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Gemini 3.8 Flash vs GPT-5.5

GPT-5.5 leads Gemini 3.8 Flash on coding, 71.3 to 61.6 on the Vibe Coding Index, and Gemini 3.8 Flash costs 8.0x less per output token ($3.75 vs $30.00 per million). Updated October 22, 2026; 113 benchmarks have a result for both.

Gemini 3.8 FlashGoogle
Coding
61.6
Overall
69.0
Output $/M
$3.75
82
GPT-5.5OpenAI
Coding
71.3
Overall
69.2
Output $/M
$30.00
31
vs boards won of 113 shared

Gemini 3.8 Flash or GPT-5.5: which to pick

Pick GPT-5.5 for coding: it scores 71.3 on the Vibe Coding Index against 61.6 for Gemini 3.8 Flash, though on 5 benchmarks against 6.

Pick Gemini 3.8 Flash for output tokens 8.0x cheaper ($3.75 vs $30.00 per million) and work measured by LMArena WebDev or AA Coding Index, where it leads.

Shared results
113
Gemini 3.8 Flash only
15
GPT-5.5 only
21
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-5.5 71.3 from 5 benchmarks.
Widest category
Math, 15.9 points apart on average over 6 shared benchmarks.
Widest single gap
FrontierMath, tier 4: Gemini 3.8 Flash 22.0% against GPT-5.5 72.5%, 50.5 points apart on a 0 to 100 scale.
Output price
Gemini 3.8 Flash $3.75 against GPT-5.5 $30.00 per million output tokens, 8.0x apart.
Context window
Gemini 3.8 Flash takes 1.05M tokens, GPT-5.5 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-5.5Ties
Coding127
Intelligence11
Agentic work145
Reasoning123
Math33
Knowledge83
Web design90
General239
All shared boards8231
CodingLike-for-likeSix of these boards feed the Vibe Coding Index127
Coding benchmarks for Gemini 3.8 Flash and GPT-5.5
BenchmarkGemini 3.8 FlashGPT-5.5Leader
LiveBench coding82.2%85.1%GPT-5.5
LMArena WebDev15851513Gemini 3.8 Flash
AA Coding Index76.374.9Gemini 3.8 Flash
LiveCodeBench (Vals AI)89.5%85.3%Gemini 3.8 Flash
SWE-bench Verified (Vals AI)80.0%82.6%GPT-5.5
Terminal-Bench 4 (Vals AI)19.7%Not measuredOnly Gemini 3.8 Flash measured
Vibe Code Bench (Vals AI)78.7%69.8%Gemini 3.8 Flash
Code migration (Vals AI)36.5%45.2%GPT-5.5
ProgramBench (Vals AI)1.0%0.5%Gemini 3.8 Flash
IOI (Vals AI)56.9%Not measuredOnly Gemini 3.8 Flash measured
Terminal-Bench 2.1 (Vals AI)81.3%76.4%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%Not measuredOnly Gemini 3.8 Flash measured
SkillsBench (Vals AI)58.0%62.5%GPT-5.5
CyberBench (Vals AI)43.8%Not measuredOnly Gemini 3.8 Flash measured
SciCode56.6%56.1%Gemini 3.8 Flash
Terminal-Bench Hard (Artificial Analysis run)Not measured60.6%Only GPT-5.5 measured
Terminal-BenchNot measured84.7%Only GPT-5.5 measured
FrontierCode41.2%43.0%GPT-5.5
FrontierSWE19.6%Not measuredOnly Gemini 3.8 Flash measured
GSO-BenchNot measured40.2%Only GPT-5.5 measured
WeirdML84.8%84.9%GPT-5.5
MirrorCodeNot measured10.0%Only GPT-5.5 measured
ALE-Bench1269.71943.0GPT-5.5
LMArena Text: coding15081494Gemini 3.8 Flash
LMArena Text: software and IT15071493Gemini 3.8 Flash
LMArena WebDev: React15771506Gemini 3.8 Flash
LMArena WebDev: HTML16161543Gemini 3.8 Flash
LMArena WebDev: from an image15931532Gemini 3.8 Flash
SciCode12.3%Not measuredOnly Gemini 3.8 Flash measured
Neither model has a result on the other 9 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for Gemini 3.8 Flash and GPT-5.5
BenchmarkGemini 3.8 FlashGPT-5.5Leader
AA Intelligence Index40.938.4Gemini 3.8 Flash
Epoch Capabilities Index157.4159.7GPT-5.5
Agentic workLike-for-likePublic boards, shown as published, kept out of the index145
Agentic work benchmarks for Gemini 3.8 Flash and GPT-5.5
