Model comparison
Compare GPT-5.6 Luna and NVIDIA Nemotron 3.5 Lightning using the same provider-sourced text & reasoning rubric. No mystery score and no invented benchmark ranking.
Facts checked September 14, 2026
Set your usage. Your estimate updates as you type.
Example: 6,000 input tokens for 10 pages, plus a 500-token summary. Page lengths vary; adjust the numbers below.
One run sends your input to the model once and receives an answer. Tokens are pieces of text: input is what you send, output is the answer you receive.
Estimates exclude taxes, tools, cache storage/writes, free allowances and custom discounts. Image estimates cover output only, not prompt or reference-image charges. Quality modes differ by model. Unlisted settings are not treated as free.
| Model | Access | Estimated total (USD) |
|---|---|---|
| GPT-5.6 LunaOpenAI | OpenAI | $0.0018 |
| NVIDIA Nemotron 3.5 LightningNVIDIA | NVIDIA | No reviewed rate |
Quick take
The budget GPT-5.6 tier for processing many short, repeatable tasks.
Low token prices do not guarantee a low task cost if the model needs retries or extensive reasoning.
NVIDIA's compact 30B mixture-of-experts model for efficient specialist agents and high-volume text workflows.
The current release is labeled preview. Validate the exact precision, language, tool template, provider route, and long-context memory needs before standardizing a production fleet.
Compare the published facts
Values use each provider's own published units and limits. A blank means the provider did not publish a directly comparable value in the sources reviewed.
| Text & reasoning | GPT-5.6 Luna | NVIDIA Nemotron 3.5 Lightning |
|---|---|---|
| Context windowMaximum combined prompt and working context documented by the provider. | 1.05M tokens | Up to 1M tokens |
| Maximum outputProvider-published response limit, where available. | 128K tokens | Not separately published |
| Knowledge cutoffLatest reliable knowledge date explicitly published by the model provider. Search and connected tools can retrieve newer information but do not change the model's built-in cutoff. | February 16, 2026 | Pretraining through Sep 2025; post-training through May 2026 |
| Input priceCurrent standard list price per million input tokens unless noted. | $0.2 / 1M | Free prototype or deployment cost |
| Output priceCurrent standard list price per million output tokens unless noted. | $1.2 / 1M | Free prototype or deployment cost |
| InputsMedia types accepted by the listed model endpoint. | Text, image | Text |
| Tools & agentsSelected native tools and agent-building capabilities, not an exhaustive list. | Functions, web/file search, code, computer, MCP | Agentic tools and long-running workflows |
How to choose
Start with the job you need to complete, then validate cost, access, and policy details on your exact provider route.
OpenAI says API inputs and outputs are not used for model training by default. Default abuse-monitoring logs may be retained for up to 30 days; qualifying organizations can request other controls.
Provider and API links
Self-hosted weights keep request data under the operator's controls. NVIDIA API trials, OpenRouter, and cloud partners each apply separate logging, retention, and training-use policies.
Provider and API links
Frequently asked questions
GPT-5.6 Luna: The budget GPT-5.6 tier for processing many short, repeatable tasks. NVIDIA Nemotron 3.5 Lightning: NVIDIA's compact 30B mixture-of-experts model for efficient specialist agents and high-volume text workflows.
Consider GPT-5.6 Luna when your priority is Data extraction. Consider NVIDIA Nemotron 3.5 Lightning when your priority is High-volume agent sub-tasks. Test both with your own data and provider route before committing.
No. This comparison aligns provider-published facts for the Text & reasoning category. It does not claim a universal winner or combine incompatible third-party benchmark scores.
