Gemini 3.8 Flash vs GPT-5.2

Gemini 3.8 Flash leads GPT-5.2 on coding, 61.6 to 55.9 on the Vibe Coding Index, and Gemini 3.8 Flash costs 3.7x less per output token ($3.75 vs $14.00 per million). Updated October 22, 2026; 86 benchmarks have a result for both.

Replace Gemini 3.8 Flash Replace GPT-5.2

Gemini 3.8 FlashGoogle

Coding: 61.6
Overall: 69.0
Output $/M: $3.75

GPT-5.2OpenAI

Coding: 55.9
Overall: 60.7
Output $/M: $14.00

vs boards won of 86 shared

Gemini 3.8 Flash or GPT-5.2: which to pick

Pick Gemini 3.8 Flash for coding: it scores 61.6 on the Vibe Coding Index against 55.9 for GPT-5.2.

Pick GPT-5.2 for a lower cost per solved task ($1.91 against $2.74) and work measured by ALE-Bench or FrontierMath, tier 4, where it leads.

Model AGemini 3.8 FlashGoogle61.6/1006 independent benchmarks$2.74 per solved task Model BGPT-5.2OpenAI55.9/1003 independent benchmarks$1.91 per solved task

864228

Shared results: 86
Gemini 3.8 Flash only: 42
GPT-5.2 only: 28
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.

Coding
Vibe Coding Index, six public coding benchmarks
Gemini 3.8 Flash
Gemini 3.8 Flash scores 61.6 against 55.9.
6 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 40.9 against 30.4.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Gemini 3.8 Flash has a AA Agentic Index result, 40.2.
Directional only
Reasoning
GPQA Diamond
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 94.4% against 91.7%.
Same board, both measured
Math
AIME
No call
Only GPT-5.2 has a AIME result, 96.9%.
Directional only
Knowledge
MMLU Pro
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 90.2% against 86.2%.
Same board, both measured
Web design
Design Arena: websites
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 1300 against 1195.
Same board, both measured
General
Vals Index
No call
Only Gemini 3.8 Flash has a Vals Index result, 56.0%.
Directional only
Long documents
Listed context window
Gemini 3.8 Flash
Gemini 3.8 Flash takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 3.8 Flash
Gemini 3.8 Flash $0.0026, GPT-5.2 $0.0088 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5.2
Gemini 3.8 Flash $2.74, GPT-5.2 $1.91.
Published attempt cost and pass rate

At a glance

Coding index: Gemini 3.8 Flash 61.6 from 6 benchmarks, GPT-5.2 55.9 from 3 benchmarks.
Widest category: Web design, 16.0 points apart on average over 8 shared benchmarks.
Widest single gap: ARC-AGI-2: Gemini 3.8 Flash 89.2% against GPT-5.2 52.9%, 36.3 points apart on a 0 to 100 scale.
Output price: Gemini 3.8 Flash $3.75 against GPT-5.2 $14.00 per million output tokens, 3.7x apart.
Context window: Gemini 3.8 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
Category	Gemini 3.8 Flash	GPT-5.2
Coding	8	1
Intelligence	2	0
Agentic work	7	0
Reasoning	14	0
Math	5	1
Knowledge	8	3
Web design	8	0
General	27	2
All shared boards	79	7

