GPT-6 Luna
- Context
- 1,050,000
- Max output
- 128,000
- Input / MTok
- $0.10
- Cached / MTok
- $0.01
- Output / MTok
- $0.50
- Input types
- text + image
HIGH-VOLUME ECONOMICS / VERIFIED 2026-10-04
GPT-6 Luna
vs Gemini 3.7 Flash
Compare lower-cost OpenAI and Google models on Standard token rates, context capacity, output limits and multimodal input.
LIVE VERIFIED FACTS
Current facts from the SXF model database.
Gemini 3.7 Flash
- Context
- 1,048,576
- Max output
- 65,536
- Input / MTok
- $0.75
- Cached / MTok
- $0.075
- Output / MTok
- $3.75
- Input types
- text + image + video + audio + PDF
Facts are generated from the canonical model catalog, not copied into this comparison.Current data ↗Change ledger ↗
DECISION FACTORS
What materially changes the choice.
Context capacity
GPT-6 Luna publishes the larger context window: 1,050,000 vs 1,048,576 tokens (1.0×).
Input modalities
Gemini 3.7 Flash additionally lists PDF, audio, video.
Direct token cost
For 100K uncached input + 10K output tokens, GPT-6 Luna is lower at $0.015 vs $0.1125 (7.5× difference).
Output policy
GPT-6 Luna: 128,000. Gemini 3.7 Flash: 65,536.
HOW TO DECIDE
Specifications narrow the field. Your workload decides.
Context, modalities and direct token economics are comparable from official sources. Coding quality, latency, reliability and agent success should be measured on your own acceptance tests before production routing.
Replay real tasks
Use representative prompts, files, tools and expected outputs from the workload you plan to ship.
Measure task cost
Include retries, cached tokens, long-context rules and tool charges—not only headline input price.
Track failures
Record hallucinations, tool errors, timeout behavior and human corrections alongside pass rate.
Route by task
A portfolio can outperform a one-model policy when different task classes have different cost and capability needs.
INDEPENDENT EVALUATIONS
No directly comparable independent result yet.
SXF does not infer quality from specifications or compare benchmark scores across different evaluator versions/configurations.
WHAT CHANGED
Changes affecting this comparison.
No post-baseline factual changes recorded for GPT-6 Luna, Gemini 3.7 Flash since 2026-09-27.
VERIFIED BASELINE2026-09-27Current facts remain aligned with the SXF ledger.
QUICK ANSWERS
Which has the larger context window: GPT-6 Luna or Gemini 3.7 Flash?
GPT-6 Luna publishes the larger context window: 1,050,000 vs 1,048,576 tokens (1.0×).
Which is cheaper: GPT-6 Luna or Gemini 3.7 Flash?
For 100K uncached input + 10K output tokens, GPT-6 Luna is lower at $0.015 vs $0.1125 (7.5× difference).
Does SXF declare an overall winner?
No. This page compares source-backed specifications and economics. Quality, latency and task success require workload-specific evaluation evidence.