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Gemini 3.7 Flash vs GPT-6.1 Terra

GPT-6.1 Terra leads Gemini 3.7 Flash on coding, 77.4 to 54.0 on the Vibe Coding Index, and Gemini 3.7 Flash costs 1.3x less per output token ($3.75 vs $5.00 per million). Updated October 29, 2026; 23 benchmarks have a result for both.

Gemini 3.7 FlashGoogle
Coding
54.0
Overall
66.4
Output $/M
$3.75
10
GPT-6.1 TerraOpenAI
Coding
77.4
Overall
76.8
Output $/M
$5.00
13
vs boards won of 23 shared

Gemini 3.7 Flash or GPT-6.1 Terra: which to pick

Pick GPT-6.1 Terra for coding: it scores 77.4 on the Vibe Coding Index against 54.0 for Gemini 3.7 Flash, though on 4 benchmarks against 5.

Pick Gemini 3.7 Flash for output tokens 1.3x cheaper ($3.75 vs $5.00 per million) and work measured by SciCode or Tax Agent Bench (Vals AI), where it leads.

Shared results
23
Gemini 3.7 Flash only
85
GPT-6.1 Terra only
13
Like-for-like categories
7 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 54.0 from 5 benchmarks, GPT-6.1 Terra 77.4 from 4 benchmarks.
Widest category
General, 26.4 points apart on average over 2 shared benchmarks.
Widest single gap
ALE-Bench: Gemini 3.7 Flash 904.3 against GPT-6.1 Terra 2608.8, 56.8 points apart on a 0 to 100 scale.
Output price
Gemini 3.7 Flash $3.75 against GPT-6.1 Terra $5.00 per million output tokens, 1.3x apart.
Context window
Gemini 3.7 Flash takes 1.05M tokens, GPT-6.1 Terra 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-6.1 TerraTies
Coding16
Agentic work21
Reasoning21
Math03
Knowledge10
Web design31
General11
All shared boards1013
CodingLike-for-likeSix of these boards feed the Vibe Coding Index16
Coding benchmarks for Gemini 3.7 Flash and GPT-6.1 Terra
BenchmarkGemini 3.7 FlashGPT-6.1 TerraLeader
LiveBench codingNot measured94.3%Only GPT-6.1 Terra measured
LMArena WebDev15901673GPT-6.1 Terra
AA Coding Index76.1Not measuredOnly Gemini 3.7 Flash measured
LiveCodeBench (Vals AI)88.7%Not measuredOnly Gemini 3.7 Flash measured
SWE-bench Verified (Vals AI)80.8%Not measuredOnly Gemini 3.7 Flash measured
Terminal-Bench 4 (Vals AI)12.1%49.5%GPT-6.1 Terra
Vibe Code Bench (Vals AI)70.4%84.0%GPT-6.1 Terra
Code migration (Vals AI)34.8%Not measuredOnly Gemini 3.7 Flash measured
ProgramBench (Vals AI)0.0%Not measuredOnly Gemini 3.7 Flash measured
IOI (Vals AI)67.8%Not measuredOnly Gemini 3.7 Flash measured
Terminal-Bench 2.1 (Vals AI)77.5%Not measuredOnly Gemini 3.7 Flash measured
SkillsBench (Vals AI)65.9%Not measuredOnly Gemini 3.7 Flash measured
CyberBench (Vals AI)43.8%Not measuredOnly Gemini 3.7 Flash measured
SciCode59.8%55.1%Gemini 3.7 Flash
FrontierCode43.6%Not measuredOnly Gemini 3.7 Flash measured
FrontierSWE20.3%Not measuredOnly Gemini 3.7 Flash measured
MirrorCode41.1%Not measuredOnly Gemini 3.7 Flash measured
ALE-Bench904.32608.8GPT-6.1 Terra
LMArena Text: coding1500Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: software and IT1499Not measuredOnly Gemini 3.7 Flash measured
LMArena WebDev: React15861657GPT-6.1 Terra
LMArena WebDev: HTML15911719GPT-6.1 Terra
LMArena WebDev: from an image1599Not measuredOnly Gemini 3.7 Flash measured
SciCode13.8%Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 19 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Gemini 3.7 Flash and GPT-6.1 Terra
BenchmarkGemini 3.7 FlashGPT-6.1 TerraLeader
AA Intelligence IndexNot measured51.0Only GPT-6.1 Terra measured
Epoch Capabilities Index158.0Not measuredOnly Gemini 3.7 Flash measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index21
Agentic work benchmarks for Gemini 3.7 Flash and GPT-6.1 Terra
BenchmarkGemini 3.7 FlashGPT-6.1 TerraLeader
AA Agentic Index35.2Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building web apps1223Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building full-stack apps1208Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building mobile apps1230Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building Android apps1240Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building Godot games1264Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building games1198Not measuredOnly Gemini 3.7 Flash measured
