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Gemini 4 Argon vs GPT-5.2 Pro

Gemini 4 Argon costs 16.8x less per output token than GPT-5.2 Pro ($10.00 vs $168.00 per million). Updated October 21, 2026; 6 benchmarks have a result for both.

Gemini 4 ArgonGoogle
Coding
81.0
Overall
52.6
Output $/M
$10.00
5
GPT-5.2 ProOpenAI
Coding
No data
Overall
No data
Output $/M
$168.00
1
vs boards won of 6 shared

Gemini 4 Argon or GPT-5.2 Pro: which to pick

Only Gemini 4 Argon has a coding score, 81.0 on the Vibe Coding Index; GPT-5.2 Pro has none, so the two cannot be ranked on coding.

Pick GPT-5.2 Pro for work measured by Chess puzzles, where it leads.

Shared results
6
Gemini 4 Argon only
86
GPT-5.2 Pro only
1
Like-for-like categories
3 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 4 Argon 81.0 from 5 benchmarks, GPT-5.2 Pro not benchmarked.
Widest category
Math, 22.0 points apart on average over 2 shared benchmarks.
Widest single gap
ARC-AGI-2: Gemini 4 Argon 91.3% against GPT-5.2 Pro 54.2%, 37.1 points apart on a 0 to 100 scale.
Output price
Gemini 4 Argon $10.00 against GPT-5.2 Pro $168.00 per million output tokens, 16.8x apart.
Context window
Gemini 4 Argon takes 1.05M tokens, GPT-5.2 Pro 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 4 ArgonBarsGPT-5.2 ProTies
Intelligence10
Reasoning21
Math20
All shared boards51
CodingDirectional onlySix of these boards feed the Vibe Coding Index19 boards, none shared
Coding benchmarks for Gemini 4 Argon and GPT-5.2 Pro
BenchmarkGemini 4 ArgonGPT-5.2 ProLeader
LiveBench coding89.7%Not measuredOnly Gemini 4 Argon measured
LMArena WebDev1678Not measuredOnly Gemini 4 Argon measured
Terminal-Bench 4 (Vals AI)57.6%Not measuredOnly Gemini 4 Argon measured
Vibe Code Bench (Vals AI)91.9%Not measuredOnly Gemini 4 Argon measured
Code migration (Vals AI)68.2%Not measuredOnly Gemini 4 Argon measured
ProgramBench (Vals AI)2.5%Not measuredOnly Gemini 4 Argon measured
IOI (Vals AI)100.0%Not measuredOnly Gemini 4 Argon measured
Terminal-Bench 2.1 (Vals AI)57.7%Not measuredOnly Gemini 4 Argon measured
SWE-bench Multimodal (Vals AI)56.0%Not measuredOnly Gemini 4 Argon measured
Vibe Code Bench 1-100 (Vals AI)21.2%Not measuredOnly Gemini 4 Argon measured
CyberBench (Vals AI)77.9%Not measuredOnly Gemini 4 Argon measured
SciCode61.8%Not measuredOnly Gemini 4 Argon measured
FrontierCode47.5%Not measuredOnly Gemini 4 Argon measured
FrontierSWE55.0%Not measuredOnly Gemini 4 Argon measured
ALE-Bench2100.1Not measuredOnly Gemini 4 Argon measured
LMArena Text: coding1546Not measuredOnly Gemini 4 Argon measured
LMArena Text: software and IT1556Not measuredOnly Gemini 4 Argon measured
LMArena WebDev: React1692Not measuredOnly Gemini 4 Argon measured
LMArena WebDev: HTML1643Not measuredOnly Gemini 4 Argon measured
Neither model has a result on the other 19 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Gemini 4 Argon and GPT-5.2 Pro
BenchmarkGemini 4 ArgonGPT-5.2 ProLeader
AA Intelligence Index52.6Not measuredOnly Gemini 4 Argon measured
Epoch Capabilities Index166.4156.3Gemini 4 Argon
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index18 boards, none shared
Agentic work benchmarks for Gemini 4 Argon and GPT-5.2 Pro
BenchmarkGemini 4 ArgonGPT-5.2 ProLeader
Design Arena: spreadsheets1142Not measuredOnly Gemini 4 Argon measured
LiveBench research83.1%Not measuredOnly Gemini 4 Argon measured
LiveBench browser92.0%Not measuredOnly Gemini 4 Argon measured
LiveBench long agentic69.9%Not measuredOnly Gemini 4 Argon measured
SREBench (Vals AI)44.3%Not measuredOnly Gemini 4 Argon measured
Finance Agent (Vals AI)65.4%Not measuredOnly Gemini 4 Argon measured
Tax Agent Bench (Vals AI)44.6%Not measuredOnly Gemini 4 Argon measured
Legal Research Bench (Vals AI)54.8%Not measuredOnly Gemini 4 Argon measured
Harvey's Legal Agent Benchmark (Vals AI)27.1%Not measuredOnly Gemini 4 Argon measured
Excel Modeling Benchmark (Vals AI)75.2%Not measuredOnly Gemini 4 Argon measured
BioMysteryBench (Vals AI)76.3%Not measuredOnly Gemini 4 Argon measured
Terminal-Bench-Science (Vals AI)44.3%Not measuredOnly Gemini 4 Argon measured
Vals Science Index55.4%Not measuredOnly Gemini 4 Argon measured
Time Horizon Index (Vals AI)52.5%Not measuredOnly Gemini 4 Argon measured
CUA-bench (Vals AI)4.8%Not measuredOnly Gemini 4 Argon measured
Robo-bench (Vals AI)0.8%Not measuredOnly Gemini 4 Argon measured
APEX-Agents82.4%Not measuredOnly Gemini 4 Argon measured
Vending-Bench 2$13,718Not measuredOnly Gemini 4 Argon measured
Neither model has a result on the other 21 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index21
Reasoning benchmarks for Gemini 4 Argon and GPT-5.2 Pro
