Enter opens the highlighted result. Esc closes.

Gemini 3.7 Flash vs GPT-5.5

GPT-5.5 leads Gemini 3.7 Flash on coding, 71.3 to 58.0 on the Vibe Coding Index, and Gemini 3.7 Flash costs 8.0x less per output token ($3.75 vs $30.00 per million). Updated October 21, 2026; 107 benchmarks have a result for both.

Replace Gemini 3.7 Flash Replace GPT-5.5
Gemini 3.7 FlashGoogle
Coding
58.0
Overall
65.7
Output $/M
$3.75
83
GPT-5.5OpenAI
Coding
71.3
Overall
69.2
Output $/M
$30.00
24
vs boards won of 107 shared

Gemini 3.7 Flash or GPT-5.5: which to pick

Pick GPT-5.5 for coding: it scores 71.3 on the Vibe Coding Index against 58.0 for Gemini 3.7 Flash, though on 5 benchmarks against 6.

Pick Gemini 3.7 Flash for output tokens 8.0x cheaper ($3.75 vs $30.00 per million) and work measured by LMArena WebDev or LiveCodeBench (Vals AI), where it leads.

Model AGemini 3.7 FlashGoogle58.0/1006 independent benchmarks$1.78 per solved taskModel BGPT-5.5OpenAI71.3/1005 independent benchmarks$1.65 per solved task
Shared results
107
Gemini 3.7 Flash only
7
GPT-5.5 only
27
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 3.7 Flash 58.0 from 6 benchmarks, GPT-5.5 71.3 from 5 benchmarks.
Widest category
Math, 12.6 points apart on average over 6 shared benchmarks.
Widest single gap
FrontierMath, tier 4: Gemini 3.7 Flash 36.6% against GPT-5.5 72.5%, 35.9 points apart on a 0 to 100 scale.
Output price
Gemini 3.7 Flash $3.75 against GPT-5.5 $30.00 per million output tokens, 8.0x apart.
Context window
Gemini 3.7 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 3.7 FlashBarsGPT-5.5Ties
Coding126
Intelligence11
Agentic work133
Reasoning114
Math42
Knowledge92
Web design90
General246
All shared boards8324
CodingLike-for-likeSix of these boards feed the Vibe Coding Index126
Coding benchmarks for Gemini 3.7 Flash and GPT-5.5
BenchmarkGemini 3.7 FlashGPT-5.5Leader
LiveBench coding80.5%85.1%GPT-5.5
LMArena WebDev15911513Gemini 3.7 Flash
AA Coding Index71.574.9GPT-5.5
LiveCodeBench (Vals AI)88.7%85.3%Gemini 3.7 Flash
SWE-bench Verified (Vals AI)80.8%82.6%GPT-5.5
Terminal-Bench 4 (Vals AI)12.1%Not measuredOnly Gemini 3.7 Flash measured
Vibe Code Bench (Vals AI)70.4%69.8%Gemini 3.7 Flash
Code migration (Vals AI)34.8%45.2%GPT-5.5
ProgramBench (Vals AI)0.0%0.5%GPT-5.5
IOI (Vals AI)67.8%Not measuredOnly Gemini 3.7 Flash measured
Terminal-Bench 2.1 (Vals AI)77.5%76.4%Gemini 3.7 Flash
SkillsBench (Vals AI)65.9%62.5%Gemini 3.7 Flash
CyberBench (Vals AI)43.8%Not measuredOnly Gemini 3.7 Flash measured
SciCode59.8%56.1%Gemini 3.7 Flash
Terminal-Bench Hard (Artificial Analysis run)Not measured60.6%Only GPT-5.5 measured
Terminal-BenchNot measured84.7%Only GPT-5.5 measured
FrontierCode43.6%43.0%Gemini 3.7 Flash
FrontierSWE20.3%Not measuredOnly Gemini 3.7 Flash measured
GSO-BenchNot measured40.2%Only GPT-5.5 measured
WeirdMLNot measured84.9%Only GPT-5.5 measured
MirrorCodeNot measured10.0%Only GPT-5.5 measured
ALE-Bench904.31943.0GPT-5.5
LMArena Text: coding14991494Gemini 3.7 Flash
LMArena Text: software and IT14981493Gemini 3.7 Flash
LMArena WebDev: React15871506Gemini 3.7 Flash
LMArena WebDev: HTML15931543Gemini 3.7 Flash
LMArena WebDev: from an image15991532Gemini 3.7 Flash
SciCode13.8%Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 11 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for Gemini 3.7 Flash and GPT-5.5
BenchmarkGemini 3.7 FlashGPT-5.5Leader
AA Intelligence Index39.638.4Gemini 3.7 Flash
Epoch Capabilities Index158.0159.7GPT-5.5
Agentic workLike-for-likePublic boards, shown as published, kept out of the index133
Agentic work benchmarks for Gemini 3.7 Flash and GPT-5.5
BenchmarkGemini 3.7 FlashGPT-5.5Leader
AA Agentic IndexNot measured36.4Only GPT-5.5 measured
Design Arena: agents building web apps12231117Gemini 3.7 Flash
Design Arena: agents building full-stack apps12081089Gemini 3.7 Flash
Design Arena: agents building mobile apps12301143Gemini 3.7 Flash
Design Arena: agents building Android apps12421163Gemini 3.7 Flash
Design Arena: agents building Godot games12641173Gemini 3.7 Flash
Design Arena: agents building games12351179Gemini 3.7 Flash
Design Arena: HTML slidesNot measured1067Only GPT-5.5 measured
Design Arena: PowerPoint slidesNot measured1109Only GPT-5.5 measured
Design Arena: spreadsheets1053Not measuredOnly Gemini 3.7 Flash measured
LiveBench research76.5%61.6%Gemini 3.7 Flash
LiveBench browser56.0%48.0%Gemini 3.7 Flash
LiveBench long agentic28.3%44.6%GPT-5.5
SREBench (Vals AI)4.6%3.8%Gemini 3.7 Flash
Finance Agent (Vals AI)59.0%51.8%Gemini 3.7 Flash
Tax Agent Bench (Vals AI)22.8%21.8%Gemini 3.7 Flash
Legal Research Bench (Vals AI)34.6%40.4%GPT-5.5
Excel Modeling Benchmark (Vals AI)71.3%64.5%Gemini 3.7 Flash
Terminal-Bench-Science (Vals AI)7.1%Not measuredOnly Gemini 3.7 Flash measured
Time Horizon Index (Vals AI)Not measured8.3%Only GPT-5.5 measured
τ²-Bench TelecomNot measured93.9%Only GPT-5.5 measured
APEX-Agents67.8%55.1%Gemini 3.7 Flash