Design Arena: spreadsheets1104Not measuredOnly Gemini 3.7 Flash measured
LiveBench researchNot measured73.9%Only GPT-6.1 Terra measured
LiveBench browserNot measured93.1%Only GPT-6.1 Terra measured
LiveBench long agenticNot measured48.6%Only GPT-6.1 Terra measured
SREBench (Vals AI)4.6%Not measuredOnly Gemini 3.7 Flash measured
Finance Agent (Vals AI)59.0%Not measuredOnly Gemini 3.7 Flash measured
Tax Agent Bench (Vals AI)22.8%15.2%Gemini 3.7 Flash
Legal Research Bench (Vals AI)34.6%26.0%Gemini 3.7 Flash
Harvey's Legal Agent Benchmark (Vals AI)Not measured1.7%Only GPT-6.1 Terra measured
Excel Modeling Benchmark (Vals AI)71.3%Not measuredOnly Gemini 3.7 Flash measured
Terminal-Bench-Science (Vals AI)7.1%Not measuredOnly Gemini 3.7 Flash measured
APEX-Agents67.8%68.3%GPT-6.1 Terra
Remote Labor Index5.0%Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 22 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index21
Reasoning benchmarks for Gemini 3.7 Flash and GPT-6.1 Terra
BenchmarkGemini 3.7 FlashGPT-6.1 TerraLeader
GPQA Diamond93.9%Not measuredOnly Gemini 3.7 Flash measured
LiveBench reasoningNot measured88.7%Only GPT-6.1 Terra measured
MMMU Pro (Vals AI)89.0%Not measuredOnly Gemini 3.7 Flash measured
GPQA Diamond (Artificial Analysis run)94.5%Not measuredOnly Gemini 3.7 Flash measured
Humanity's Last Exam (Artificial Analysis run)47.9%46.2%Gemini 3.7 Flash
GPQA Diamond (Epoch AI run)94.8%94.3%Gemini 3.7 Flash
ARC-AGI95.5%Not measuredOnly Gemini 3.7 Flash measured
ARC-AGI-284.6%Not measuredOnly Gemini 3.7 Flash measured
Chess puzzles66.0%Not measuredOnly Gemini 3.7 Flash measured
Mystery game puzzles37.0%74.0%GPT-6.1 Terra
EBR-benchNot measured78.1%Only GPT-6.1 Terra measured
LMArena Text: hard prompts1497Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: expert1514Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: hard prompts in English1489Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: diagrams1329Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: homework1320Not measuredOnly Gemini 3.7 Flash measured
Humanity's Last Exam (Scale run)Not measured35.7%Only GPT-6.1 Terra measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for Gemini 3.7 Flash and GPT-6.1 Terra
BenchmarkGemini 3.7 FlashGPT-6.1 TerraLeader
OTIS Mock AIME97.2%100.0%GPT-6.1 Terra
FrontierMath, tiers 1 to 371.6%90.9%GPT-6.1 Terra
FrontierMath, tier 436.6%92.7%GPT-6.1 Terra
ProofBench58.0%Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: math1507Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: mathematical work1501Not measuredOnly Gemini 3.7 Flash measured
MathArena25.7%Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for Gemini 3.7 Flash and GPT-6.1 Terra
BenchmarkGemini 3.7 FlashGPT-6.1 TerraLeader
MMLU Pro90.1%Not measuredOnly Gemini 3.7 Flash measured
LegalBench (Vals AI)87.3%Not measuredOnly Gemini 3.7 Flash measured
TaxEval (Vals AI)74.7%Not measuredOnly Gemini 3.7 Flash measured
MortgageTax (Vals AI)66.7%Not measuredOnly Gemini 3.7 Flash measured
MedCode (Vals AI)53.4%Not measuredOnly Gemini 3.7 Flash measured
SimpleQA Verified69.2%57.3%Gemini 3.7 Flash
LMArena Text: science1511Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: medicine and healthcare1497Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: legal and government1497Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: business and finance1480Not measuredOnly Gemini 3.7 Flash measured
FACTS Benchmark Suite65.4%Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 9 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index31
Web design benchmarks for Gemini 3.7 Flash and GPT-6.1 Terra
BenchmarkGemini 3.7 FlashGPT-6.1 TerraLeader
Design Arena: websites13021283Gemini 3.7 Flash
Design Arena: UI components12921277Gemini 3.7 Flash
Design Arena: game dev13181348GPT-6.1 Terra
Design Arena: data viz1318Not measuredOnly Gemini 3.7 Flash measured
Design Arena: 3D1306Not measuredOnly Gemini 3.7 Flash measured
Design Arena: all code categories13061295Gemini 3.7 Flash
Design Arena: SVG1281Not measuredOnly Gemini 3.7 Flash measured
Design Arena: ASCII art1280Not measuredOnly Gemini 3.7 Flash measured
