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Gemini 3.5 Flash vs GPT-5.2

GPT-5.2 leads Gemini 3.5 Flash on coding, 55.9 to 39.8 on the Vibe Coding Index, and Gemini 3.5 Flash costs 1.6x less per output token ($9.00 vs $14.00 per million). Updated October 22, 2026; 91 benchmarks have a result for both.

Replace Gemini 3.5 Flash Replace GPT-5.2
Gemini 3.5 FlashGoogle
Coding
39.8
Overall
63.8
Output $/M
$9.00
77
GPT-5.2OpenAI
Coding
55.9
Overall
60.7
Output $/M
$14.00
14
vs boards won of 91 shared

Gemini 3.5 Flash or GPT-5.2: which to pick

Pick GPT-5.2 for coding: it scores 55.9 on the Vibe Coding Index against 39.8 for Gemini 3.5 Flash, though on 3 benchmarks against 4.

Pick Gemini 3.5 Flash for output tokens 1.6x cheaper ($9.00 vs $14.00 per million) and a lower cost per solved task ($1.21 against $1.91).

Model AGemini 3.5 FlashGoogle39.8/1004 independent benchmarks$1.21 per solved taskModel BGPT-5.2OpenAI55.9/1003 independent benchmarks$1.91 per solved task
Shared results
91
Gemini 3.5 Flash only
21
GPT-5.2 only
23
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 3.5 Flash 39.8 from 4 benchmarks, GPT-5.2 55.9 from 3 benchmarks.
Widest category
Agentic work, 12.5 points apart on average over 7 shared benchmarks.
Widest single gap
SimpleBench: Gemini 3.5 Flash 76.7% against GPT-5.2 45.8%, 30.9 points apart on a 0 to 100 scale.
Output price
Gemini 3.5 Flash $9.00 against GPT-5.2 $14.00 per million output tokens, 1.6x apart.
Context window
Gemini 3.5 Flash takes 1.05M tokens, GPT-5.2 400K.

