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Gemini 3.7 Flash vs Gemini 4 Argon

Gemini 4 Argon leads Gemini 3.7 Flash on coding, 81.0 to 58.0 on the Vibe Coding Index, and Gemini 3.7 Flash costs 2.7x less per output token ($3.75 vs $10.00 per million). Updated October 22, 2026; 80 benchmarks have a result for both.

Replace Gemini 3.7 Flash Replace Gemini 4 Argon
Gemini 3.7 FlashGoogle
Coding
58.0
Overall
65.7
Output $/M
$3.75
4
Gemini 4 ArgonGoogle
Coding
81.0
Overall
84.0
Output $/M
$10.00
76
vs boards won of 80 shared

Gemini 3.7 Flash or Gemini 4 Argon: which to pick

Pick Gemini 4 Argon for coding: it scores 81.0 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 2.7x cheaper ($3.75 vs $10.00 per million) and work measured by Terminal-Bench 2.1 (Vals AI) or SciCode, where it leads.

Model AGemini 3.7 FlashGoogle58.0/1006 independent benchmarks$1.78 per solved taskModel BGemini 4 ArgonGoogle81.0/1005 independent benchmarksNo cost per solved task
Shared results
80
Gemini 3.7 Flash only
34
Gemini 4 Argon only
14
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, Gemini 4 Argon 81.0 from 5 benchmarks.
Widest category
Agentic work, 21.8 points apart on average over 11 shared benchmarks.
Widest single gap
Terminal-Bench 4 (Vals AI): Gemini 3.7 Flash 12.1% against Gemini 4 Argon 57.6%, 60.6 points apart on a 0 to 100 scale.
Output price
Gemini 3.7 Flash $3.75 against Gemini 4 Argon $10.00 per million output tokens, 2.7x apart.
Context window
Both take 1.05M tokens.

