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Gemini 3.8 Flash vs GPT-5.6 Luna

Gemini 3.8 Flash leads GPT-5.6 Luna on coding, 61.6 to 58.0 on the Vibe Coding Index, and GPT-5.6 Luna costs 3.1x less per output token ($1.20 vs $3.75 per million). Updated October 22, 2026; 113 benchmarks have a result for both.

Replace Gemini 3.8 Flash Replace GPT-5.6 Luna
Gemini 3.8 FlashGoogle
Coding
61.6
Overall
69.0
Output $/M
$3.75
94
GPT-5.6 LunaOpenAI
Coding
58.0
Overall
61.6
Output $/M
$1.20
19
vs boards won of 113 shared

Gemini 3.8 Flash or GPT-5.6 Luna: which to pick

Pick Gemini 3.8 Flash for coding: it scores 61.6 on the Vibe Coding Index against 58.0 for GPT-5.6 Luna.

Pick GPT-5.6 Luna for output tokens 3.1x cheaper ($1.20 vs $3.75 per million) and a lower cost per solved task ($0.04 against $2.74).

Model AGemini 3.8 FlashGoogle61.6/1006 independent benchmarks$2.74 per solved taskModel BGPT-5.6 LunaOpenAI58.0/1006 independent benchmarks$0.04 per solved task
Shared results
113
Gemini 3.8 Flash only
15
GPT-5.6 Luna only
6
Like-for-like categories
8 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Gemini 3.8 Flash 61.6 from 6 benchmarks, GPT-5.6 Luna 58.0 from 6 benchmarks.
Widest category
Math, 14.3 points apart on average over 6 shared benchmarks.
Widest single gap
FrontierMath, tier 4: Gemini 3.8 Flash 22.0% against GPT-5.6 Luna 61.0%, 39.0 points apart on a 0 to 100 scale.
Output price
Gemini 3.8 Flash $3.75 against GPT-5.6 Luna $1.20 per million output tokens, 3.1x apart.
Context window
Gemini 3.8 Flash takes 1.05M tokens, GPT-5.6 Luna 1.05M.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryGemini 3.8 FlashBarsGPT-5.6 LunaTies
Coding167
Intelligence20
Agentic work113
Reasoning160
Math33
Knowledge92
Web design81
General293
All shared boards9419
CodingLike-for-likeSix of these boards feed the Vibe Coding Index167
Coding benchmarks for Gemini 3.8 Flash and GPT-5.6 Luna
BenchmarkGemini 3.8 FlashGPT-5.6 LunaLeader
LiveBench coding82.2%73.6%Gemini 3.8 Flash
LMArena WebDev15851518Gemini 3.8 Flash
AA Coding Index76.371.4Gemini 3.8 Flash
LiveCodeBench (Vals AI)89.5%Not measuredOnly Gemini 3.8 Flash measured
SWE-bench Verified (Vals AI)80.0%93.0%GPT-5.6 Luna
Terminal-Bench 4 (Vals AI)19.7%11.6%Gemini 3.8 Flash
Vibe Code Bench (Vals AI)78.7%77.1%Gemini 3.8 Flash
Code migration (Vals AI)36.5%44.5%GPT-5.6 Luna
ProgramBench (Vals AI)1.0%0.0%Gemini 3.8 Flash
IOI (Vals AI)56.9%61.8%GPT-5.6 Luna
Terminal-Bench 2.1 (Vals AI)81.3%79.0%Gemini 3.8 Flash
SWE-bench Multimodal (Vals AI)40.8%Not measuredOnly Gemini 3.8 Flash measured
Vibe Code Bench 1-100 (Vals AI)18.8%22.6%GPT-5.6 Luna
SkillsBench (Vals AI)58.0%60.5%GPT-5.6 Luna
CyberBench (Vals AI)43.8%73.6%GPT-5.6 Luna
SciCode56.6%53.6%Gemini 3.8 Flash
FrontierCode41.2%39.8%Gemini 3.8 Flash
FrontierSWE19.6%Not measuredOnly Gemini 3.8 Flash measured
WeirdML84.8%60.9%Gemini 3.8 Flash
ALE-Bench1269.71667.4GPT-5.6 Luna
LMArena Text: coding15081466Gemini 3.8 Flash
LMArena Text: software and IT15071463Gemini 3.8 Flash
LMArena WebDev: React15771508Gemini 3.8 Flash
LMArena WebDev: HTML16161520Gemini 3.8 Flash
LMArena WebDev: from an image15931517Gemini 3.8 Flash
SciCode12.3%6.2%Gemini 3.8 Flash
Neither model has a result on the other 13 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Gemini 3.8 Flash and GPT-5.6 Luna
BenchmarkGemini 3.8 FlashGPT-5.6 LunaLeader
AA Intelligence Index40.937.3Gemini 3.8 Flash