BenchmarkGemini 3.8 FlashGPT-5.5Leader
AA Agentic Index40.236.4Gemini 3.8 Flash
Design Arena: agents building web apps12381117Gemini 3.8 Flash
Design Arena: agents building full-stack apps12441089Gemini 3.8 Flash
Design Arena: agents building mobile apps12361142Gemini 3.8 Flash
Design Arena: agents building Android apps10781164GPT-5.5
Design Arena: agents building Godot games12731173Gemini 3.8 Flash
Design Arena: agents building gamesNot measured1179Only GPT-5.5 measured
Design Arena: HTML slidesNot measured1017Only GPT-5.5 measured
Design Arena: PowerPoint slides11531084Gemini 3.8 Flash
Design Arena: spreadsheets1022Not measuredOnly Gemini 3.8 Flash measured
LiveBench research79.1%61.6%Gemini 3.8 Flash
LiveBench browser64.0%48.0%Gemini 3.8 Flash
LiveBench long agentic30.1%44.6%GPT-5.5
SREBench (Vals AI)11.1%3.8%Gemini 3.8 Flash
Finance Agent (Vals AI)61.4%51.8%Gemini 3.8 Flash
Tax Agent Bench (Vals AI)32.1%21.8%Gemini 3.8 Flash
Legal Research Bench (Vals AI)38.9%40.4%GPT-5.5
Harvey's Legal Agent Benchmark (Vals AI)12.1%Not measuredOnly Gemini 3.8 Flash measured
Excel Modeling Benchmark (Vals AI)72.2%64.5%Gemini 3.8 Flash
BioMysteryBench (Vals AI)62.2%Not measuredOnly Gemini 3.8 Flash measured
Terminal-Bench-Science (Vals AI)8.6%Not measuredOnly Gemini 3.8 Flash measured
Vals Science Index35.8%Not measuredOnly Gemini 3.8 Flash measured
Time Horizon Index (Vals AI)18.8%8.3%Gemini 3.8 Flash
CUA-bench (Vals AI)4.2%Not measuredOnly Gemini 3.8 Flash measured
τ²-Bench TelecomNot measured93.9%Only GPT-5.5 measured
APEX-Agents64.3%55.1%Gemini 3.8 Flash
Remote Labor Index5.8%6.3%GPT-5.5
OSWorld 2.0Not measured13.0%Only GPT-5.5 measured
DeepResearch BenchNot measured54.0%Only GPT-5.5 measured
PostTrainBenchNot measured27.2%Only GPT-5.5 measured
Vending-Bench 2$5,094$7,524GPT-5.5
Neither model has a result on the other 10 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index123
Reasoning benchmarks for Gemini 3.8 Flash and GPT-5.5
BenchmarkGemini 3.8 FlashGPT-5.5Leader
GPQA Diamond94.4%93.2%Gemini 3.8 Flash
LiveBench reasoning89.3%89.7%GPT-5.5
MysteryMechanism (Vals AI)36.5%Not measuredOnly Gemini 3.8 Flash measured
MMMU Pro (Vals AI)89.1%88.3%Gemini 3.8 Flash
GPQA Diamond (Artificial Analysis run)95.3%93.5%Gemini 3.8 Flash
Humanity's Last Exam (Artificial Analysis run)47.8%45.8%Gemini 3.8 Flash
GPQA Diamond (Epoch AI run)95.4%90.7%Gemini 3.8 Flash
ARC-AGI98.5%95.0%Gemini 3.8 Flash
ARC-AGI-289.2%85.0%Gemini 3.8 Flash
SimpleBenchNot measured69.0%Only GPT-5.5 measured
Chess puzzles58.0%63.0%GPT-5.5
Mystery game puzzles47.0%56.0%GPT-5.5
EBR-benchNot measured34.3%Only GPT-5.5 measured
LMArena Text: hard prompts15091489Gemini 3.8 Flash
LMArena Text: expert15261507Gemini 3.8 Flash
LMArena Text: hard prompts in English15041483Gemini 3.8 Flash
LMArena Vision: diagrams13451325Gemini 3.8 Flash
LMArena Vision: homework13511332Gemini 3.8 Flash
Kagi LLM BenchmarkNot measured88.8%Only GPT-5.5 measured
Neither model has a result on the other 3 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index33
Math benchmarks for Gemini 3.8 Flash and GPT-5.5
BenchmarkGemini 3.8 FlashGPT-5.5Leader
OTIS Mock AIME98.9%84.4%Gemini 3.8 Flash
FrontierMath, tiers 1 to 368.4%85.3%GPT-5.5
FrontierMath, tier 422.0%72.5%GPT-5.5
ProofBench48.0%50.0%GPT-5.5
LMArena Text: math15321487Gemini 3.8 Flash
LMArena Text: mathematical work15191496Gemini 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 index83
Knowledge benchmarks for Gemini 3.8 Flash and GPT-5.5