BenchmarkGemini 4 ArgonGPT-5.2 ProLeader
LiveBench reasoning95.1%Not measuredOnly Gemini 4 Argon measured
MysteryMechanism (Vals AI)45.5%Not measuredOnly Gemini 4 Argon measured
Humanity's Last Exam (Artificial Analysis run)57.1%Not measuredOnly Gemini 4 Argon measured
GPQA Diamond (Epoch AI run)96.4%Not measuredOnly Gemini 4 Argon measured
ARC-AGI98.5%90.5%Gemini 4 Argon
ARC-AGI-291.3%54.2%Gemini 4 Argon
SimpleBenchNot measured57.4%Only GPT-5.2 Pro measured
Chess puzzles59.0%60.0%GPT-5.2 Pro
Mystery game puzzles64.0%Not measuredOnly Gemini 4 Argon measured
EBR-bench64.8%Not measuredOnly Gemini 4 Argon measured
LMArena Text: hard prompts1546Not measuredOnly Gemini 4 Argon measured
LMArena Text: expert1550Not measuredOnly Gemini 4 Argon measured
LMArena Text: hard prompts in English1548Not measuredOnly Gemini 4 Argon measured
Neither model has a result on the other 8 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Gemini 4 Argon and GPT-5.2 Pro
BenchmarkGemini 4 ArgonGPT-5.2 ProLeader
OTIS Mock AIME100.0%Not measuredOnly Gemini 4 Argon measured
FrontierMath, tiers 1 to 386.0%74.0%Gemini 4 Argon
FrontierMath, tier 478.0%46.0%Gemini 4 Argon
ProofBench99.0%Not measuredOnly Gemini 4 Argon measured
LMArena Text: math1536Not measuredOnly Gemini 4 Argon measured
LMArena Text: mathematical work1557Not measuredOnly Gemini 4 Argon measured
Neither model has a result on the other 7 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Knowledge benchmarks for Gemini 4 Argon and GPT-5.2 Pro
BenchmarkGemini 4 ArgonGPT-5.2 ProLeader
LegalBench (Vals AI)88.3%Not measuredOnly Gemini 4 Argon measured
MedCode (Vals AI)58.8%Not measuredOnly Gemini 4 Argon measured
SimpleQA Verified76.0%Not measuredOnly Gemini 4 Argon measured
LMArena Text: science1548Not measuredOnly Gemini 4 Argon measured
LMArena Text: medicine and healthcare1555Not measuredOnly Gemini 4 Argon measured
LMArena Text: legal and government1548Not measuredOnly Gemini 4 Argon measured
LMArena Text: business and finance1525Not measuredOnly Gemini 4 Argon measured
Neither model has a result on the other 10 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for Gemini 4 Argon and GPT-5.2 Pro
BenchmarkGemini 4 ArgonGPT-5.2 ProLeader
Design Arena: websites1315Not measuredOnly Gemini 4 Argon measured
Design Arena: UI components1331Not measuredOnly Gemini 4 Argon measured
Design Arena: game dev1375Not measuredOnly Gemini 4 Argon measured
Design Arena: data viz1336Not measuredOnly Gemini 4 Argon measured
Design Arena: 3D1389Not measuredOnly Gemini 4 Argon measured
Design Arena: all code categories1329Not measuredOnly Gemini 4 Argon measured
LiveBench design73.7%Not measuredOnly Gemini 4 Argon measured
Neither model has a result on the other 2 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index21 boards, none shared
General benchmarks for Gemini 4 Argon and GPT-5.2 Pro
BenchmarkGemini 4 ArgonGPT-5.2 ProLeader
Vals Index69.2%Not measuredOnly Gemini 4 Argon measured
LiveBench data analysis85.2%Not measuredOnly Gemini 4 Argon measured
Public Benefits Bench (Vals AI)69.8%Not measuredOnly Gemini 4 Argon measured
SAGE (Vals AI)53.6%Not measuredOnly Gemini 4 Argon measured
MedScribe (Vals AI)87.4%Not measuredOnly Gemini 4 Argon measured
Long context reasoning (AA-LCR)79.7%Not measuredOnly Gemini 4 Argon measured
DTBench97.6%Not measuredOnly Gemini 4 Argon measured
LMCA63.7%Not measuredOnly Gemini 4 Argon measured
Furniture assembly72.5%Not measuredOnly Gemini 4 Argon measured
LMArena Text1532Not measuredOnly Gemini 4 Argon measured
LMArena Text: instruction following1534Not measuredOnly Gemini 4 Argon measured
LMArena Text: creative writing1527Not measuredOnly Gemini 4 Argon measured
LMArena Text: English1538Not measuredOnly Gemini 4 Argon measured
LMArena Text: non-English1522Not measuredOnly Gemini 4 Argon measured
LMArena Text: Chinese1611Not measuredOnly Gemini 4 Argon measured
LMArena Text: Spanish1503Not measuredOnly Gemini 4 Argon measured
LMArena Text: Russian1534Not measuredOnly Gemini 4 Argon measured
LMArena Text: multi-turn1556Not measuredOnly Gemini 4 Argon measured
LMArena Text: longer queries1547Not measuredOnly Gemini 4 Argon measured
LMArena Text: writing and language1529Not measuredOnly Gemini 4 Argon measured
LMArena Text: entertainment and media1527Not measuredOnly Gemini 4 Argon measured
Neither model has a result on the other 25 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 4 Argon and GPT-5.2 Pro
BenchmarkGemini 4 ArgonGPT-5.2 ProLeader
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 4 Argon$0.0070Fits in one request
GPT-5.2 Pro$0.105Fits in one request

