As of August 20, 2026, Llama 4 Scout is 76% cheaper per million tokens than K-EXAONE-236B-A23B. K-EXAONE-236B-A23B is $0.60 / $1.00 per million input/output tokens versus Llama 4 Scout at $0.08 / $0.30. Sources: https://anotherwrapper.com/tools/llm-pricing and https://llama.meta.com/
Sources: AnotherWrapper LLM pricing (https://anotherwrapper.com/tools/llm-pricing); Meta pricing (https://llama.meta.com/)
K-EXAONE-236B-A23B
LG AI Research
Input
$0.60
Output
$1.00
Llama 4 Scout
Meta
Input
$0.08
Output
$0.30
Token pricing, specs, and benchmarks side by side
K-EXAONE-236B-A23BLlama 4 ScoutVerdict
Llama 4 Scout offers significantly lower pricing, while K-EXAONE-236B-A23B leads on benchmark performance. Your choice depends on whether cost efficiency or raw capability matters more for your use case.
As of August 20, 2026, Llama 4 Scout is 76% cheaper on blended LLM API pricing. Llama 4 Scout costs $0.08 per million input tokens and $0.30 per million output tokens ($0.38 blended 1M-in + 1M-out). K-EXAONE-236B-A23B costs $0.60 / $1.00 per million tokens ($1.60 blended). Sources: https://anotherwrapper.com/tools/llm-pricing and https://llama.meta.com/. The cheapest LLM for your app still depends on how many output tokens you generate.
K-EXAONE-236B-A23B LG AI Research API pricing is $0.60 input and $1.00 output per million tokens via LG AI Research. Llama 4 Scout Meta API pricing is $0.08 input and $0.30 output per million tokens via Meta. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Llama 4 Scout has a published LiveCodeBench score of 32.8%. K-EXAONE-236B-A23B does not have that eval on this page yet.
K-EXAONE-236B-A23B supports a 33K token context window, while Llama 4 Scout supports 10M tokens. Llama 4 Scout offers a larger context window. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.
K-EXAONE-236B-A23B leads on 1 of 1 shared benchmarks versus Llama 4 Scout's 0 wins. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.
Both K-EXAONE-236B-A23B and Llama 4 Scout are production API models. For cost-sensitive production traffic, Llama 4 Scout has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.
Yes. Call K-EXAONE-236B-A23B through LG AI Research and Llama 4 Scout through Meta with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.
List rates are the latest published LG AI Research API pricing and Meta API pricing, quoted per million tokens. Official rate sheets: https://anotherwrapper.com/tools/llm-pricing and https://llama.meta.com/. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.
K-EXAONE-236B-A23B supports up to 33K output tokens per request, while Llama 4 Scout supports up to 10M output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
K-EXAONE-236B-A23B runs at approximately 50 tokens/second while Llama 4 Scout runs at 76.1 tokens/second. Llama 4 Scout is faster in raw throughput. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open K-EXAONE-236B-A23B or Llama 4 Scout from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
This comparison covers API pricing, context window, throughput, and benchmark scores. K-EXAONE-236B-A23B costs $0.60/M input and $1.00/M output. Llama 4 Scout costs $0.08/M input and $0.30/M output.
Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.
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