CodingLike-for-likeSix of these boards feed the Vibe Coding Index81

Coding benchmarks for Gemini 3.8 Flash and GPT-5.2
Benchmark	Gemini 3.8 Flash	GPT-5.2	Leader
SWE-bench Verified	Not measured	72.8%	Only GPT-5.2 measured
SWE-bench Multilingual	Not measured	66.7%	Only GPT-5.2 measured
LiveBench coding	82.2%	Not measured	Only Gemini 3.8 Flash measured
LMArena WebDev	1585	1417	Gemini 3.8 Flash
AA Coding Index	76.3	Not measured	Only Gemini 3.8 Flash measured
LiveCodeBench (Vals AI)	89.5%	85.4%	Gemini 3.8 Flash
SWE-bench Verified (Vals AI)	80.0%	75.8%	Gemini 3.8 Flash
Terminal-Bench 4 (Vals AI)	19.7%	Not measured	Only Gemini 3.8 Flash measured
Vibe Code Bench (Vals AI)	78.7%	53.5%	Gemini 3.8 Flash
Code migration (Vals AI)	36.5%	Not measured	Only Gemini 3.8 Flash measured
ProgramBench (Vals AI)	1.0%	Not measured	Only Gemini 3.8 Flash measured
IOI (Vals AI)	56.9%	Not measured	Only Gemini 3.8 Flash measured
Terminal-Bench 2.1 (Vals AI)	81.3%	Not measured	Only Gemini 3.8 Flash measured
SWE-bench Multimodal (Vals AI)	40.8%	Not measured	Only Gemini 3.8 Flash measured
Vibe Code Bench 1-100 (Vals AI)	18.8%	Not measured	Only Gemini 3.8 Flash measured
SkillsBench (Vals AI)	58.0%	Not measured	Only Gemini 3.8 Flash measured
CyberBench (Vals AI)	43.8%	Not measured	Only Gemini 3.8 Flash measured
LiveCodeBench (Artificial Analysis run)	Not measured	89.4%	Only GPT-5.2 measured
SciCode	56.6%	Not measured	Only Gemini 3.8 Flash measured
Terminal-Bench Hard (Artificial Analysis run)	Not measured	47.0%	Only GPT-5.2 measured
Terminal-Bench	Not measured	64.9%	Only GPT-5.2 measured
FrontierCode	41.2%	Not measured	Only Gemini 3.8 Flash measured
FrontierSWE	19.6%	Not measured	Only Gemini 3.8 Flash measured
GSO-Bench	Not measured	27.5%	Only GPT-5.2 measured
WeirdML	84.8%	72.2%	Gemini 3.8 Flash
ALE-Bench	1269.7	1293.5	GPT-5.2
LMArena Text: coding	1508	1442	Gemini 3.8 Flash
LMArena Text: software and IT	1507	1434	Gemini 3.8 Flash
LMArena WebDev: React	1577	Not measured	Only Gemini 3.8 Flash measured
LMArena WebDev: HTML	1616	1427	Gemini 3.8 Flash
LMArena WebDev: from an image	1593	Not measured	Only Gemini 3.8 Flash measured
SciCode	12.3%	Not measured	Only Gemini 3.8 Flash measured
Neither model has a result on the other 7 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20

Intelligence benchmarks for Gemini 3.8 Flash and GPT-5.2
Benchmark	Gemini 3.8 Flash	GPT-5.2	Leader
AA Intelligence Index	40.9	30.4	Gemini 3.8 Flash
Epoch Capabilities Index	157.4	153.7	Gemini 3.8 Flash

Agentic workLike-for-likePublic boards, shown as published, kept out of the index70