Gemini 4 Argon costs less

Repository review

50K input + 3K output tokens

Gemini 4 Argon$0.130Fits in one request
GPT-5.2 Pro$1.55Fits in one request

Gemini 4 Argon costs less

Agent loop

200K input + 10K output tokens

Gemini 4 Argon$0.500Fits in one request
GPT-5.2 Pro$5.88Fits in one request

Gemini 4 Argon 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 4 Argon and GPT-5.2 Pro
SpecificationGoogle Gemini 4 ArgonOpenAI GPT-5.2 Pro
MakerGoogleOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedOctober 13, 2026December 10, 2025
Context window1.05M400K
Input $/Mtok$2.00$21.00
Output $/Mtok$10.00$168.00
Coding index81.0Not benchmarked
Independent measurements behind it50
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 4 Argon better than GPT-5.2 Pro for coding?

Only Gemini 4 Argon has a coding score, 81.0 on the Vibe Coding Index; GPT-5.2 Pro has none, so the two cannot be ranked on coding. Pick GPT-5.2 Pro for work measured by Chess puzzles, where it leads.

Which is cheaper, Gemini 4 Argon or GPT-5.2 Pro?

Gemini 4 Argon costs $2.00 per million input tokens and $10.00 per million output tokens; GPT-5.2 Pro costs $21.00 and $168.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Gemini 4 Argon or GPT-5.2 Pro?

Gemini 4 Argon, with 1.05M tokens against 400K.

How many benchmarks is the Gemini 4 Argon vs GPT-5.2 Pro comparison based on?

6 benchmarks have a result for both models as of October 21, 2026. Gemini 4 Argon's coding index rests on 5 independent benchmarks and GPT-5.2 Pro's on 0. Where only one model has a result, the page says so instead of naming a winner.

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