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 FlashBarsGemini 4 ArgonTies
Coding216
Intelligence02
Agentic work011
Reasoning19
Math06
Knowledge07
Web design07
General118
All shared boards476
CodingLike-for-likeSix of these boards feed the Vibe Coding Index216
Coding benchmarks for Gemini 3.7 Flash and Gemini 4 Argon
BenchmarkGemini 3.7 FlashGemini 4 ArgonLeader
LiveBench coding80.5%89.7%Gemini 4 Argon
LMArena WebDev15911678Gemini 4 Argon
AA Coding Index71.5Not 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%57.6%Gemini 4 Argon
Vibe Code Bench (Vals AI)70.4%91.9%Gemini 4 Argon
Code migration (Vals AI)34.8%68.2%Gemini 4 Argon
ProgramBench (Vals AI)0.0%2.5%Gemini 4 Argon
IOI (Vals AI)67.8%100.0%Gemini 4 Argon
Terminal-Bench 2.1 (Vals AI)77.5%57.7%Gemini 3.7 Flash
SWE-bench Multimodal (Vals AI)Not measured56.0%Only Gemini 4 Argon measured
Vibe Code Bench 1-100 (Vals AI)Not measured21.2%Only Gemini 4 Argon measured
SkillsBench (Vals AI)65.9%Not measuredOnly Gemini 3.7 Flash measured
CyberBench (Vals AI)43.8%77.9%Gemini 4 Argon
SciCode59.8%61.8%Gemini 4 Argon
FrontierCode43.6%47.5%Gemini 4 Argon
FrontierSWE20.3%55.0%Gemini 4 Argon
MirrorCodeNot measured58.9%Only Gemini 4 Argon measured
ALE-Bench904.32100.1Gemini 4 Argon
LMArena Text: coding14991546Gemini 4 Argon
LMArena Text: software and IT14981556Gemini 4 Argon
LMArena WebDev: React15871692Gemini 4 Argon
LMArena WebDev: HTML15931643Gemini 4 Argon
LMArena WebDev: from an image1599Not measuredOnly Gemini 3.7 Flash measured
SciCode13.8%12.3%Gemini 3.7 Flash
Neither model has a result on the other 13 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Gemini 3.7 Flash and Gemini 4 Argon
BenchmarkGemini 3.7 FlashGemini 4 ArgonLeader
AA Intelligence Index39.652.6Gemini 4 Argon
Epoch Capabilities Index158.0166.4Gemini 4 Argon
Agentic workLike-for-likePublic boards, shown as published, kept out of the index011
Agentic work benchmarks for Gemini 3.7 Flash and Gemini 4 Argon
BenchmarkGemini 3.7 FlashGemini 4 ArgonLeader
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 apps1229Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building Android apps1243Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building Godot games1264Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building games1235Not measuredOnly Gemini 3.7 Flash measured
Design Arena: spreadsheets10581157Gemini 4 Argon
LiveBench research76.5%83.1%Gemini 4 Argon
LiveBench browser56.0%92.0%Gemini 4 Argon
LiveBench long agentic28.3%69.9%Gemini 4 Argon
SREBench (Vals AI)4.6%44.3%Gemini 4 Argon
Finance Agent (Vals AI)59.0%65.4%Gemini 4 Argon
Tax Agent Bench (Vals AI)22.8%44.6%Gemini 4 Argon
Legal Research Bench (Vals AI)34.6%54.8%Gemini 4 Argon
Harvey's Legal Agent Benchmark (Vals AI)Not measured27.1%Only Gemini 4 Argon measured
Excel Modeling Benchmark (Vals AI)71.3%75.2%Gemini 4 Argon
BioMysteryBench (Vals AI)Not measured76.3%Only Gemini 4 Argon measured
Terminal-Bench-Science (Vals AI)7.1%44.3%Gemini 4 Argon
Vals Science IndexNot measured55.4%Only Gemini 4 Argon measured
Time Horizon Index (Vals AI)Not measured52.5%Only Gemini 4 Argon measured
CUA-bench (Vals AI)Not measured4.8%Only Gemini 4 Argon measured
Robo-bench (Vals AI)Not measured0.8%Only Gemini 4 Argon measured
APEX-Agents67.8%82.4%Gemini 4 Argon
Remote Labor Index5.0%Not measuredOnly Gemini 3.7 Flash measured
Vending-Bench 2Not measured$13,718Only Gemini 4 Argon measured
Neither model has a result on the other 16 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index19
Reasoning benchmarks for Gemini 3.7 Flash and Gemini 4 Argon
BenchmarkGemini 3.7 FlashGemini 4 ArgonLeader
GPQA Diamond93.9%Not measuredOnly Gemini 3.7 Flash measured
LiveBench reasoning87.8%95.1%Gemini 4 Argon
MysteryMechanism (Vals AI)Not measured45.5%Only Gemini 4 Argon 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%57.1%Gemini 4 Argon
GPQA Diamond (Epoch AI run)94.8%96.4%Gemini 4 Argon
ARC-AGI95.5%98.5%Gemini 4 Argon
ARC-AGI-284.6%91.3%Gemini 4 Argon
Chess puzzles66.0%59.0%Gemini 3.7 Flash
Mystery game puzzles37.0%64.0%Gemini 4 Argon
EBR-benchNot measured64.8%Only Gemini 4 Argon measured
LMArena Text: hard prompts14951546Gemini 4 Argon
LMArena Text: expert15121550Gemini 4 Argon
LMArena Text: hard prompts in English14871548Gemini 4 Argon
LMArena Vision: diagrams1329Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: homework1320Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index06
Math benchmarks for Gemini 3.7 Flash and Gemini 4 Argon
BenchmarkGemini 3.7 FlashGemini 4 ArgonLeader
OTIS Mock AIME97.2%100.0%Gemini 4 Argon
FrontierMath, tiers 1 to 371.6%86.0%Gemini 4 Argon
FrontierMath, tier 436.6%78.0%Gemini 4 Argon
ProofBench58.0%99.0%Gemini 4 Argon
LMArena Text: math15111536Gemini 4 Argon