Epoch Capabilities Index157.4156.5Gemini 3.8 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index113
Agentic work benchmarks for Gemini 3.8 Flash and GPT-5.6 Luna
BenchmarkGemini 3.8 FlashGPT-5.6 LunaLeader
AA Agentic Index40.242.1GPT-5.6 Luna
Design Arena: agents building web apps1238Not measuredOnly Gemini 3.8 Flash measured
Design Arena: agents building full-stack apps1244Not measuredOnly Gemini 3.8 Flash measured
Design Arena: agents building mobile apps1236Not measuredOnly Gemini 3.8 Flash measured
Design Arena: agents building Android apps1078Not measuredOnly Gemini 3.8 Flash measured
Design Arena: agents building Godot games1273Not measuredOnly Gemini 3.8 Flash measured
Design Arena: PowerPoint slides1153Not measuredOnly Gemini 3.8 Flash measured
Design Arena: spreadsheets1022Not measuredOnly Gemini 3.8 Flash measured
LiveBench research79.1%51.0%Gemini 3.8 Flash
LiveBench browser64.0%68.0%GPT-5.6 Luna
LiveBench long agentic30.1%30.4%GPT-5.6 Luna
SREBench (Vals AI)11.1%1.5%Gemini 3.8 Flash
Finance Agent (Vals AI)61.4%55.0%Gemini 3.8 Flash
Tax Agent Bench (Vals AI)32.1%24.8%Gemini 3.8 Flash
Legal Research Bench (Vals AI)38.9%36.5%Gemini 3.8 Flash
Harvey's Legal Agent Benchmark (Vals AI)12.1%Not measuredOnly Gemini 3.8 Flash measured
Excel Modeling Benchmark (Vals AI)72.2%67.1%Gemini 3.8 Flash
BioMysteryBench (Vals AI)62.2%61.5%Gemini 3.8 Flash
Terminal-Bench-Science (Vals AI)8.6%0.0%Gemini 3.8 Flash
Vals Science Index35.8%25.3%Gemini 3.8 Flash
Time Horizon Index (Vals AI)18.8%Not measuredOnly Gemini 3.8 Flash measured
CUA-bench (Vals AI)4.2%Not measuredOnly Gemini 3.8 Flash measured
APEX-Agents64.3%43.0%Gemini 3.8 Flash
Remote Labor Index5.8%Not measuredOnly Gemini 3.8 Flash measured
BALROGNot measured45.6%Only GPT-5.6 Luna measured
Vending-Bench 2$5,094$4,095Gemini 3.8 Flash
Neither model has a result on the other 15 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index160
Reasoning benchmarks for Gemini 3.8 Flash and GPT-5.6 Luna
BenchmarkGemini 3.8 FlashGPT-5.6 LunaLeader
GPQA Diamond94.4%91.7%Gemini 3.8 Flash
LiveBench reasoning89.3%85.6%Gemini 3.8 Flash
MysteryMechanism (Vals AI)36.5%14.4%Gemini 3.8 Flash
MMMU Pro (Vals AI)89.1%85.0%Gemini 3.8 Flash
GPQA Diamond (Artificial Analysis run)95.3%91.1%Gemini 3.8 Flash
Humanity's Last Exam (Artificial Analysis run)47.8%39.5%Gemini 3.8 Flash
GPQA Diamond (Epoch AI run)95.4%91.6%Gemini 3.8 Flash
ARC-AGI98.5%88.0%Gemini 3.8 Flash
ARC-AGI-289.2%59.5%Gemini 3.8 Flash
SimpleBenchNot measured46.8%Only GPT-5.6 Luna measured
Chess puzzles58.0%43.0%Gemini 3.8 Flash
Mystery game puzzles47.0%21.0%Gemini 3.8 Flash
LMArena Text: hard prompts15091451Gemini 3.8 Flash
LMArena Text: expert15261478Gemini 3.8 Flash
LMArena Text: hard prompts in English15041460Gemini 3.8 Flash
LMArena Vision: diagrams13451273Gemini 3.8 Flash
LMArena Vision: homework13511282Gemini 3.8 Flash
Kagi LLM BenchmarkNot measured49.1%Only GPT-5.6 Luna measured
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index33
Math benchmarks for Gemini 3.8 Flash and GPT-5.6 Luna
BenchmarkGemini 3.8 FlashGPT-5.6 LunaLeader
OTIS Mock AIME98.9%98.3%Gemini 3.8 Flash
FrontierMath, tiers 1 to 368.4%82.1%GPT-5.6 Luna
FrontierMath, tier 422.0%61.0%GPT-5.6 Luna
ProofBench48.0%60.0%GPT-5.6 Luna
LMArena Text: math15321459Gemini 3.8 Flash
LMArena Text: mathematical work15191470Gemini 3.8 Flash
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index92
Knowledge benchmarks for Gemini 3.8 Flash and GPT-5.6 Luna