LiveBench designNot measured82.3%Only GPT-6.1 Terra measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
General benchmarks for Gemini 3.7 Flash and GPT-6.1 Terra
BenchmarkGemini 3.7 FlashGPT-6.1 TerraLeader
Vals IndexNot measured60.5%Only GPT-6.1 Terra measured
LiveBench data analysisNot measured82.3%Only GPT-6.1 Terra measured
MedScribe (Vals AI)83.9%Not measuredOnly Gemini 3.7 Flash measured
Long context reasoning (AA-LCR)83.0%82.7%Gemini 3.7 Flash
DTBench96.8%Not measuredOnly Gemini 3.7 Flash measured
LMCA50.4%Not measuredOnly Gemini 3.7 Flash measured
Furniture assembly26.7%79.2%GPT-6.1 Terra
LMArena Text1489Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: instruction following1486Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: creative writing1487Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision1314Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: English1485Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: non-English1486Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Chinese1554Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: German1515Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Japanese1514Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Korean1484Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: French1495Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Spanish1489Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Russian1513Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Polish1504Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: multi-turn1485Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: longer queries1494Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: writing and language1490Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: entertainment and media1475Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: English1309Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: Chinese1394Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: reading text1322Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: humor1299Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: creative writing1312Not measuredOnly Gemini 3.7 Flash measured
MultiChallengeNot measured74.2%Only GPT-6.1 Terra measured
Neither model has a result on the other 17 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-6.1 Terra
BenchmarkGemini 3.7 FlashGPT-6.1 TerraLeader
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-6.1 Terra$0.0035Fits 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-6.1 Terra$0.065Fits 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-6.1 Terra$0.250Fits 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-6.1 Terra
SpecificationGoogle Gemini 3.7 FlashOpenAI GPT-6.1 Terra
MakerGoogleOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedAugust 13, 2026October 26, 2026
Context window1.05M1.05M
Input $/Mtok$0.75$1.00
Output $/Mtok$3.75$5.00
Coding index54.077.4
Independent measurements behind it54
Cost per solved task$1.78Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.7 Flash better than GPT-6.1 Terra for coding?

Pick GPT-6.1 Terra for coding: it scores 77.4 on the Vibe Coding Index against 54.0 for Gemini 3.7 Flash, though on 4 benchmarks against 5. Pick Gemini 3.7 Flash for output tokens 1.3x cheaper ($3.75 vs $5.00 per million) and work measured by SciCode or Tax Agent Bench (Vals AI), where it leads.

Which is cheaper, Gemini 3.7 Flash or GPT-6.1 Terra?

Gemini 3.7 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; GPT-6.1 Terra costs $1.00 and $5.00. Cost per solved task is known for Gemini 3.7 Flash only.

Which has the bigger context window, Gemini 3.7 Flash or GPT-6.1 Terra?

GPT-6.1 Terra, with 1.05M tokens against 1.05M.

How many benchmarks is the Gemini 3.7 Flash vs GPT-6.1 Terra comparison based on?

23 benchmarks have a result for both models as of October 29, 2026. Gemini 3.7 Flash's coding index rests on 5 independent benchmarks and GPT-6.1 Terra's on 4. 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-3-7-flash-vs-gpt-6-1-terra">LLMBenchmark.ai, Gemini 3.7 Flash vs GPT-6.1 Terra</a></p>