Which is cheaper, GPT-4o mini or K-EXAONE-236B-A23B?
As of August 25, 2026, GPT-4o mini is 53% cheaper on blended LLM API pricing. GPT-4o mini costs $0.15 per million input tokens and $0.60 per million output tokens ($0.75 blended 1M-in + 1M-out). K-EXAONE-236B-A23B costs $0.60 / $1.00 per million tokens ($1.60 blended). Sources: https://developers.openai.com/api/docs/pricing and https://anotherwrapper.com/tools/llm-pricing. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does GPT-4o mini vs K-EXAONE-236B-A23B cost per million tokens?
GPT-4o mini OpenAI API pricing is $0.15 input and $0.60 output per million tokens via OpenAI. K-EXAONE-236B-A23B LG AI Research API pricing is $0.60 input and $1.00 output per million tokens via LG AI Research. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, GPT-4o mini or K-EXAONE-236B-A23B?
GPT-4o mini has a published SWE-bench Verified score of 8.7%. K-EXAONE-236B-A23B does not have that eval on this page yet.
What is the context window for GPT-4o mini vs K-EXAONE-236B-A23B?
GPT-4o mini supports a 128K token context window, while K-EXAONE-236B-A23B supports 33K tokens. GPT-4o mini 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.
Which model performs better on benchmarks, GPT-4o mini or K-EXAONE-236B-A23B?
K-EXAONE-236B-A23B leads on 2 of 2 shared benchmarks versus GPT-4o mini'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.
Is GPT-4o mini or K-EXAONE-236B-A23B better for production use?
Both GPT-4o mini and K-EXAONE-236B-A23B are production API models. For cost-sensitive production traffic, GPT-4o mini 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.
Can I switch between GPT-4o mini and K-EXAONE-236B-A23B in my app?
Yes. Call GPT-4o mini through OpenAI and K-EXAONE-236B-A23B through LG AI Research 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.
How accurate is this GPT-4o mini vs K-EXAONE-236B-A23B pricing data?
List rates are the latest published OpenAI API pricing and LG AI Research API pricing, quoted per million tokens. Official rate sheets: https://developers.openai.com/api/docs/pricing and https://anotherwrapper.com/tools/llm-pricing. 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.
What is the output token limit for GPT-4o mini and K-EXAONE-236B-A23B?
GPT-4o mini supports up to 16K output tokens per request, while K-EXAONE-236B-A23B supports up to 33K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Which model has better throughput, GPT-4o mini or K-EXAONE-236B-A23B?
GPT-4o mini runs at approximately 92 tokens/second while K-EXAONE-236B-A23B runs at 50 tokens/second. GPT-4o mini 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.
How do I switch the models in this GPT-4o mini vs K-EXAONE-236B-A23B comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open GPT-4o mini or K-EXAONE-236B-A23B from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
