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Model comparison

Gemini 3.6 Flash vs GPT-6 Luna

Google against OpenAI, compared on context, price, and attributed benchmark results.

Recorded profile verification October 1, 2026Individual provider fields may changeEvidence confidence: Medium — see receipts below

Google

Gemini 3.6 Flash

Balanced

vs

OpenAI

GPT-6 Luna

Budget

AI model capability comparison
SpecificationGemini 3.6 FlashGPT-6 Luna
ProviderGoogleOpenAI
TierBalancedBudget
Context window1.05MWinner: 1.05M
Max output66KWinner: 128K
Input / 1M tokens$0.75Winner: $0.10
Output / 1M tokens$3.75Winner: $0.50
WeightsClosedClosed
ParametersNot verifiedUnverifiedNot verifiedUnverified
Reasoning levelsminimal, low, medium, highnone, low, medium, high, xhigh, max
Modalitiestext, image, video, audio, pdftext, image
API model idgemini-3.6-flashgpt-6-luna
ReleasedJuly 21, 2026September 22, 2026
Terminal-Bench 2.1 · source date Gemini 3.6 Flash: 2026-0778Not verifiedUnverified
DeepSWE 1.1 · source date Gemini 3.6 Flash: 2026-0848.6Not verifiedUnverified
DeepSWE 1.1 [max] · source date GPT-6 Luna: 2026-09-22Not verifiedUnverified66.6
HLE-Verified · source date Gemini 3.6 Flash: 2026-0851.2Not verifiedUnverified

Dates beside benchmark scores refer to the linked source’s publication or capture date unless that source explicitly states when it measured the result. A shared URL alone does not establish comparable runs; unverified setups are marked. Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.

Benchmark receipts

Where each score comes from, and how far it can be compared across models.

Pricing tiers

Gemini 3.6 Flash: Intro Standard $0.75/$3.75 per MTok through December 31, 2026; $1.50/$7.50 from January 1, 2027. Output includes thinking tokens. Cached input $0.075, rising to $0.15; storage $0.50/MTok-hour, rising to $1. Batch/Flex input/output are $0.375/$1.875, rising to $0.75/$3.75. Priority $1.35/$6.75, rising to $2.70/$13.50. Grounding tools have separate charges and quotas; free-tier limits differ from paid.

GPT-6 Luna: Standard $0.10/$0.50 per MTok, compared with GPT-5.6 Luna’s $0.20/$1.20. Cached input $0.01 and cache writes $0.125. Above 272K the full request bills $0.20/$0.75, cached $0.02 and cache writes $0.25. Batch/Flex are half Standard; Fast is 2x. Regional/FedRAMP processing adds 10% where eligible. Knowledge cutoff May 18 2026.

BalancedRecord checked October 1, 2026

Gemini 3.6 Flash

Gemini 3.6 Flash is Google's balanced multimodal Flash tier with a 1M-token context.

Best for

  • Multimodal pipelines
  • High-volume processing
  • Video and audio input

Watch out

An earlier Flash model, still listed as stable. Google reports improvements on selected tasks for later releases; that does not establish a quality increase for every workload. Thinking includes minimal through high; computer use is Preview. Intro pricing doubles January 1, 2027.

BudgetRecord checked October 1, 2026

GPT-6 Luna

OpenAI’s GPT-6 budget tier for focused, high-volume tasks, with text/image input, text output and a 1.05M-token context at $0.10/$0.50 per million tokens.

Best for

  • High-volume chat and extraction
  • Classification
  • Cost-capped agent loops

Watch out

Use Responses for tools; Chat Completions supports function calling only with reasoning_effort none. A September 25 image-encoding fix can affect older visual evaluations. The DeepSWE result is vendor-reported at max effort; an index score alone does not establish quality on your tasks.

When the cheaper one wins

GPT-6 Luna is cheaper on output at $0.50 per million tokens against $3.75 for Gemini 3.6 Flash — about 7.5×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. This compares standard short-context token rates, not total cost per accepted task. Include input, cache, context tiers, schedules, retries and review in your pilot.

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Evidence confidence: Medium

How strong and complete the evidence behind this comparison is — not a prediction of which model is better.