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 3.5 FlashBarsGPT-5.2Ties
Coding64
Intelligence20
Agentic work61
Reasoning142
Math33
Knowledge102
Web design80
General282
All shared boards7714
CodingLike-for-likeSix of these boards feed the Vibe Coding Index64
Coding benchmarks for Gemini 3.5 Flash and GPT-5.2
BenchmarkGemini 3.5 FlashGPT-5.2Leader
SWE-bench VerifiedNot measured72.8%Only GPT-5.2 measured
SWE-bench MultilingualNot measured66.7%Only GPT-5.2 measured
LMArena WebDev14991417Gemini 3.5 Flash
LiveCodeBench (Vals AI)87.6%85.4%Gemini 3.5 Flash
SWE-bench Verified (Vals AI)78.8%75.8%Gemini 3.5 Flash
Terminal-Bench 4 (Vals AI)6.1%Not measuredOnly Gemini 3.5 Flash measured
Vibe Code Bench (Vals AI)48.7%53.5%GPT-5.2
Code migration (Vals AI)26.8%Not measuredOnly Gemini 3.5 Flash measured
ProgramBench (Vals AI)0.0%Not measuredOnly Gemini 3.5 Flash measured
Terminal-Bench 2.1 (Vals AI)74.2%Not measuredOnly Gemini 3.5 Flash measured
SkillsBench (Vals AI)52.7%Not measuredOnly Gemini 3.5 Flash measured
LiveCodeBench (Artificial Analysis run)Not measured89.4%Only GPT-5.2 measured
SciCode53.9%Not measuredOnly Gemini 3.5 Flash measured
Terminal-Bench Hard (Artificial Analysis run)46.2%47.0%GPT-5.2
Terminal-BenchNot measured64.9%Only GPT-5.2 measured
GSO-BenchNot measured27.5%Only GPT-5.2 measured
WeirdML62.6%72.2%GPT-5.2
ALE-Bench911.01293.5GPT-5.2
LMArena Text: coding14931442Gemini 3.5 Flash
LMArena Text: software and IT14941434Gemini 3.5 Flash
LMArena WebDev: React1495Not measuredOnly Gemini 3.5 Flash measured
LMArena WebDev: HTML15221427Gemini 3.5 Flash
LMArena WebDev: from an image1504Not measuredOnly Gemini 3.5 Flash measured
SciCode12.3%Not measuredOnly Gemini 3.5 Flash measured
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Gemini 3.5 Flash and GPT-5.2
BenchmarkGemini 3.5 FlashGPT-5.2Leader
AA Intelligence Index33.630.4Gemini 3.5 Flash
Epoch Capabilities Index154.9153.7Gemini 3.5 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index61
Agentic work benchmarks for Gemini 3.5 Flash and GPT-5.2
BenchmarkGemini 3.5 FlashGPT-5.2Leader
Design Arena: agents building web apps12021086Gemini 3.5 Flash
Design Arena: agents building full-stack apps11971043Gemini 3.5 Flash
Design Arena: agents building mobile apps11741093Gemini 3.5 Flash
Design Arena: agents building Android apps11851059Gemini 3.5 Flash
Design Arena: agents building Godot games10981142GPT-5.2
Design Arena: agents building games1180Not measuredOnly Gemini 3.5 Flash measured
Design Arena: HTML slides1093Not measuredOnly Gemini 3.5 Flash measured
Design Arena: PowerPoint slides1154Not measuredOnly Gemini 3.5 Flash measured
Finance Agent (Vals AI)57.9%Not measuredOnly Gemini 3.5 Flash measured
Tax Agent Bench (Vals AI)21.6%Not measuredOnly Gemini 3.5 Flash measured
Legal Research Bench (Vals AI)30.8%Not measuredOnly Gemini 3.5 Flash measured
Excel Modeling Benchmark (Vals AI)63.5%Not measuredOnly Gemini 3.5 Flash measured
Terminal-Bench-Science (Vals AI)5.7%Not measuredOnly Gemini 3.5 Flash measured
τ²-Bench Telecom95.6%84.8%Gemini 3.5 Flash
APEX-Agents27.5%Not measuredOnly Gemini 3.5 Flash measured
METR time horizonsNot measured75.3%Only GPT-5.2 measured
Remote Labor IndexNot measured2.5%Only GPT-5.2 measured
GDPvalNot measured49.7%Only GPT-5.2 measured
DeepResearch BenchNot measured41.1%Only GPT-5.2 measured
Vending-Bench 2$5,396$3,591Gemini 3.5 Flash
Berkeley Function Calling Leaderboard (BFCL)Not measured55.9%Only GPT-5.2 measured
Neither model has a result on the other 20 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index142
Reasoning benchmarks for Gemini 3.5 Flash and GPT-5.2
BenchmarkGemini 3.5 FlashGPT-5.2Leader
GPQA Diamond92.7%91.7%Gemini 3.5 Flash
MMMU Pro (Vals AI)88.3%86.7%Gemini 3.5 Flash
GPQA Diamond (Artificial Analysis run)92.2%90.3%Gemini 3.5 Flash
Humanity's Last Exam (Artificial Analysis run)42.7%37.7%Gemini 3.5 Flash
GPQA Diamond (Epoch AI run)92.8%91.4%Gemini 3.5 Flash
ARC-AGI92.5%86.2%Gemini 3.5 Flash
ARC-AGI-272.1%52.9%Gemini 3.5 Flash
SimpleBench76.7%45.8%Gemini 3.5 Flash
Chess puzzles45.0%48.0%GPT-5.2
Mystery game puzzles32.0%23.0%Gemini 3.5 Flash
EBR-bench4.8%23.0%GPT-5.2
VPCTNot measured84.0%Only GPT-5.2 measured
LMArena Text: hard prompts14881428Gemini 3.5 Flash
LMArena Text: expert14951445Gemini 3.5 Flash
LMArena Text: hard prompts in English14831431Gemini 3.5 Flash
LMArena Vision: diagrams13231265Gemini 3.5 Flash
