Skip to main content
AI Choice Engine

Model comparison

Gemini 3.5 Flash-Lite vs GPT-5.6 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 3.5 Flash-Lite

Budget

vs

OpenAI

GPT-5.6 Luna

Budget

AI model capability comparison
SpecificationGemini 3.5 Flash-LiteGPT-5.6 Luna
ProviderGoogleOpenAI
TierBudgetBudget
Context window1.05MWinner: 1.05M
Max output66KWinner: 128K
Input / 1M tokens$0.30Winner: $0.20
Output / 1M tokens$2.50Winner: $1.20
WeightsClosedClosed
ParametersNot verifiedUnverifiedNot verifiedUnverified
Reasoning levelsminimal, low, medium, highnone, low, medium, high, xhigh, max
Modalitiestext, image, video, audio, pdftext, image
API model idgemini-3.5-flash-litegpt-5.6-luna
ReleasedJuly 21, 2026July 9, 2026
Artificial Analysis Intelligence Index · source date Gemini 3.5 Flash-Lite: 2026-10-0122Not verifiedUnverified
Terminal-Bench 2.1 · source date GPT-5.6 Luna: 2026-07-09Not verifiedUnverified84.7
LiveBench · source date GPT-5.6 Luna: 2026-09-05Not verifiedUnverified73.6

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.

  • Source date2026-10-01
    Artificial Analysis (Gemini 3.5 Flash-Lite)

    Composite index blending reasoning, knowledge, and coding evals into one 0–100 score.

    Comparable with caveatOnly same-version scores are comparable. v4.3.2 was rebaselined (the top score fell from 66 on v4.1.1 to ~58), so v4.1.1 figures must not be compared with v4.3.2 figures — check the cited source and its date.

  • Source date2026-09-05
    LiveBench official leaderboard (benchmark-owned), max effort

    Contamination-resistant general capability across reasoning, coding, math, data analysis, and language, with monthly question refreshes.

    Comparable with caveatCompare only observations confirmed to use the same exact question-set version. Date proximity (including within one month) does not establish identical questions; when the version is unavailable, treat the scores as unaligned.

  • Source date2026-07-09
    OpenAI GPT-5.6 launch table (vendor-reported; effort and experiment date unspecified) (Vendor launch table; complete common run settings unverified)

    Agentic terminal work: multi-step tasks executed in a sandboxed shell environment.

    Comparable with caveatNot comparable with Terminal-Bench 3.0 or 4.0 (different task sets) or v1; harness configuration (container, time limits) also shifts results.

Pricing tiers

Gemini 3.5 Flash-Lite: Standard $0.30 input for text/image/video/audio and $2.50 output including thinking per MTok. Cached input $0.03 plus $1/MTok-hour storage. Batch/Flex $0.15/$1.25 with published cached input $0.02. Priority $0.54/$4.50, cached $0.05. Grounding tools have separate charges/quotas. The older 3.1 Flash-Lite has modality-dependent input rates.

GPT-5.6 Luna: Launch $1/$6, reduced to $0.20/$1.20 on July 30. Above 272K input the full request bills $0.40/$1.80. Cached input $0.02; cache writes $0.25 at short context. Batch $0.10/$0.60 at short context. Regional/FedRAMP processing adds 10% where eligible.

BudgetRecord checked October 1, 2026

Gemini 3.5 Flash-Lite

Gemini 3.5 Flash-Lite is Google's recommended Flash-Lite tier for high-volume, latency-sensitive agent loops.

Best for

  • High-volume agents
  • Document pipelines
  • Cost-sensitive multimodal

Watch out

Compare input modality: 3.1 Flash-Lite is $0.25 for text/image/video but $0.50 for audio, versus this model's $0.30 for either. Thinking includes minimal through high; computer use is Preview. Price alone does not establish quality on reasoning tasks.

BudgetRecord checked October 1, 2026

GPT-5.6 Luna

OpenAI’s GPT-5.6 budget tier, succeeded by GPT-6 Luna on September 22. The newer model halves input pricing ($0.20→$0.10) and lowers output pricing from $1.20 to $0.50.

