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GPT-4 vs Llama 4 Scout
Pricing is only the shared seller matrix below. Best rates and catalog map are separate sections, so no chart is embedded in pricing. Open the calculator for the same workload on each side.
Llama 4 Scout is cheaper across the board — 99% cheaper on input and 99% cheaper on output.
Pricing matrix
Shared sellers only. Each row is a host that lists both models. Dollar amounts are per 1M tokens. Lowest in each pair of columns is emphasized.
| Provider | GPT-4 in | GPT-4 out | Llama 4 Scout in | Llama 4 Scout out |
|---|---|---|---|---|
| Azure | $30.00 | $60.00 | N/A | N/A |
| Github Copilot | N/A | N/A | N/A | N/A |
| OpenAI | $30.00 | $60.00 | N/A | N/A |
| Openrouter | $10.00 | $30.00 | $0.080 | $0.300 |
| Vercel Ai Gateway | $10.00 | $30.00 | $0.100 | $0.300 |
Best listed rates (this pair)
Same "best row in current pricing" logic as model pages: a compact view of the lowest input and output we show for each side. This is not the seller matrix.
Catalog map · OpenAI · Meta
Each chart uses real catalog rows that include both list input and list output ($/1M). Larger green dots are the models on this comparison page; accent dots are other active models from that provider.
OpenAI · input vs output
Scatter chart: X = input $/M, Y = output $/M. This page's models are labeled on the green dots; hover others for detail.
One dot per catalog row that has both list prices. Green dots are labeled with the models on this page; hover any dot for name and prices. Upper-right means higher cost on both axes ($/1M).
Meta · input vs output
One dot per catalog row that has both list prices. Green dots are labeled with the models on this page; hover any dot for name and prices. Upper-right means higher cost on both axes ($/1M).
Specifications
Each column header is the full model name. Tint marks the favorable value where we compute a winner.
- Context window
- 8,192 tokens
- 131,072 tokens
- Max output tokens
- 4,096 tokens
- 8,192 tokens
- Vision
- No
- Yes
- Function calling
- Yes
- Yes
- Streaming
- No
- No
- Release date
- May 2023
- Apr 2025
Cost calculator
Same requests, input tokens, and output tokens for both columns. Pick the provider row that matches how you buy.
When to pick which
Short takeaways: no cards, just the points. Validate with your own workloads.
Long-context tasks
Use Llama 4 Scout. Its 131K context window handles large codebases and documents better than 8K.
High-volume text generation
Use Llama 4 Scout. Output tokens are 99% cheaper, which compounds significantly at scale.
Long output (reports, code files)
Use Llama 4 Scout. Its 8K max output limit reduces the need to split requests.
Frequently asked questions
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