BenchmarkGemini 3.8 FlashGPT-5.6 LunaLeader
MMLU Pro90.2%86.0%Gemini 3.8 Flash
LegalBench (Vals AI)87.0%84.0%Gemini 3.8 Flash
CorpFin (Vals AI)Not measured64.2%Only GPT-5.6 Luna measured
TaxEval (Vals AI)74.5%76.2%GPT-5.6 Luna
MortgageTax (Vals AI)65.3%67.3%GPT-5.6 Luna
MedCode (Vals AI)48.1%42.4%Gemini 3.8 Flash
SimpleQA Verified69.7%41.0%Gemini 3.8 Flash
LMArena Text: science15231433Gemini 3.8 Flash
LMArena Text: medicine and healthcare15081399Gemini 3.8 Flash
LMArena Text: legal and government14971446Gemini 3.8 Flash
LMArena Text: business and finance14791439Gemini 3.8 Flash
FACTS Benchmark Suite69.4%35.0%Gemini 3.8 Flash
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index81
Web design benchmarks for Gemini 3.8 Flash and GPT-5.6 Luna
BenchmarkGemini 3.8 FlashGPT-5.6 LunaLeader
Design Arena: websites13001255Gemini 3.8 Flash
Design Arena: UI components13161248Gemini 3.8 Flash
Design Arena: game dev13041194Gemini 3.8 Flash
Design Arena: data viz12701211Gemini 3.8 Flash
Design Arena: 3D12941121Gemini 3.8 Flash
Design Arena: all code categories13031231Gemini 3.8 Flash
Design Arena: SVG12961194Gemini 3.8 Flash
Design Arena: ASCII art12621142Gemini 3.8 Flash
LiveBench design72.7%76.0%GPT-5.6 Luna
GeneralLike-for-likePublic boards, shown as published, kept out of the index293
General benchmarks for Gemini 3.8 Flash and GPT-5.6 Luna
BenchmarkGemini 3.8 FlashGPT-5.6 LunaLeader
Vals Index56.0%Not measuredOnly Gemini 3.8 Flash measured
LiveBench data analysis54.0%78.0%GPT-5.6 Luna
Public Benefits Bench (Vals AI)65.3%61.2%Gemini 3.8 Flash
SAGE (Vals AI)35.1%44.2%GPT-5.6 Luna
MedScribe (Vals AI)84.5%84.4%Gemini 3.8 Flash
Vals Multimodal IndexNot measured69.1%Only GPT-5.6 Luna measured
Long context reasoning (AA-LCR)84.0%83.7%Gemini 3.8 Flash
DTBench95.7%89.1%Gemini 3.8 Flash
LMCA52.9%48.5%Gemini 3.8 Flash
Surface Evolver Bench76.9%61.9%Gemini 3.8 Flash
Furniture assembly31.7%42.5%GPT-5.6 Luna
LMArena Text14991431Gemini 3.8 Flash
LMArena Text: instruction following14921437Gemini 3.8 Flash
LMArena Text: creative writing14881396Gemini 3.8 Flash
LMArena Vision13151257Gemini 3.8 Flash
LMArena Text: English14981441Gemini 3.8 Flash
LMArena Text: non-English14911417Gemini 3.8 Flash
LMArena Text: Chinese15531470Gemini 3.8 Flash
LMArena Text: German15011455Gemini 3.8 Flash
LMArena Text: Japanese15071415Gemini 3.8 Flash
LMArena Text: Korean14641415Gemini 3.8 Flash
LMArena Text: French14961458Gemini 3.8 Flash
LMArena Text: Spanish14871446Gemini 3.8 Flash
LMArena Text: Russian15141427Gemini 3.8 Flash
LMArena Text: Polish14971405Gemini 3.8 Flash
LMArena Text: multi-turn15031434Gemini 3.8 Flash
LMArena Text: longer queries15071436Gemini 3.8 Flash
LMArena Text: writing and language14941419Gemini 3.8 Flash
LMArena Text: entertainment and media14801402Gemini 3.8 Flash
LMArena Vision: English13181263Gemini 3.8 Flash
LMArena Vision: Chinese14161294Gemini 3.8 Flash
LMArena Vision: reading text13331264Gemini 3.8 Flash
LMArena Vision: humor13211190Gemini 3.8 Flash
LMArena Vision: creative writing12991257Gemini 3.8 Flash
LMArena DocumentNot measured1457Only GPT-5.6 Luna measured
Neither model has a result on the other 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 3.8 Flash and GPT-5.6 Luna
BenchmarkGemini 3.8 FlashGPT-5.6 LunaLeader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Gemini 3.8 Flash$0.0026Fits in one request
GPT-5.6 Luna$0.0008Fits in one request