Best for

  • Classification
  • High-volume chat
  • Latency-sensitive pipelines

Watch out

Superseded by GPT-6 Luna and still listed in the API. Historical index captures are not current evidence of equal quality; the successor has lower Standard input and output prices.

When the cheaper one wins

GPT-5.6 Luna is cheaper on output at $1.20 per million tokens against $2.50 for Gemini 3.5 Flash-Lite — about 2.1×. 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.

Run the model picker

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 3.5 Flash-Lite · GPT-5.6 Luna

Common questions

Gemini 3.5 Flash-Lite vs GPT-5.6 Luna

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

Is Gemini 3.5 Flash-Lite or GPT-5.6 Luna cheaper for input?
GPT-5.6 Luna is cheaper at $0.20 per million input tokens, against $0.30 for Gemini 3.5 Flash-Lite — roughly 1.5× the price. Estimate both input and output token volume for your workload. These are base rates; Gemini 3.5 Flash-Lite: Standard $0.30 input for text/image/video/audio and $2.50 output including thinking per MTok. Cached input $0.03 plus $1/MTok-hour storage. Batch/Flex $0.15/$1.25 with published cached input $0.02. Priority $0.54/$4.50, cached $0.05. Grounding tools have separate charges/quotas. The older 3.1 Flash-Lite has modality-dependent input rates. GPT-5.6 Luna: Launch $1/$6, reduced to $0.20/$1.20 on July 30. Above 272K input the full request bills $0.40/$1.80. Cached input $0.02; cache writes $0.25 at short context. Batch $0.10/$0.60 at short context. Regional/FedRAMP processing adds 10% where eligible.
Is Gemini 3.5 Flash-Lite or GPT-5.6 Luna cheaper for output?
GPT-5.6 Luna is cheaper at $1.20 per million output tokens, against $2.50 for Gemini 3.5 Flash-Lite — roughly 2.1× the price. Estimate both input and output token volume for your workload. These are base rates; Gemini 3.5 Flash-Lite: Standard $0.30 input for text/image/video/audio and $2.50 output including thinking per MTok. Cached input $0.03 plus $1/MTok-hour storage. Batch/Flex $0.15/$1.25 with published cached input $0.02. Priority $0.54/$4.50, cached $0.05. Grounding tools have separate charges/quotas. The older 3.1 Flash-Lite has modality-dependent input rates. GPT-5.6 Luna: Launch $1/$6, reduced to $0.20/$1.20 on July 30. Above 272K input the full request bills $0.40/$1.80. Cached input $0.02; cache writes $0.25 at short context. Batch $0.10/$0.60 at short context. Regional/FedRAMP processing adds 10% where eligible.
Which has the larger context window, Gemini 3.5 Flash-Lite or GPT-5.6 Luna?
Both accept about 1.05M tokens of context, so document length will not decide between them.
Do Gemini 3.5 Flash-Lite and GPT-5.6 Luna support the same reasoning levels?
Gemini 3.5 Flash-Lite exposes minimal, low, medium, high, while GPT-5.6 Luna exposes none, low, medium, high, xhigh, max.
Should I use Gemini 3.5 Flash-Lite or GPT-5.6 Luna?
Both are classified in our budget tier; this editorial grouping does not imply equal capability. Gemini 3.5 Flash-Lite is a candidate for high-volume agents; GPT-5.6 Luna is a candidate for classification. Compare accuracy, tool reliability, latency and cost on representative tasks.

Next step

Choosing between them

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

  • Input price: GPT-5.6 Luna costs $0.20 per 1M tokens versus $0.30 for Gemini 3.5 Flash-Lite — a 1.5x difference at the headline tier.
  • Context: GPT-5.6 Luna takes 1.05M against 1.05M for Gemini 3.5 Flash-Lite — only decisive if your prompts approach the smaller window.
Run the model pickerEstimate stack costAll model comparisons

Choosing a harness rather than a model — Cursor, Copilot, Claude Code, Windsurf, or Lovable? Compare agentic harnesses · Latest releases.