Which is cheaper, GPT-5.6 Luna or GPT-5.6 Sol?
As of August 20, 2026, GPT-5.6 Luna is 96% cheaper on blended LLM API pricing. GPT-5.6 Luna costs $0.20 per million input tokens and $1.20 per million output tokens ($1.40 blended 1M-in + 1M-out). GPT-5.6 Sol costs $5.00 / $30.00 per million tokens ($35.00 blended). Sources: https://developers.openai.com/api/docs/pricing and https://developers.openai.com/api/docs/pricing. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does GPT-5.6 Luna vs GPT-5.6 Sol cost per million tokens?
GPT-5.6 Luna OpenAI API pricing is $0.20 input and $1.20 output per million tokens via OpenAI. GPT-5.6 Sol OpenAI API pricing is $5.00 input and $30.00 output per million tokens via OpenAI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, GPT-5.6 Luna or GPT-5.6 Sol?
GPT-5.6 Sol leads on SWE-bench Verified: GPT-5.6 Luna at 93% vs GPT-5.6 Sol at 96.2%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
What is the context window for GPT-5.6 Luna vs GPT-5.6 Sol?
GPT-5.6 Luna supports a 1M token context window, while GPT-5.6 Sol supports 1M tokens. Both models have the same context window size. 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-5.6 Luna or GPT-5.6 Sol?
GPT-5.6 Sol leads on 69 of 72 shared benchmarks versus GPT-5.6 Luna's 3 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-5.6 Luna or GPT-5.6 Sol better for production use?
Both GPT-5.6 Luna and GPT-5.6 Sol are production API models. For cost-sensitive production traffic, GPT-5.6 Luna 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-5.6 Luna and GPT-5.6 Sol in my app?
Yes. Call GPT-5.6 Luna through OpenAI and GPT-5.6 Sol through OpenAI 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-5.6 Luna vs GPT-5.6 Sol pricing data?
List rates are the latest published OpenAI API pricing and OpenAI API pricing, quoted per million tokens. Official rate sheets: https://developers.openai.com/api/docs/pricing and https://developers.openai.com/api/docs/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-5.6 Luna and GPT-5.6 Sol?
GPT-5.6 Luna supports up to 128K output tokens per request, while GPT-5.6 Sol supports up to 128K 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-5.6 Luna or GPT-5.6 Sol?
GPT-5.6 Luna runs at approximately 48.45216448188169 tokens/second while GPT-5.6 Sol runs at 26.722697498416323 tokens/second. GPT-5.6 Luna 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-5.6 Luna vs GPT-5.6 Sol comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open GPT-5.6 Luna or GPT-5.6 Sol from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