Agentic work benchmarks for Gemini 3.8 Flash and GPT-5.2
Benchmark	Gemini 3.8 Flash	GPT-5.2	Leader
AA Agentic Index	40.2	Not measured	Only Gemini 3.8 Flash measured
Design Arena: agents building web apps	1238	1086	Gemini 3.8 Flash
Design Arena: agents building full-stack apps	1244	1043	Gemini 3.8 Flash
Design Arena: agents building mobile apps	1236	1093	Gemini 3.8 Flash
Design Arena: agents building Android apps	1079	1060	Gemini 3.8 Flash
Design Arena: agents building Godot games	1273	1142	Gemini 3.8 Flash
Design Arena: PowerPoint slides	1155	Not measured	Only Gemini 3.8 Flash measured
Design Arena: spreadsheets	1034	Not measured	Only Gemini 3.8 Flash measured
LiveBench research	79.1%	Not measured	Only Gemini 3.8 Flash measured
LiveBench browser	64.0%	Not measured	Only Gemini 3.8 Flash measured
LiveBench long agentic	30.1%	Not measured	Only Gemini 3.8 Flash measured
SREBench (Vals AI)	11.1%	Not measured	Only Gemini 3.8 Flash measured
Finance Agent (Vals AI)	61.4%	Not measured	Only Gemini 3.8 Flash measured
Tax Agent Bench (Vals AI)	32.1%	Not measured	Only Gemini 3.8 Flash measured
Legal Research Bench (Vals AI)	38.9%	Not measured	Only Gemini 3.8 Flash measured
Harvey's Legal Agent Benchmark (Vals AI)	12.1%	Not measured	Only Gemini 3.8 Flash measured
Excel Modeling Benchmark (Vals AI)	72.2%	Not measured	Only Gemini 3.8 Flash measured
BioMysteryBench (Vals AI)	62.2%	Not measured	Only Gemini 3.8 Flash measured
Terminal-Bench-Science (Vals AI)	8.6%	Not measured	Only Gemini 3.8 Flash measured
Vals Science Index	35.8%	Not measured	Only Gemini 3.8 Flash measured
Time Horizon Index (Vals AI)	18.8%	Not measured	Only Gemini 3.8 Flash measured
CUA-bench (Vals AI)	4.2%	Not measured	Only Gemini 3.8 Flash measured
τ²-Bench Telecom	Not measured	84.8%	Only GPT-5.2 measured
APEX-Agents	64.3%	Not measured	Only Gemini 3.8 Flash measured
METR time horizons	Not measured	75.3%	Only GPT-5.2 measured
Remote Labor Index	5.8%	2.5%	Gemini 3.8 Flash
GDPval	Not measured	49.7%	Only GPT-5.2 measured
DeepResearch Bench	Not measured	41.1%	Only GPT-5.2 measured
Vending-Bench 2	$5,094	$3,591	Gemini 3.8 Flash
Berkeley Function Calling Leaderboard (BFCL)	Not measured	55.9%	Only GPT-5.2 measured
Neither model has a result on the other 11 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index140

Reasoning benchmarks for Gemini 3.8 Flash and GPT-5.2
Benchmark	Gemini 3.8 Flash	GPT-5.2	Leader
GPQA Diamond	94.4%	91.7%	Gemini 3.8 Flash
LiveBench reasoning	89.3%	Not measured	Only Gemini 3.8 Flash measured
MysteryMechanism (Vals AI)	36.5%	Not measured	Only Gemini 3.8 Flash measured
MMMU Pro (Vals AI)	89.1%	86.7%	Gemini 3.8 Flash
GPQA Diamond (Artificial Analysis run)	95.3%	90.3%	Gemini 3.8 Flash
Humanity's Last Exam (Artificial Analysis run)	47.8%	37.7%	Gemini 3.8 Flash
GPQA Diamond (Epoch AI run)	95.4%	91.4%	Gemini 3.8 Flash
ARC-AGI	98.5%	86.2%	Gemini 3.8 Flash
ARC-AGI-2	89.2%	52.9%	Gemini 3.8 Flash
SimpleBench	Not measured	45.8%	Only GPT-5.2 measured
Chess puzzles	58.0%	48.0%	Gemini 3.8 Flash
Mystery game puzzles	47.0%	23.0%	Gemini 3.8 Flash
EBR-bench	Not measured	23.0%	Only GPT-5.2 measured
VPCT	Not measured	84.0%	Only GPT-5.2 measured
LMArena Text: hard prompts	1509	1428	Gemini 3.8 Flash
LMArena Text: expert	1526	1445	Gemini 3.8 Flash
LMArena Text: hard prompts in English	1504	1431	Gemini 3.8 Flash
LMArena Vision: diagrams	1345	1265	Gemini 3.8 Flash
LMArena Vision: homework	1351	1276	Gemini 3.8 Flash
Kagi LLM Benchmark	Not measured	73.3%	Only GPT-5.2 measured
Neither model has a result on the other 2 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index51

Math benchmarks for Gemini 3.8 Flash and GPT-5.2
Benchmark	Gemini 3.8 Flash	GPT-5.2	Leader
AIME	Not measured	96.9%	Only GPT-5.2 measured
MGSM (Vals AI)	Not measured	94.0%	Only GPT-5.2 measured
AA Math Index	Not measured	99.0	Only GPT-5.2 measured
AIME 2025 (Artificial Analysis run)	Not measured	99.0%	Only GPT-5.2 measured
OTIS Mock AIME	98.9%	96.1%	Gemini 3.8 Flash
FrontierMath, tiers 1 to 3	68.4%	67.4%	Gemini 3.8 Flash
FrontierMath, tier 4	22.0%	31.7%	GPT-5.2
ProofBench	48.0%	15.0%	Gemini 3.8 Flash
LMArena Text: math	1532	1440	Gemini 3.8 Flash
LMArena Text: mathematical work	1519	1442	Gemini 3.8 Flash
Neither model has a result on the other 3 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index83