GPT-5.6 Luna costs less

Repository review

50K input + 3K output tokens

Gemini 3.8 Flash$0.049Fits in one request
GPT-5.6 Luna$0.014Fits in one request

GPT-5.6 Luna costs less

Agent loop

200K input + 10K output tokens

Gemini 3.8 Flash$0.188Fits in one request
GPT-5.6 Luna$0.052Fits in one request

GPT-5.6 Luna costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Gemini 3.8 Flash and GPT-5.6 Luna
SpecificationGoogle Gemini 3.8 FlashOpenAI GPT-5.6 Luna
MakerGoogleOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedSeptember 2, 2026July 9, 2026
Context window1.05M1.05M
Input $/Mtok$0.75$0.20
Output $/Mtok$3.75$1.20
Coding index61.658.0
Independent measurements behind it66
Cost per solved task$2.74$0.04
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.8 Flash better than GPT-5.6 Luna for coding?

Pick Gemini 3.8 Flash for coding: it scores 61.6 on the Vibe Coding Index against 58.0 for GPT-5.6 Luna. Pick GPT-5.6 Luna for output tokens 3.1x cheaper ($1.20 vs $3.75 per million) and a lower cost per solved task ($0.04 against $2.74).

Which is cheaper, Gemini 3.8 Flash or GPT-5.6 Luna?

Gemini 3.8 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; GPT-5.6 Luna costs $0.20 and $1.20. Per solved SWE-bench Verified task, Gemini 3.8 Flash costs $2.74 and GPT-5.6 Luna $0.04.

Which has the bigger context window, Gemini 3.8 Flash or GPT-5.6 Luna?

GPT-5.6 Luna, with 1.05M tokens against 1.05M.

How many benchmarks is the Gemini 3.8 Flash vs GPT-5.6 Luna comparison based on?

113 benchmarks have a result for both models as of October 22, 2026. Gemini 3.8 Flash's coding index rests on 6 independent benchmarks and GPT-5.6 Luna's on 6. Where only one model has a result, the page says so instead of naming a winner.

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