (OpenAI): $5 input / $30 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 — GPT-5.5 costs $25.0000 per 1M total tokens and Llama 4 Scout costs $0.2600. Llama 4 Scout is 99% cheaper for this pattern. For your exact ratio, paste a real prompt into the calculator above.
GPT-5.5 has a 1.1M-token context window — approximately 788K 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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