Knowledge benchmarks for Gemini 3.8 Flash and GPT-5.2
Benchmark	Gemini 3.8 Flash	GPT-5.2	Leader
MMLU Pro	90.2%	86.2%	Gemini 3.8 Flash
LegalBench (Vals AI)	87.0%	82.8%	Gemini 3.8 Flash
CaseLaw (Vals AI)	Not measured	66.0%	Only GPT-5.2 measured
CorpFin (Vals AI)	Not measured	65.9%	Only GPT-5.2 measured
TaxEval (Vals AI)	74.5%	75.8%	GPT-5.2
MortgageTax (Vals AI)	65.3%	67.1%	GPT-5.2
MedQA (Vals AI)	Not measured	94.1%	Only GPT-5.2 measured
MedCode (Vals AI)	48.1%	49.8%	GPT-5.2
MMLU Pro (Artificial Analysis run)	Not measured	87.4%	Only GPT-5.2 measured
SimpleQA Verified	69.7%	37.1%	Gemini 3.8 Flash
LMArena Text: science	1523	1425	Gemini 3.8 Flash
LMArena Text: medicine and healthcare	1508	1425	Gemini 3.8 Flash
LMArena Text: legal and government	1497	1427	Gemini 3.8 Flash
LMArena Text: business and finance	1479	1414	Gemini 3.8 Flash
FACTS Benchmark Suite	69.4%	48.5%	Gemini 3.8 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 3.8 Flash and GPT-5.2
Benchmark	Gemini 3.8 Flash	GPT-5.2	Leader
Design Arena: websites	1300	1195	Gemini 3.8 Flash
Design Arena: UI components	1316	1188	Gemini 3.8 Flash
Design Arena: game dev	1304	1195	Gemini 3.8 Flash
Design Arena: data viz	1271	1202	Gemini 3.8 Flash
Design Arena: 3D	1294	1079	Gemini 3.8 Flash
Design Arena: all code categories	1303	1170	Gemini 3.8 Flash
Design Arena: SVG	1294	1139	Gemini 3.8 Flash
Design Arena: ASCII art	1264	1152	Gemini 3.8 Flash
LiveBench design	72.7%	Not measured	Only Gemini 3.8 Flash measured