BenchmarkGemini 3.8 FlashGPT-5.5Leader
MMLU Pro90.2%88.1%Gemini 3.8 Flash
LegalBench (Vals AI)87.0%86.5%Gemini 3.8 Flash
CaseLaw (Vals AI)Not measured66.2%Only GPT-5.5 measured
CorpFin (Vals AI)Not measured68.4%Only GPT-5.5 measured
TaxEval (Vals AI)74.5%75.0%GPT-5.5
MortgageTax (Vals AI)65.3%68.8%GPT-5.5
MedCode (Vals AI)48.1%49.1%GPT-5.5
SimpleQA Verified69.7%63.0%Gemini 3.8 Flash
LMArena Text: science15231485Gemini 3.8 Flash
LMArena Text: medicine and healthcare15081465Gemini 3.8 Flash
LMArena Text: legal and government14971491Gemini 3.8 Flash
LMArena Text: business and finance14791478Gemini 3.8 Flash
FACTS Benchmark Suite69.4%66.7%Gemini 3.8 Flash
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index90
Web design benchmarks for Gemini 3.8 Flash and GPT-5.5
BenchmarkGemini 3.8 FlashGPT-5.5Leader
Design Arena: websites13001256Gemini 3.8 Flash
Design Arena: UI components13161257Gemini 3.8 Flash
Design Arena: game dev13041293Gemini 3.8 Flash
Design Arena: data viz12701264Gemini 3.8 Flash
Design Arena: 3D12941197Gemini 3.8 Flash
Design Arena: all code categories13031260Gemini 3.8 Flash
Design Arena: SVG12961234Gemini 3.8 Flash
Design Arena: ASCII art12621255Gemini 3.8 Flash
LiveBench design72.7%70.3%Gemini 3.8 Flash
GeneralLike-for-likePublic boards, shown as published, kept out of the index239
General benchmarks for Gemini 3.8 Flash and GPT-5.5
BenchmarkGemini 3.8 FlashGPT-5.5Leader
Vals Index56.0%Not measuredOnly Gemini 3.8 Flash measured
LiveBench data analysis54.0%81.6%GPT-5.5
Public Benefits Bench (Vals AI)65.3%60.9%Gemini 3.8 Flash
SAGE (Vals AI)35.1%51.5%GPT-5.5
MedScribe (Vals AI)84.5%86.9%GPT-5.5
Vals Multimodal IndexNot measured68.1%Only GPT-5.5 measured
IFBenchNot measured75.9%Only GPT-5.5 measured
Long context reasoning (AA-LCR)84.0%84.3%GPT-5.5
DTBench95.7%96.0%GPT-5.5
LMCA52.9%54.3%GPT-5.5
Surface Evolver Bench76.9%88.1%GPT-5.5
Furniture assembly31.7%44.2%GPT-5.5
ExploitBenchNot measured47.4%Only GPT-5.5 measured
CL-bench LifeNot measured22.2%Only GPT-5.5 measured
LMArena Text14991471Gemini 3.8 Flash
LMArena Text: instruction following14921478Gemini 3.8 Flash
LMArena Text: creative writing14881455Gemini 3.8 Flash
LMArena Vision13151297Gemini 3.8 Flash
LMArena Text: English14981470Gemini 3.8 Flash
LMArena Text: non-English14911467Gemini 3.8 Flash
LMArena Text: Chinese15531534Gemini 3.8 Flash
LMArena Text: German15011480Gemini 3.8 Flash
LMArena Text: Japanese15071499Gemini 3.8 Flash
LMArena Text: Korean14641460Gemini 3.8 Flash
LMArena Text: French14961485Gemini 3.8 Flash
LMArena Text: Spanish14871468Gemini 3.8 Flash
LMArena Text: Russian15141473Gemini 3.8 Flash
LMArena Text: Polish14971465Gemini 3.8 Flash
LMArena Text: multi-turn15031476Gemini 3.8 Flash
LMArena Text: longer queries15071484Gemini 3.8 Flash
LMArena Text: writing and language14941466Gemini 3.8 Flash
LMArena Text: entertainment and media14801449Gemini 3.8 Flash
LMArena Vision: English13181292Gemini 3.8 Flash
LMArena Vision: Chinese14161360Gemini 3.8 Flash
LMArena Vision: reading text13331306Gemini 3.8 Flash
LMArena Vision: humor13211293Gemini 3.8 Flash
LMArena Vision: recognizing thingsNot measured1231Only GPT-5.5 measured
LMArena Vision: creative writing12991301GPT-5.5
LMArena DocumentNot measured1486Only GPT-5.5 measured
Neither model has a result on the other 7 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-5.5
BenchmarkGemini 3.8 FlashGPT-5.5Leader
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-5.5$0.020Fits in one request

