GPT-5.6 Luna or Gemini 3.8 Flash?
Choose GPT-5.6 Luna when high-volume extraction, classification and routine agent tasks is the closer match. Choose Gemini 3.8 Flash when real-time developer assistance, automated patching and high-volume extraction matters more. Test both on the same real tasks before moving a production workflow.
High-volume extraction, classification and routine agent tasks
Real-time developer assistance, automated patching and high-volume extraction
GPT-5.6 Luna
GPT-5.6 model optimized for cost-sensitive, high-volume workloads.
Official specification ↗Gemini 3.8 Flash
Google's fast, cost-efficient model for high-frequency coding and tool-calling agents.
Official specification ↗Side-by-side comparison
| Category | GPT-5.6 Luna | Gemini 3.8 Flash |
|---|---|---|
| Provider | OpenAI | |
| Type | Model · Reasoning model | Model · Fast model |
| Pricing summary | $0.20 input, $0.02 cached input and $1.20 output per 1M tokens | $0.75 input, $0.075 cached input and $3.75 output per 1M tokens |
| Input price | $0.20 / 1M tokens | $0.75 / 1M tokens |
| Cached input | $0.02 / 1M tokens | $0.075 / 1M tokens |
| Output price | $1.20 / 1M tokens | $3.75 / 1M tokens |
| Context window | 1.05M tokens | 1M tokens |
| Maximum output | 128K tokens | 64K tokens |
| Knowledge cutoff | February 16, 2026 | July 2026 |
| Reasoning | none, low, medium, high, xhigh, max | Configurable thinking budget |
| Relative speed | Fast / cost optimized | Ultra fast |
| Input modalities | Text and image | Text, image, audio, video |
| Output modalities | Text | Text and code |
| Tools and integrations | Functions, web search, file search, computer use and supported Responses API tools | Function calling, code execution, Google Search grounding |
| API / access | v1/responses, v1/chat/completions and v1/batch | Gemini API & Vertex AI |
| Best fit | High-volume extraction, classification and routine agent tasks | Real-time developer assistance, automated patching and high-volume extraction |
| Company | OpenAI | |
| Product category | Model · Reasoning model | Model · Fast model |
| Current pricing note | $0.20 input, $0.02 cached input and $1.20 output per 1M tokens | $0.75 input, $0.075 cached input and $3.75 output per 1M tokens |
| Best suited to | High-volume extraction, classification and routine agent tasks | Real-time developer assistance, automated patching and high-volume extraction |
| Key capabilities | 1.05M context; 128K maximum output; Vision input; Responses API tools | 1M context window; Configurable thinking mode; Native audio/video processing; Fast coding throughput |
| Last verified | 2026-09-08 | 2026-09-08 |
| Official product source | https://developers.openai.com/api/docs/models/gpt-5.6-luna | https://ai.google.dev/gemini-api/docs/models/gemini-3.8-flash |
How we reached this verdict
We looked at the things that affect everyday use: what each product can do, how its plans are structured, where it fits into your existing workflow, and what the provider currently documents. Benchmark results are useful context, but they are not a universal winner score because test settings and tools vary.
Common questions
GPT-5.6 Luna or Gemini 3.8 Flash: which should I choose?
Choose GPT-5.6 Luna for high-volume extraction, classification and routine agent tasks. Choose Gemini 3.8 Flash for real-time developer assistance, automated patching and high-volume extraction. Validate the decision with your own prompts and total task cost.
Is GPT-5.6 Luna cheaper than Gemini 3.8 Flash?
Pricing units can differ. GPT-5.6 Luna: $0.20 input, $0.02 cached input and $1.20 output per 1M tokens. Gemini 3.8 Flash: $0.75 input, $0.075 cached input and $3.75 output per 1M tokens. Check tool charges, plan limits, caching and long-context rules before comparing totals.
Which is better for coding and agent work?
Capability depends on the selected product surface, tools and harness. GPT-5.6 Luna is positioned for high-volume extraction, classification and routine agent tasks; Gemini 3.8 Flash is positioned for real-time developer assistance, automated patching and high-volume extraction. Run the same repository task on both.
How do their context windows compare?
GPT-5.6 Luna lists 1.05M tokens; Gemini 3.8 Flash lists 1M tokens. A larger limit does not by itself guarantee better retrieval or lower cost.
Official sources
Use these provider pages to confirm current features, pricing and availability.
AI tools change quickly. We checked this page on 2026-09-08. Before you subscribe, confirm the latest price, regional availability and usage limits on the provider website.