Remote Labor Index5.0%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 2Not measured$7,524Only GPT-5.5 measured
Neither model has a result on the other 14 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index114
Reasoning benchmarks for Gemini 3.7 Flash and GPT-5.5
BenchmarkGemini 3.7 FlashGPT-5.5Leader
GPQA Diamond93.9%93.2%Gemini 3.7 Flash
LiveBench reasoning87.8%89.7%GPT-5.5
MMMU Pro (Vals AI)89.0%88.3%Gemini 3.7 Flash
GPQA Diamond (Artificial Analysis run)94.5%93.5%Gemini 3.7 Flash
Humanity's Last Exam (Artificial Analysis run)47.9%45.8%Gemini 3.7 Flash
GPQA Diamond (Epoch AI run)94.8%90.7%Gemini 3.7 Flash
ARC-AGI95.5%95.0%Gemini 3.7 Flash
ARC-AGI-284.6%85.0%GPT-5.5
SimpleBenchNot measured69.0%Only GPT-5.5 measured
Chess puzzles66.0%63.0%Gemini 3.7 Flash
Mystery game puzzles37.0%56.0%GPT-5.5
EBR-benchNot measured34.3%Only GPT-5.5 measured
LMArena Text: hard prompts14951489Gemini 3.7 Flash
LMArena Text: expert15121507Gemini 3.7 Flash
LMArena Text: hard prompts in English14871483Gemini 3.7 Flash
LMArena Vision: diagrams13291325Gemini 3.7 Flash
LMArena Vision: homework13201332GPT-5.5
Kagi LLM BenchmarkNot measured88.8%Only GPT-5.5 measured
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index42
Math benchmarks for Gemini 3.7 Flash and GPT-5.5
BenchmarkGemini 3.7 FlashGPT-5.5Leader
OTIS Mock AIME97.2%84.4%Gemini 3.7 Flash
FrontierMath, tiers 1 to 371.6%85.3%GPT-5.5
FrontierMath, tier 436.6%72.5%GPT-5.5
ProofBench58.0%50.0%Gemini 3.7 Flash
LMArena Text: math15111487Gemini 3.7 Flash
LMArena Text: mathematical work15021496Gemini 3.7 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 3.7 Flash and GPT-5.5
BenchmarkGemini 3.7 FlashGPT-5.5Leader
MMLU Pro90.1%88.1%Gemini 3.7 Flash
LegalBench (Vals AI)87.3%86.5%Gemini 3.7 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)74.7%75.0%GPT-5.5
MortgageTax (Vals AI)66.7%68.8%GPT-5.5
MedCode (Vals AI)53.4%49.1%Gemini 3.7 Flash
SimpleQA Verified69.2%63.0%Gemini 3.7 Flash
LMArena Text: science15111485Gemini 3.7 Flash
LMArena Text: medicine and healthcare14941465Gemini 3.7 Flash
LMArena Text: legal and government14961491Gemini 3.7 Flash
LMArena Text: business and finance14791478Gemini 3.7 Flash
FACTS Benchmark Suite71.2%66.7%Gemini 3.7 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 3.7 Flash and GPT-5.5
BenchmarkGemini 3.7 FlashGPT-5.5Leader
Design Arena: websites13041256Gemini 3.7 Flash
Design Arena: UI components12991260Gemini 3.7 Flash
Design Arena: game dev13181294Gemini 3.7 Flash
Design Arena: data viz13151265Gemini 3.7 Flash
Design Arena: 3D13081198Gemini 3.7 Flash
Design Arena: all code categories13081260Gemini 3.7 Flash
Design Arena: SVG12831234Gemini 3.7 Flash
Design Arena: ASCII art12761255Gemini 3.7 Flash
LiveBench design73.2%70.3%Gemini 3.7 Flash
GeneralLike-for-likePublic boards, shown as published, kept out of the index246
General benchmarks for Gemini 3.7 Flash and GPT-5.5
BenchmarkGemini 3.7 FlashGPT-5.5Leader
LiveBench data analysis68.0%81.6%GPT-5.5
Public Benefits Bench (Vals AI)Not measured60.9%Only GPT-5.5 measured
SAGE (Vals AI)49.2%51.5%GPT-5.5
MedScribe (Vals AI)83.9%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)83.0%84.3%GPT-5.5
DTBench96.8%96.0%Gemini 3.7 Flash
LMCA50.4%54.3%GPT-5.5
Surface Evolver BenchNot measured88.1%Only GPT-5.5 measured
Furniture assembly26.7%44.2%GPT-5.5
ExploitBenchNot measured47.4%Only GPT-5.5 measured
CL-bench LifeNot measured22.2%Only GPT-5.5 measured
LMArena Text14891471Gemini 3.7 Flash
LMArena Text: instruction following14841478Gemini 3.7 Flash
LMArena Text: creative writing14881455Gemini 3.7 Flash
LMArena Vision13141297Gemini 3.7 Flash
LMArena Text: English14831470Gemini 3.7 Flash
LMArena Text: non-English14871467Gemini 3.7 Flash
LMArena Text: Chinese15521534Gemini 3.7 Flash
LMArena Text: German15061480Gemini 3.7 Flash
LMArena Text: Japanese15111499Gemini 3.7 Flash
LMArena Text: Korean14811460Gemini 3.7 Flash
LMArena Text: French15001485Gemini 3.7 Flash
LMArena Text: Spanish14951468Gemini 3.7 Flash
LMArena Text: Russian15151473Gemini 3.7 Flash
LMArena Text: Polish15031465Gemini 3.7 Flash
LMArena Text: multi-turn14851476Gemini 3.7 Flash
LMArena Text: longer queries14921484Gemini 3.7 Flash
LMArena Text: writing and language14911466Gemini 3.7 Flash
LMArena Text: entertainment and media14771449Gemini 3.7 Flash
LMArena Vision: English13091292Gemini 3.7 Flash
LMArena Vision: Chinese13941360Gemini 3.7 Flash
LMArena Vision: reading text13221306Gemini 3.7 Flash
LMArena Vision: humor12991293Gemini 3.7 Flash
LMArena Vision: recognizing thingsNot measured1231Only GPT-5.5 measured
LMArena Vision: creative writing13121301Gemini 3.7 Flash
LMArena DocumentNot measured1486Only GPT-5.5 measured
Neither model has a result on the other 8 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 3.7 Flash and GPT-5.5
BenchmarkGemini 3.7 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 3.7 Flash$0.0026Fits in one request
GPT-5.5$0.020Fits in one request