Gemini 3.8 Flash costs less

Repository review

50K input + 3K output tokens

Gemini 3.8 Flash$0.049Fits in one request
GPT-5.5$0.340Fits in one request

Gemini 3.8 Flash costs less

Agent loop

200K input + 10K output tokens

Gemini 3.8 Flash$0.188Fits in one request
GPT-5.5$1.30Fits in one request

Gemini 3.8 Flash 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-5.5
SpecificationGoogle Gemini 3.8 FlashOpenAI GPT-5.5
MakerGoogleOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedSeptember 2, 2026April 24, 2026
Context window1.05M1.05M
Input $/Mtok$0.75$5.00
Output $/Mtok$3.75$30.00
Coding index61.671.3
Independent measurements behind it65
Cost per solved task$2.74$1.65
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.8 Flash better than GPT-5.5 for coding?

Pick GPT-5.5 for coding: it scores 71.3 on the Vibe Coding Index against 61.6 for Gemini 3.8 Flash, though on 5 benchmarks against 6. Pick Gemini 3.8 Flash for output tokens 8.0x cheaper ($3.75 vs $30.00 per million) and work measured by LMArena WebDev or AA Coding Index, where it leads.

Which is cheaper, Gemini 3.8 Flash or GPT-5.5?

Gemini 3.8 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; GPT-5.5 costs $5.00 and $30.00. Per solved SWE-bench Verified task, Gemini 3.8 Flash costs $2.74 and GPT-5.5 $1.65.

Which has the bigger context window, Gemini 3.8 Flash or GPT-5.5?

GPT-5.5, with 1.05M tokens against 1.05M.

How many benchmarks is the Gemini 3.8 Flash vs GPT-5.5 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-5.5's on 5. Where only one model has a result, the page says so instead of naming a winner.

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