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GPT-5.2 vs Llama 4 Scout 17b 16e

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.

OpenAI

Model

GPT-5.2

Image inputTool calling

Best $1.75 in · $14.00 out

Context window 272K

Pricing
Meta

Model

Llama 4 Scout 17b 16e

Tool calling

Best $0.050 in · $0.100 out

Context window 328K

Pricing

Llama 4 Scout 17b 16e is cheaper across the board — 97% 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.

ProviderGPT-5.2 inGPT-5.2 outLlama 4 Scout 17b 16e inLlama 4 Scout 17b 16e out
Azure$1.75$14.00$0.200$0.780
DeepInfraN/AN/A$0.080$0.300
Github CopilotN/AN/AN/AN/A
Gmi$1.75$14.00N/AN/A
GroqN/AN/A$0.110$0.340
LambdaN/AN/A$0.050$0.100
NovitaN/AN/A$0.180$0.590
NscaleN/AN/A$0.090$0.290
OpenAI$1.75$14.00N/AN/A
Openrouter$1.75$14.00N/AN/A
SambanovaN/AN/A$0.400$0.700
Together AIN/AN/A$0.180$0.590
WandbN/AN/A$17000.00$66000.00

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.

ListedoutputUSD/1M

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

ListedoutputUSD/1M

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.

Spec
GPT-5.2
Llama 4 Scout 17b 16e
Context window
272,000 tokens
327,680 tokens
Max output tokens
128,000 tokens
327,680 tokens
Vision
Yes
No
Function calling
Yes
Yes
Streaming
No
No
Release date
Dec 2025
N/A

Cost calculator

Same requests, input tokens, and output tokens for both columns. Pick the provider row that matches how you buy.

GPT-5.2
Monthly
$2.6K
Annual
$31.9K
Llama 4 Scout 17b 16e
Monthly
$143
Annual
$1.7K
Save $2.5K/month with Llama 4 Scout 17b 16e

When to pick which

Short takeaways: no cards, just the points. Validate with your own workloads.

  • Long-context tasks

    Use Llama 4 Scout 17b 16e. Its 327K context window handles large codebases and documents better than 272K.

  • High-volume text generation

    Use Llama 4 Scout 17b 16e. Output tokens are 99% cheaper, which compounds significantly at scale.

  • Long output (reports, code files)

    Use Llama 4 Scout 17b 16e. Its 327K max output limit reduces the need to split requests.

Frequently asked questions

Llama 4 Scout 17b 16e is cheaper on both input and output tokens.

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