Gemini 3.8 Flash vs gpt-oss-120b

Gemini 3.8 Flash leads gpt-oss-120b on the Artificial Analysis Intelligence Index, 40.9 to 11.6, and gpt-oss-120b costs 7.5x less per output token ($0.50 vs $3.75 per million). Updated October 21, 2026; 59 benchmarks have a result for both.

Replace Gemini 3.8 Flash Replace gpt-oss-120b

Gemini 3.8 FlashGoogle

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

gpt-oss-120bOpenAI

Coding: No data
Overall: 50.0
Output $/M: $0.50

vs boards won of 59 shared

Gemini 3.8 Flash or gpt-oss-120b: which to pick

Only Gemini 3.8 Flash has a coding score, 61.6 on the Vibe Coding Index; gpt-oss-120b has none, so the two cannot be ranked on coding.

Pick gpt-oss-120b for output tokens 7.5x cheaper ($0.50 vs $3.75 per million) and a lower cost per solved task ($0.51 against $2.74).

Model AGemini 3.8 FlashGoogle61.6/1006 independent benchmarks$2.74 per solved task Model Bgpt-oss-120bOpenAINot benchmarked1 independent benchmark$0.51 per solved task

596922

Shared results: 59
Gemini 3.8 Flash only: 69
gpt-oss-120b only: 22
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
No call
Only Gemini 3.8 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 40.9 against 11.6.
Same board, both measured
Agentic work
AA Agentic Index
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 40.2 against 3.7.
Same board, both measured
Reasoning
GPQA Diamond
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 94.4% against 78.5%.
Same board, both measured
Math
AIME
No call
Only gpt-oss-120b has a AIME result, 92.6%.
Directional only
Knowledge
MMLU Pro
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 90.2% against 79.2%.
Same board, both measured
Web design
Design Arena: websites
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 1300 against 968.
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 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
gpt-oss-120b
Gemini 3.8 Flash $0.0026, gpt-oss-120b $0.0003 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
gpt-oss-120b
Gemini 3.8 Flash $2.74, gpt-oss-120b $0.51.
Published attempt cost and pass rate

At a glance

Coding index: Gemini 3.8 Flash 61.6 from 6 benchmarks, gpt-oss-120b not benchmarked.
Widest category: Web design, 42.8 points apart on average over 6 shared benchmarks.
Widest single gap: APEX-Agents: Gemini 3.8 Flash 64.3% against gpt-oss-120b 4.4%, 59.9 points apart on a 0 to 100 scale.
Output price: Gemini 3.8 Flash $3.75 against gpt-oss-120b $0.50 per million output tokens, 7.5x apart.
Context window: Gemini 3.8 Flash takes 1.05M tokens, gpt-oss-120b 131K.

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	Bars	gpt-oss-120b	Ties
Coding	9		0
Intelligence	2		0
Agentic work	3		0
Reasoning	8		0
Math	3		0
Knowledge	7		0
Web design	6		0
General	21		0
All shared boards	59		0

CodingLike-for-likeSix of these boards feed the Vibe Coding Index90

Coding benchmarks for Gemini 3.8 Flash and gpt-oss-120b
Benchmark	Gemini 3.8 Flash	gpt-oss-120b	Leader
Aider polyglot	Not measured	41.8%	Only gpt-oss-120b measured
SWE-bench Verified	Not measured	26.0%	Only gpt-oss-120b measured
LiveBench coding	82.2%	Not measured	Only Gemini 3.8 Flash measured
LMArena WebDev	1585	Not measured	Only Gemini 3.8 Flash measured
AA Coding Index	76.3	30.4	Gemini 3.8 Flash
LiveCodeBench (Vals AI)	89.5%	83.2%	Gemini 3.8 Flash
SWE-bench Verified (Vals AI)	80.0%	33.6%	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%	Not measured	Only Gemini 3.8 Flash measured
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	87.8%	Only gpt-oss-120b measured
SciCode	56.6%	34.0%	Gemini 3.8 Flash
Terminal-Bench Hard (Artificial Analysis run)	Not measured	23.5%	Only gpt-oss-120b measured
Terminal-Bench	Not measured	18.7%	Only gpt-oss-120b measured
FrontierCode	41.2%	Not measured	Only Gemini 3.8 Flash measured
FrontierSWE	19.6%	Not measured	Only Gemini 3.8 Flash measured
WeirdML	84.8%	48.2%	Gemini 3.8 Flash
ALE-Bench	1269.7	575.6	Gemini 3.8 Flash
LMArena Text: coding	1508	1379	Gemini 3.8 Flash
LMArena Text: software and IT	1507	1387	Gemini 3.8 Flash
LMArena WebDev: React	1577	Not measured	Only Gemini 3.8 Flash measured
LMArena WebDev: HTML	1616	Not measured	Only Gemini 3.8 Flash measured
LMArena WebDev: from an image	1593	Not measured	Only Gemini 3.8 Flash measured
SciCode	12.3%	7.7%	Gemini 3.8 Flash
Neither model has a result on the other 8 boards here