LMArena Vision: homework13301276Gemini 3.5 Flash
Kagi LLM BenchmarkNot measured73.3%Only GPT-5.2 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 3.5 Flash and GPT-5.2
BenchmarkGemini 3.5 FlashGPT-5.2Leader
AIMENot measured96.9%Only GPT-5.2 measured
MGSM (Vals AI)Not measured94.0%Only GPT-5.2 measured
AA Math IndexNot measured99.0Only GPT-5.2 measured
AIME 2025 (Artificial Analysis run)Not measured99.0%Only GPT-5.2 measured
OTIS Mock AIME95.6%96.1%GPT-5.2
FrontierMath, tiers 1 to 362.8%67.4%GPT-5.2
FrontierMath, tier 426.8%31.7%GPT-5.2
ProofBench31.0%15.0%Gemini 3.5 Flash
LMArena Text: math15041440Gemini 3.5 Flash
LMArena Text: mathematical work14951442Gemini 3.5 Flash
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index102
Knowledge benchmarks for Gemini 3.5 Flash and GPT-5.2
BenchmarkGemini 3.5 FlashGPT-5.2Leader
MMLU Pro89.5%86.2%Gemini 3.5 Flash
LegalBench (Vals AI)83.6%82.8%Gemini 3.5 Flash
CaseLaw (Vals AI)Not measured66.0%Only GPT-5.2 measured
CorpFin (Vals AI)64.7%65.9%GPT-5.2
TaxEval (Vals AI)74.4%75.8%GPT-5.2
MortgageTax (Vals AI)68.1%67.1%Gemini 3.5 Flash
MedQA (Vals AI)Not measured94.1%Only GPT-5.2 measured
MedCode (Vals AI)55.8%49.8%Gemini 3.5 Flash
MMLU Pro (Artificial Analysis run)Not measured87.4%Only GPT-5.2 measured
SimpleQA Verified66.2%37.1%Gemini 3.5 Flash
LMArena Text: science14951425Gemini 3.5 Flash
LMArena Text: medicine and healthcare14831425Gemini 3.5 Flash
LMArena Text: legal and government14881427Gemini 3.5 Flash
LMArena Text: business and finance14671414Gemini 3.5 Flash
FACTS Benchmark Suite63.1%48.5%Gemini 3.5 Flash
Neither model has a result on the other 3 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index80
Web design benchmarks for Gemini 3.5 Flash and GPT-5.2
BenchmarkGemini 3.5 FlashGPT-5.2Leader
Design Arena: websites12671195Gemini 3.5 Flash
Design Arena: UI components12691190Gemini 3.5 Flash
Design Arena: game dev12631195Gemini 3.5 Flash
Design Arena: data viz12361202Gemini 3.5 Flash
Design Arena: 3D12431079Gemini 3.5 Flash
Design Arena: all code categories12661170Gemini 3.5 Flash
Design Arena: SVG12531139Gemini 3.5 Flash
Design Arena: ASCII art12541152Gemini 3.5 Flash
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index282
General benchmarks for Gemini 3.5 Flash and GPT-5.2
BenchmarkGemini 3.5 FlashGPT-5.2Leader
Public Benefits Bench (Vals AI)59.5%Not measuredOnly Gemini 3.5 Flash measured
SAGE (Vals AI)49.9%49.3%Gemini 3.5 Flash
MedScribe (Vals AI)76.6%84.4%GPT-5.2
Vals Multimodal Index62.9%Not measuredOnly Gemini 3.5 Flash measured
IFBench76.3%75.4%Gemini 3.5 Flash
Long context reasoning (AA-LCR)74.3%82.7%GPT-5.2
DTBench94.7%90.9%Gemini 3.5 Flash
LMCA47.1%43.9%Gemini 3.5 Flash
CL-benchNot measured18.2%Only GPT-5.2 measured
Surface Evolver Bench58.1%Not measuredOnly Gemini 3.5 Flash measured
Furniture assemblyNot measured38.3%Only GPT-5.2 measured
LMArena Text14821416Gemini 3.5 Flash
LMArena Text: instruction following14671409Gemini 3.5 Flash
LMArena Text: creative writing14701376Gemini 3.5 Flash
LMArena Vision13081246Gemini 3.5 Flash
LMArena Text: English14811422Gemini 3.5 Flash
LMArena Text: non-English14751405Gemini 3.5 Flash
LMArena Text: Chinese15271447Gemini 3.5 Flash
LMArena Text: German14941444Gemini 3.5 Flash
LMArena Text: Japanese14861420Gemini 3.5 Flash
LMArena Text: Korean14481374Gemini 3.5 Flash
LMArena Text: French14901454Gemini 3.5 Flash
LMArena Text: Spanish14801413Gemini 3.5 Flash
LMArena Text: Russian14931415Gemini 3.5 Flash
LMArena Text: Polish15161426Gemini 3.5 Flash
LMArena Text: multi-turn14811419Gemini 3.5 Flash
LMArena Text: longer queries14831413Gemini 3.5 Flash
LMArena Text: writing and language14781392Gemini 3.5 Flash
LMArena Text: entertainment and media14591378Gemini 3.5 Flash
LMArena Vision: English13051243Gemini 3.5 Flash
LMArena Vision: Chinese13771305Gemini 3.5 Flash
LMArena Vision: reading text13171257Gemini 3.5 Flash
LMArena Vision: humor13211227Gemini 3.5 Flash
LMArena Vision: captioningNot measured1267Only GPT-5.2 measured
LMArena Vision: recognizing thingsNot measured1232Only GPT-5.2 measured
LMArena Vision: creative writing13011225Gemini 3.5 Flash
LMArena Document14631405Gemini 3.5 Flash
Neither model has a result on the other 9 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 3.5 Flash and GPT-5.2
BenchmarkGemini 3.5 FlashGPT-5.2Leader
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 3.5 Flash$0.0060Fits in one request
GPT-5.2$0.0088Fits in one request