  • Pricing verified on both sides — Input and output rates are verified for both models.
  • 4/5 core specs verified on both sides — Not published for at least one side: parameter count.
  • No directly aligned benchmark setup — No benchmark has matching cited sources, source dates, units, effort and recorded run details on both models.
  • Verified within the last 90 days — Older of the two catalog checks was 25 days ago.
  • Both models carry source citations — Each side has at least two catalog sources on record.

Source receipts

Each catalog figure was checked against the provider or an independent second source on the date shown.

Related comparisons

Diving deeper on one model? Gemini 3.6 Flash · GPT-6 Luna

Common questions

Gemini 3.6 Flash vs GPT-6 Luna

Answered from the verified figures on this page rather than general guidance.

Is Gemini 3.6 Flash or GPT-6 Luna cheaper for input?
GPT-6 Luna is cheaper at $0.10 per million input tokens, against $0.75 for Gemini 3.6 Flash — roughly 7.5× the price. Estimate both input and output token volume for your workload. These are base rates; Gemini 3.6 Flash: Intro Standard $0.75/$3.75 per MTok through December 31, 2026; $1.50/$7.50 from January 1, 2027. Output includes thinking tokens. Cached input $0.075, rising to $0.15; storage $0.50/MTok-hour, rising to $1. Batch/Flex input/output are $0.375/$1.875, rising to $0.75/$3.75. Priority $1.35/$6.75, rising to $2.70/$13.50. Grounding tools have separate charges and quotas; free-tier limits differ from paid. GPT-6 Luna: Standard $0.10/$0.50 per MTok, compared with GPT-5.6 Luna’s $0.20/$1.20. Cached input $0.01 and cache writes $0.125. Above 272K the full request bills $0.20/$0.75, cached $0.02 and cache writes $0.25. Batch/Flex are half Standard; Fast is 2x. Regional/FedRAMP processing adds 10% where eligible. Knowledge cutoff May 18 2026.
Is Gemini 3.6 Flash or GPT-6 Luna cheaper for output?
GPT-6 Luna is cheaper at $0.50 per million output tokens, against $3.75 for Gemini 3.6 Flash — roughly 7.5× the price. Estimate both input and output token volume for your workload. These are base rates; Gemini 3.6 Flash: Intro Standard $0.75/$3.75 per MTok through December 31, 2026; $1.50/$7.50 from January 1, 2027. Output includes thinking tokens. Cached input $0.075, rising to $0.15; storage $0.50/MTok-hour, rising to $1. Batch/Flex input/output are $0.375/$1.875, rising to $0.75/$3.75. Priority $1.35/$6.75, rising to $2.70/$13.50. Grounding tools have separate charges and quotas; free-tier limits differ from paid. GPT-6 Luna: Standard $0.10/$0.50 per MTok, compared with GPT-5.6 Luna’s $0.20/$1.20. Cached input $0.01 and cache writes $0.125. Above 272K the full request bills $0.20/$0.75, cached $0.02 and cache writes $0.25. Batch/Flex are half Standard; Fast is 2x. Regional/FedRAMP processing adds 10% where eligible. Knowledge cutoff May 18 2026.
Which has the larger context window, Gemini 3.6 Flash or GPT-6 Luna?
Both accept about 1.05M tokens of context, so document length will not decide between them.
Do Gemini 3.6 Flash and GPT-6 Luna support the same reasoning levels?
Gemini 3.6 Flash exposes minimal, low, medium, high, while GPT-6 Luna exposes none, low, medium, high, xhigh, max.
Should I use Gemini 3.6 Flash or GPT-6 Luna?
We classify Gemini 3.6 Flash in the balanced tier and GPT-6 Luna in the budget tier. Test whether either meets your accuracy, tool-use and latency requirements before choosing on price.

Next step

Choosing between them

The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.

  • Input price: GPT-6 Luna costs $0.10 per 1M tokens versus $0.75 for Gemini 3.6 Flash — a 7.5x difference at the headline tier.
  • Context: GPT-6 Luna takes 1.05M against 1.05M for Gemini 3.6 Flash — only decisive if your prompts approach the smaller window.
  • Positioning: Gemini 3.6 Flash sits in the balanced tier, GPT-6 Luna in the budget tier. Compare accuracy, reliability, latency, and cost on representative tasks before choosing.
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