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

Intelligence benchmarks for Gemini 3.8 Flash and gpt-oss-120b
Benchmark	Gemini 3.8 Flash	gpt-oss-120b	Leader
AA Intelligence Index	40.9	11.6	Gemini 3.8 Flash
Epoch Capabilities Index	157.4	139.8	Gemini 3.8 Flash

Agentic workLike-for-likePublic boards, shown as published, kept out of the index30

Agentic work benchmarks for Gemini 3.8 Flash and gpt-oss-120b
Benchmark	Gemini 3.8 Flash	gpt-oss-120b	Leader
AA Agentic Index	40.2	3.7	Gemini 3.8 Flash
Design Arena: agents building web apps	1238	Not measured	Only Gemini 3.8 Flash measured
Design Arena: agents building full-stack apps	1244	Not measured	Only Gemini 3.8 Flash measured
Design Arena: agents building mobile apps	1236	Not measured	Only Gemini 3.8 Flash measured
Design Arena: agents building Android apps	1074	Not measured	Only Gemini 3.8 Flash measured
Design Arena: agents building Godot games	1273	Not measured	Only Gemini 3.8 Flash measured
Design Arena: PowerPoint slides	1177	Not measured	Only Gemini 3.8 Flash measured
Design Arena: spreadsheets	1056	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	65.8%	Only gpt-oss-120b measured
APEX-Agents	64.3%	4.4%	Gemini 3.8 Flash
METR time horizons	Not measured	56.6%	Only gpt-oss-120b measured
Remote Labor Index	5.8%	Not measured	Only Gemini 3.8 Flash measured
Vending-Bench 2	$5,094	-$22	Gemini 3.8 Flash
BrowseComp-Plus	Not measured	67.0%	Only gpt-oss-120b measured
Neither model has a result on the other 13 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index80

Reasoning benchmarks for Gemini 3.8 Flash and gpt-oss-120b
Benchmark	Gemini 3.8 Flash	gpt-oss-120b	Leader
GPQA Diamond	94.4%	78.5%	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%	Not measured	Only Gemini 3.8 Flash measured
GPQA Diamond (Artificial Analysis run)	95.3%	78.2%	Gemini 3.8 Flash
Humanity's Last Exam (Artificial Analysis run)	47.8%	19.6%	Gemini 3.8 Flash
GPQA Diamond (Epoch AI run)	95.4%	75.8%	Gemini 3.8 Flash
ARC-AGI	98.5%	Not measured	Only Gemini 3.8 Flash measured
ARC-AGI-2	89.2%	Not measured	Only Gemini 3.8 Flash measured
SimpleBench	Not measured	22.1%	Only gpt-oss-120b measured
Chess puzzles	58.0%	Not measured	Only Gemini 3.8 Flash measured
Mystery game puzzles	47.0%	2.0%	Gemini 3.8 Flash
LMArena Text: hard prompts	1509	1364	Gemini 3.8 Flash
LMArena Text: expert	1526	1356	Gemini 3.8 Flash
LMArena Text: hard prompts in English	1504	1368	Gemini 3.8 Flash
LMArena Vision: diagrams	1345	Not measured	Only Gemini 3.8 Flash measured
LMArena Vision: homework	1351	Not measured	Only Gemini 3.8 Flash measured
Kagi LLM Benchmark	Not measured	58.6%	Only gpt-oss-120b measured
Neither model has a result on the other 4 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index30