Gemini 3.5 Flash costs less

Repository review

50K input + 3K output tokens

Gemini 3.5 Flash$0.102Fits in one request
GPT-5.2$0.130Fits in one request

Gemini 3.5 Flash costs less

Agent loop

200K input + 10K output tokens

Gemini 3.5 Flash$0.390Fits in one request
GPT-5.2$0.490Fits in one request

Gemini 3.5 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 3.5 Flash and GPT-5.2
SpecificationGoogle Gemini 3.5 FlashOpenAI GPT-5.2
MakerGoogleOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedMay 19, 2026December 10, 2025
Context window1.05M400K
Input $/Mtok$1.50$1.75
Output $/Mtok$9.00$14.00
Coding index39.855.9
Independent measurements behind it43
Cost per solved task$1.21$1.91
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.5 Flash better than GPT-5.2 for coding?

Pick GPT-5.2 for coding: it scores 55.9 on the Vibe Coding Index against 39.8 for Gemini 3.5 Flash, though on 3 benchmarks against 4. Pick Gemini 3.5 Flash for output tokens 1.6x cheaper ($9.00 vs $14.00 per million) and a lower cost per solved task ($1.21 against $1.91).

Which is cheaper, Gemini 3.5 Flash or GPT-5.2?

Gemini 3.5 Flash costs $1.50 per million input tokens and $9.00 per million output tokens; GPT-5.2 costs $1.75 and $14.00. Per solved SWE-bench Verified task, Gemini 3.5 Flash costs $1.21 and GPT-5.2 $1.91.

Which has the bigger context window, Gemini 3.5 Flash or GPT-5.2?

Gemini 3.5 Flash, with 1.05M tokens against 400K.

How many benchmarks is the Gemini 3.5 Flash vs GPT-5.2 comparison based on?

91 benchmarks have a result for both models as of October 22, 2026. Gemini 3.5 Flash's coding index rests on 4 independent benchmarks and GPT-5.2's on 3. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/gemini-3-5-flash-vs-gpt-5-2">LLMBenchmark.ai, Gemini 3.5 Flash vs GPT-5.2</a></p>