Gemini 3.7 Flash costs less

Repository review

50K input + 3K output tokens

Gemini 3.7 Flash$0.049Fits in one request
GPT-5.5$0.340Fits in one request

Gemini 3.7 Flash costs less

Agent loop

200K input + 10K output tokens

Gemini 3.7 Flash$0.188Fits in one request
GPT-5.5$1.30Fits in one request

Gemini 3.7 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 3.7 Flash and GPT-5.5
SpecificationGoogle Gemini 3.7 FlashOpenAI GPT-5.5
MakerGoogleOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedAugust 13, 2026April 24, 2026
Context window1.05M1.05M
Input $/Mtok$0.75$5.00
Output $/Mtok$3.75$30.00
Coding index58.071.3
Independent measurements behind it65
Cost per solved task$1.78$1.65
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.7 Flash better than GPT-5.5 for coding?

Pick GPT-5.5 for coding: it scores 71.3 on the Vibe Coding Index against 58.0 for Gemini 3.7 Flash, though on 5 benchmarks against 6. Pick Gemini 3.7 Flash for output tokens 8.0x cheaper ($3.75 vs $30.00 per million) and work measured by LMArena WebDev or LiveCodeBench (Vals AI), where it leads.

Which is cheaper, Gemini 3.7 Flash or GPT-5.5?

Gemini 3.7 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 3.7 Flash costs $1.78 and GPT-5.5 $1.65.

Which has the bigger context window, Gemini 3.7 Flash or GPT-5.5?

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

How many benchmarks is the Gemini 3.7 Flash vs GPT-5.5 comparison based on?

107 benchmarks have a result for both models as of October 21, 2026. Gemini 3.7 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.

Compare next

Embed this comparison on your site

Free under CC BY 4.0, while the source link stays visible. Preview the frame · Terms and other embeds

<iframe src="https://llmbenchmark.ai/embed/compare/gemini-3-7-flash-vs-gpt-5-5" title="Gemini 3.7 Flash vs GPT-5.5, LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/gemini-3-7-flash-vs-gpt-5-5">LLMBenchmark.ai, Gemini 3.7 Flash vs GPT-5.5</a></p>