LMArena Text: mathematical work15021557Gemini 4 Argon
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index07
Knowledge benchmarks for Gemini 3.7 Flash and Gemini 4 Argon
BenchmarkGemini 3.7 FlashGemini 4 ArgonLeader
MMLU Pro90.1%Not measuredOnly Gemini 3.7 Flash measured
LegalBench (Vals AI)87.3%88.3%Gemini 4 Argon
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%58.8%Gemini 4 Argon
SimpleQA Verified69.2%76.0%Gemini 4 Argon
LMArena Text: science15111548Gemini 4 Argon
LMArena Text: medicine and healthcare14941555Gemini 4 Argon
LMArena Text: legal and government14961548Gemini 4 Argon
LMArena Text: business and finance14791525Gemini 4 Argon
FACTS Benchmark Suite71.2%Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for Gemini 3.7 Flash and Gemini 4 Argon
BenchmarkGemini 3.7 FlashGemini 4 ArgonLeader
Design Arena: websites13031315Gemini 4 Argon
Design Arena: UI components12961333Gemini 4 Argon
Design Arena: game dev13171377Gemini 4 Argon
Design Arena: data viz13151332Gemini 4 Argon
Design Arena: 3D13071388Gemini 4 Argon
Design Arena: all code categories13081329Gemini 4 Argon
Design Arena: SVG1283Not measuredOnly Gemini 3.7 Flash measured
Design Arena: ASCII art1276Not measuredOnly Gemini 3.7 Flash measured
LiveBench design73.2%73.7%Gemini 4 Argon
GeneralLike-for-likePublic boards, shown as published, kept out of the index118
General benchmarks for Gemini 3.7 Flash and Gemini 4 Argon
BenchmarkGemini 3.7 FlashGemini 4 ArgonLeader
Vals IndexNot measured69.2%Only Gemini 4 Argon measured
LiveBench data analysis68.0%85.2%Gemini 4 Argon
Public Benefits Bench (Vals AI)Not measured69.8%Only Gemini 4 Argon measured
SAGE (Vals AI)49.2%53.6%Gemini 4 Argon
MedScribe (Vals AI)83.9%87.4%Gemini 4 Argon
Long context reasoning (AA-LCR)83.0%79.7%Gemini 3.7 Flash
DTBench96.8%97.6%Gemini 4 Argon
LMCA50.4%63.7%Gemini 4 Argon
Furniture assembly26.7%72.5%Gemini 4 Argon
LMArena Text14891532Gemini 4 Argon
LMArena Text: instruction following14841534Gemini 4 Argon
LMArena Text: creative writing14881527Gemini 4 Argon
LMArena Vision1314Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: English14831538Gemini 4 Argon
LMArena Text: non-English14871522Gemini 4 Argon
LMArena Text: Chinese15521611Gemini 4 Argon
LMArena Text: German1506Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Japanese1511Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Korean1481Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: French1500Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Spanish14951503Gemini 4 Argon
LMArena Text: Russian15151534Gemini 4 Argon
LMArena Text: Polish1503Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: multi-turn14851556Gemini 4 Argon
LMArena Text: longer queries14921547Gemini 4 Argon
LMArena Text: writing and language14911529Gemini 4 Argon
LMArena Text: entertainment and media14771527Gemini 4 Argon
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
Neither model has a result on the other 14 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 Gemini 4 Argon
BenchmarkGemini 3.7 FlashGemini 4 ArgonLeader
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
Gemini 4 Argon$0.0070Fits 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
Gemini 4 Argon$0.130Fits 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
Gemini 4 Argon$0.500Fits 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 Gemini 4 Argon
SpecificationGoogle Gemini 3.7 FlashGoogle Gemini 4 Argon
MakerGoogleGoogle
WeightsNo public weights listedNo public weights listed
ReleasedAugust 13, 2026October 13, 2026
Context window1.05M1.05M
Input $/Mtok$0.75$2.00
Output $/Mtok$3.75$10.00
Coding index58.081.0
Independent measurements behind it65
Cost per solved task$1.78Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.7 Flash better than Gemini 4 Argon for coding?

Pick Gemini 4 Argon for coding: it scores 81.0 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 2.7x cheaper ($3.75 vs $10.00 per million) and work measured by Terminal-Bench 2.1 (Vals AI) or SciCode, where it leads.

Which is cheaper, Gemini 3.7 Flash or Gemini 4 Argon?

Gemini 3.7 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; Gemini 4 Argon costs $2.00 and $10.00. Cost per solved task is known for Gemini 3.7 Flash only.

Which has the bigger context window, Gemini 3.7 Flash or Gemini 4 Argon?

Neither: both take 1.05M tokens.

How many benchmarks is the Gemini 3.7 Flash vs Gemini 4 Argon comparison based on?

80 benchmarks have a result for both models as of October 22, 2026. Gemini 3.7 Flash's coding index rests on 6 independent benchmarks and Gemini 4 Argon's on 5. Where only one model has a result, the page says so instead of naming a winner.

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