Which is cheaper, GPT-5.6 Luna or Nemotron Nano 9B v2?
As of August 20, 2026, Nemotron Nano 9B v2 is 100% cheaper on blended LLM API pricing. Nemotron Nano 9B v2 costs $0.00 per million input tokens and $0.00 per million output tokens ($0.00 blended 1M-in + 1M-out). GPT-5.6 Luna costs $0.20 / $1.20 per million tokens ($1.40 blended). Sources: https://developers.openai.com/api/docs/pricing and https://openrouter.ai/api/v1/models. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does GPT-5.6 Luna vs Nemotron Nano 9B v2 cost per million tokens?
GPT-5.6 Luna OpenAI API pricing is $0.20 input and $1.20 output per million tokens via OpenAI. Nemotron Nano 9B v2 OpenRouter API pricing is $0.00 input and $0.00 output per million tokens via OpenRouter. 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 Nemotron Nano 9B v2?
GPT-5.6 Luna has a published SWE-bench Verified score of 93%. Nemotron Nano 9B v2 does not have that eval on this page yet.
What is the context window for GPT-5.6 Luna vs Nemotron Nano 9B v2?
GPT-5.6 Luna supports a 1M token context window, while Nemotron Nano 9B v2 supports 128K tokens. GPT-5.6 Luna 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-5.6 Luna or Nemotron Nano 9B v2?
GPT-5.6 Luna and Nemotron Nano 9B v2 are tied across 2 shared benchmarks. Check the table for category-level strengths. 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 Nemotron Nano 9B v2 better for production use?
Both GPT-5.6 Luna and Nemotron Nano 9B v2 are production API models. For cost-sensitive production traffic, Nemotron Nano 9B v2 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 Nemotron Nano 9B v2 in my app?
Yes. Call GPT-5.6 Luna through OpenAI and Nemotron Nano 9B v2 through OpenRouter 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 Nemotron Nano 9B v2 pricing data?
List rates are the latest published OpenAI API pricing and OpenRouter API pricing, quoted per million tokens. Official rate sheets: https://developers.openai.com/api/docs/pricing and https://openrouter.ai/api/v1/models. 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 Nemotron Nano 9B v2?
GPT-5.6 Luna supports up to 128K output tokens per request, while Nemotron Nano 9B v2 supports up to an unspecified number of 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 Nemotron Nano 9B v2?
GPT-5.6 Luna has a measured throughput of approximately 48.45216448188169 tokens/second. Throughput data for Nemotron Nano 9B v2 is not yet available. 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 Nemotron Nano 9B v2 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 Nemotron Nano 9B v2 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