GeneralLike-for-likePublic boards, shown as published, kept out of the index272

General benchmarks for Gemini 3.8 Flash and GPT-5.2
Benchmark	Gemini 3.8 Flash	GPT-5.2	Leader
Vals Index	56.0%	Not measured	Only Gemini 3.8 Flash measured
LiveBench data analysis	54.0%	Not measured	Only Gemini 3.8 Flash measured
Public Benefits Bench (Vals AI)	65.3%	Not measured	Only Gemini 3.8 Flash measured
SAGE (Vals AI)	35.1%	49.3%	GPT-5.2
MedScribe (Vals AI)	84.5%	84.4%	Gemini 3.8 Flash
IFBench	Not measured	75.4%	Only GPT-5.2 measured
Long context reasoning (AA-LCR)	84.0%	82.7%	Gemini 3.8 Flash
DTBench	95.7%	90.9%	Gemini 3.8 Flash
LMCA	52.9%	43.9%	Gemini 3.8 Flash
CL-bench	Not measured	18.2%	Only GPT-5.2 measured
Surface Evolver Bench	76.9%	Not measured	Only Gemini 3.8 Flash measured
Furniture assembly	31.7%	38.3%	GPT-5.2
LMArena Text	1499	1416	Gemini 3.8 Flash
LMArena Text: instruction following	1492	1409	Gemini 3.8 Flash
LMArena Text: creative writing	1488	1376	Gemini 3.8 Flash
LMArena Vision	1315	1246	Gemini 3.8 Flash
LMArena Text: English	1498	1422	Gemini 3.8 Flash
LMArena Text: non-English	1491	1405	Gemini 3.8 Flash
LMArena Text: Chinese	1553	1447	Gemini 3.8 Flash
LMArena Text: German	1501	1444	Gemini 3.8 Flash
LMArena Text: Japanese	1507	1420	Gemini 3.8 Flash
LMArena Text: Korean	1464	1374	Gemini 3.8 Flash
LMArena Text: French	1496	1454	Gemini 3.8 Flash
LMArena Text: Spanish	1487	1413	Gemini 3.8 Flash
LMArena Text: Russian	1514	1415	Gemini 3.8 Flash
LMArena Text: Polish	1497	1426	Gemini 3.8 Flash
LMArena Text: multi-turn	1503	1419	Gemini 3.8 Flash
LMArena Text: longer queries	1507	1413	Gemini 3.8 Flash
LMArena Text: writing and language	1494	1392	Gemini 3.8 Flash
LMArena Text: entertainment and media	1480	1378	Gemini 3.8 Flash
LMArena Vision: English	1318	1243	Gemini 3.8 Flash
LMArena Vision: Chinese	1416	1305	Gemini 3.8 Flash
LMArena Vision: reading text	1333	1257	Gemini 3.8 Flash
LMArena Vision: humor	1321	1227	Gemini 3.8 Flash
LMArena Vision: captioning	Not measured	1267	Only GPT-5.2 measured
LMArena Vision: recognizing things	Not measured	1232	Only GPT-5.2 measured
LMArena Vision: creative writing	1299	1225	Gemini 3.8 Flash
LMArena Document	Not measured	1405	Only GPT-5.2 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 3.8 Flash and GPT-5.2
Benchmark	Gemini 3.8 Flash	GPT-5.2	Leader
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 3.8 Flash$0.0026Fits in one request

GPT-5.2$0.0088Fits in one request

Gemini 3.8 Flash costs less

Repository review

50K input + 3K output tokens

Gemini 3.8 Flash$0.049Fits in one request

GPT-5.2$0.130Fits in one request

Gemini 3.8 Flash costs less

Agent loop

200K input + 10K output tokens

Gemini 3.8 Flash$0.188Fits in one request

GPT-5.2$0.490Fits in one request

Gemini 3.8 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 3.8 Flash and GPT-5.2
Specification	Google Gemini 3.8 Flash	OpenAI GPT-5.2
Maker	Google	OpenAI
Weights	No public weights listed	No public weights listed
Released	September 2, 2026	December 10, 2025
Context window	1.05M	400K
Input $/Mtok	$0.75	$1.75
Output $/Mtok	$3.75	$14.00
Coding index	61.6	55.9
Independent measurements behind it	6	3
Cost per solved task	$2.74	$1.91
Source	OpenRouter listing	OpenRouter listing

Questions

Is Gemini 3.8 Flash better than GPT-5.2 for coding?

Pick Gemini 3.8 Flash for coding: it scores 61.6 on the Vibe Coding Index against 55.9 for GPT-5.2. Pick GPT-5.2 for a lower cost per solved task ($1.91 against $2.74) and work measured by ALE-Bench or FrontierMath, tier 4, where it leads.

Which is cheaper, Gemini 3.8 Flash or GPT-5.2?

Gemini 3.8 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; GPT-5.2 costs $1.75 and $14.00. Per solved SWE-bench Verified task, Gemini 3.8 Flash costs $2.74 and GPT-5.2 $1.91.

Which has the bigger context window, Gemini 3.8 Flash or GPT-5.2?

Gemini 3.8 Flash, with 1.05M tokens against 400K.

How many benchmarks is the Gemini 3.8 Flash vs GPT-5.2 comparison based on?

86 benchmarks have a result for both models as of October 22, 2026. Gemini 3.8 Flash's coding index rests on 6 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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Gemini 3.8 Flash or GPT-5.2: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Math

Knowledge

Web design

General

Long documents

Everyday cost

Cost per solved task

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

Compare next