Math benchmarks for Gemini 3.8 Flash and gpt-oss-120b
Benchmark	Gemini 3.8 Flash	gpt-oss-120b	Leader
AIME	Not measured	92.6%	Only gpt-oss-120b measured
MATH 500 (Vals AI)	Not measured	94.8%	Only gpt-oss-120b measured
MGSM (Vals AI)	Not measured	92.0%	Only gpt-oss-120b measured
AA Math Index	Not measured	93.4	Only gpt-oss-120b measured
AIME 2025 (Artificial Analysis run)	Not measured	93.4%	Only gpt-oss-120b measured
OTIS Mock AIME	98.9%	88.9%	Gemini 3.8 Flash
FrontierMath, tiers 1 to 3	68.4%	Not measured	Only Gemini 3.8 Flash measured
FrontierMath, tier 4	22.0%	Not measured	Only Gemini 3.8 Flash measured
ProofBench	48.0%	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: math	1532	1389	Gemini 3.8 Flash
LMArena Text: mathematical work	1519	1386	Gemini 3.8 Flash
Neither model has a result on the other 2 boards here

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

Knowledge benchmarks for Gemini 3.8 Flash and gpt-oss-120b
Benchmark	Gemini 3.8 Flash	gpt-oss-120b	Leader
MMLU Pro	90.2%	79.2%	Gemini 3.8 Flash
LegalBench (Vals AI)	87.0%	75.9%	Gemini 3.8 Flash
CaseLaw (Vals AI)	Not measured	48.8%	Only gpt-oss-120b measured
CorpFin (Vals AI)	Not measured	58.2%	Only gpt-oss-120b measured
TaxEval (Vals AI)	74.5%	71.6%	Gemini 3.8 Flash
MortgageTax (Vals AI)	65.3%	Not measured	Only Gemini 3.8 Flash measured
MedQA (Vals AI)	Not measured	91.4%	Only gpt-oss-120b measured
MedCode (Vals AI)	48.1%	Not measured	Only Gemini 3.8 Flash measured
MMLU Pro (Artificial Analysis run)	Not measured	80.8%	Only gpt-oss-120b measured
SimpleQA Verified	69.7%	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: science	1523	1382	Gemini 3.8 Flash
LMArena Text: medicine and healthcare	1508	1388	Gemini 3.8 Flash
LMArena Text: legal and government	1497	1355	Gemini 3.8 Flash
LMArena Text: business and finance	1479	1359	Gemini 3.8 Flash
FACTS Benchmark Suite	69.4%	Not measured	Only Gemini 3.8 Flash measured
Neither model has a result on the other 3 boards here

Web designLike-for-likePublic boards, shown as published, kept out of the index60

Web design benchmarks for Gemini 3.8 Flash and gpt-oss-120b
Benchmark	Gemini 3.8 Flash	gpt-oss-120b	Leader
Design Arena: websites	1300	968	Gemini 3.8 Flash
Design Arena: UI components	1319	927	Gemini 3.8 Flash
Design Arena: game dev	1305	992	Gemini 3.8 Flash
Design Arena: data viz	1269	987	Gemini 3.8 Flash
Design Arena: 3D	1295	901	Gemini 3.8 Flash
Design Arena: all code categories	1304	963	Gemini 3.8 Flash
Design Arena: SVG	1295	Not measured	Only Gemini 3.8 Flash measured
Design Arena: ASCII art	1265	Not measured	Only Gemini 3.8 Flash measured
LiveBench design	72.7%	Not measured	Only Gemini 3.8 Flash measured

GeneralLike-for-likePublic boards, shown as published, kept out of the index210

General benchmarks for Gemini 3.8 Flash and gpt-oss-120b
Benchmark	Gemini 3.8 Flash	gpt-oss-120b	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%	Not measured	Only Gemini 3.8 Flash measured
MedScribe (Vals AI)	84.5%	Not measured	Only Gemini 3.8 Flash measured
IFBench	Not measured	69.0%	Only gpt-oss-120b measured
Long context reasoning (AA-LCR)	84.0%	52.0%	Gemini 3.8 Flash
DTBench	95.7%	76.3%	Gemini 3.8 Flash
LMCA	52.9%	22.1%	Gemini 3.8 Flash
Fiction.LiveBench	Not measured	44.4%	Only gpt-oss-120b measured
Creative writing (Lech Mazur)	Not measured	77.1%	Only gpt-oss-120b measured
Surface Evolver Bench	76.9%	25.0%	Gemini 3.8 Flash
Furniture assembly	31.7%	Not measured	Only Gemini 3.8 Flash measured
LMArena Text	1499	1366	Gemini 3.8 Flash
LMArena Text: instruction following	1492	1318	Gemini 3.8 Flash
LMArena Text: creative writing	1488	1274	Gemini 3.8 Flash
LMArena Vision	1315	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: English	1498	1375	Gemini 3.8 Flash
LMArena Text: non-English	1491	1351	Gemini 3.8 Flash
LMArena Text: Chinese	1553	1385	Gemini 3.8 Flash
LMArena Text: German	1501	1353	Gemini 3.8 Flash
LMArena Text: Japanese	1507	1331	Gemini 3.8 Flash
LMArena Text: Korean	1464	1282	Gemini 3.8 Flash
LMArena Text: French	1496	1370	Gemini 3.8 Flash
LMArena Text: Spanish	1487	1389	Gemini 3.8 Flash
LMArena Text: Russian	1514	1343	Gemini 3.8 Flash
LMArena Text: Polish	1497	1353	Gemini 3.8 Flash
LMArena Text: multi-turn	1503	1340	Gemini 3.8 Flash
LMArena Text: longer queries	1507	1319	Gemini 3.8 Flash
LMArena Text: writing and language	1494	1306	Gemini 3.8 Flash
LMArena Text: entertainment and media	1480	1292	Gemini 3.8 Flash
LMArena Vision: English	1318	Not measured	Only Gemini 3.8 Flash measured
LMArena Vision: Chinese	1416	Not measured	Only Gemini 3.8 Flash measured
LMArena Vision: reading text	1333	Not measured	Only Gemini 3.8 Flash measured
LMArena Vision: humor	1321	Not measured	Only Gemini 3.8 Flash measured
LMArena Vision: creative writing	1299	Not measured	Only Gemini 3.8 Flash measured
Neither model has a result on the other 10 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-oss-120b
Benchmark	Gemini 3.8 Flash	gpt-oss-120b	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-oss-120b$0.0003Fits in one request

gpt-oss-120b costs less

Repository review

50K input + 3K output tokens

Gemini 3.8 Flash$0.049Fits in one request

gpt-oss-120b$0.0065Fits in one request

gpt-oss-120b costs less

Agent loop

200K input + 10K output tokens

Gemini 3.8 Flash$0.188Fits in one request

gpt-oss-120b$0.025Exceeds the context window

gpt-oss-120b 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-oss-120b
Specification	Google Gemini 3.8 Flash	OpenAI gpt-oss-120b
Maker	Google	OpenAI
Weights	No public weights listed	Open weights
Released	September 2, 2026	August 5, 2025
Context window	1.05M	131K
Input $/Mtok	$0.75	$0.10
Output $/Mtok	$3.75	$0.50
Coding index	61.6	Not benchmarked
Independent measurements behind it	6	1
Cost per solved task	$2.74	$0.51
Source	OpenRouter listing	OpenRouter listing

Questions

Is Gemini 3.8 Flash better than gpt-oss-120b for coding?

Only Gemini 3.8 Flash has a coding score, 61.6 on the Vibe Coding Index; gpt-oss-120b has none, so the two cannot be ranked on coding. Pick gpt-oss-120b for output tokens 7.5x cheaper ($0.50 vs $3.75 per million) and a lower cost per solved task ($0.51 against $2.74).

Which is cheaper, Gemini 3.8 Flash or gpt-oss-120b?

Gemini 3.8 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; gpt-oss-120b costs $0.10 and $0.50. Per solved SWE-bench Verified task, Gemini 3.8 Flash costs $2.74 and gpt-oss-120b $0.51.

Which has the bigger context window, Gemini 3.8 Flash or gpt-oss-120b?

Gemini 3.8 Flash, with 1.05M tokens against 131K.

How many benchmarks is the Gemini 3.8 Flash vs gpt-oss-120b comparison based on?

59 benchmarks have a result for both models as of October 21, 2026. Gemini 3.8 Flash's coding index rests on 6 independent benchmarks and gpt-oss-120b's on 1. Where only one model has a result, the page says so instead of naming a winner.

Gemini 3.8 Flash or gpt-oss-120b: 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

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