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Gemini 2.5 Pro Preview 06-05 vs gpt-oss-120b

gpt-oss-120b costs 20.0x less per output token than Gemini 2.5 Pro Preview 06-05 ($0.50 vs $10.00 per million). Updated October 21, 2026; 11 benchmarks have a result for both.

Gemini 2.5 Pro Preview 06-05Google
Coding
No data
Overall
No data
Output $/M
$10.00
7
gpt-oss-120bOpenAI
Coding
No data
Overall
50.0
Output $/M
$0.50
3
vs boards won of 11 shared, 1 tied

Gemini 2.5 Pro Preview 06-05 or gpt-oss-120b: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick Gemini 2.5 Pro Preview 06-05 for a larger context window (1.05M against 131K tokens) and work measured by LiveCodeBench (Vals AI) or LiveCodeBench (Artificial Analysis run), where it leads.

Shared results
11
Gemini 2.5 Pro Preview 06-05 only
4
gpt-oss-120b only
70
Like-for-like categories
5 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 2.5 Pro Preview 06-05 not benchmarked, gpt-oss-120b not benchmarked.
Widest category
General, 47.3 points apart on average over 1 shared benchmark.
Widest single gap
Fiction.LiveBench: Gemini 2.5 Pro Preview 06-05 91.7% against gpt-oss-120b 44.4%, 47.3 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Pro Preview 06-05 $10.00 against gpt-oss-120b $0.50 per million output tokens, 20.0x apart.
Context window
Gemini 2.5 Pro Preview 06-05 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
CategoryGemini 2.5 Pro Preview 06-05Barsgpt-oss-120bTies
Coding121 tie
Agentic work01
Reasoning40
Knowledge10
General10
All shared boards731 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index12
Coding benchmarks for Gemini 2.5 Pro Preview 06-05 and gpt-oss-120b
BenchmarkGemini 2.5 Pro Preview 06-05gpt-oss-120bLeader
Aider polyglot83.1%41.8%Gemini 2.5 Pro Preview 06-05
SWE-bench VerifiedNot measured26.0%Only gpt-oss-120b measured
AA Coding IndexNot measured30.4Only gpt-oss-120b measured
LiveCodeBench (Vals AI)79.2%83.2%gpt-oss-120b
SWE-bench Verified (Vals AI)Not measured33.6%Only gpt-oss-120b measured
LiveCodeBench (Artificial Analysis run)77.8%87.8%gpt-oss-120b
SciCodeNot measured34.0%Only gpt-oss-120b measured
Terminal-Bench Hard (Artificial Analysis run)Not measured23.5%Only gpt-oss-120b measured
Terminal-BenchNot measured18.7%Only gpt-oss-120b measured
GSO-Bench3.9%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
WeirdMLNot measured48.2%Only gpt-oss-120b measured
ALE-BenchNot measured575.6Only gpt-oss-120b measured
LMArena Text: codingNot measured1379Only gpt-oss-120b measured
LMArena Text: software and ITNot measured1387Only gpt-oss-120b measured
SciCode7.7%7.7%Tie
Neither model has a result on the other 24 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Gemini 2.5 Pro Preview 06-05 and gpt-oss-120b
BenchmarkGemini 2.5 Pro Preview 06-05gpt-oss-120bLeader
AA Intelligence IndexNot measured11.6Only gpt-oss-120b measured
Epoch Capabilities IndexNot measured139.8Only gpt-oss-120b measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Gemini 2.5 Pro Preview 06-05 and gpt-oss-120b
BenchmarkGemini 2.5 Pro Preview 06-05gpt-oss-120bLeader
AA Agentic IndexNot measured3.7Only gpt-oss-120b measured
τ²-Bench TelecomNot measured65.8%Only gpt-oss-120b measured
APEX-AgentsNot measured4.4%Only gpt-oss-120b measured
METR time horizons55.4%56.6%gpt-oss-120b
Remote Labor Index0.8%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
DeepResearch Bench42.8%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
Vending-Bench 2Not measured-$22Only gpt-oss-120b measured
BrowseComp-PlusNot measured67.0%Only gpt-oss-120b measured
Neither model has a result on the other 33 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
Reasoning benchmarks for Gemini 2.5 Pro Preview 06-05 and gpt-oss-120b
BenchmarkGemini 2.5 Pro Preview 06-05gpt-oss-120bLeader
GPQA DiamondNot measured78.5%Only gpt-oss-120b measured
GPQA Diamond (Artificial Analysis run)83.6%78.2%Gemini 2.5 Pro Preview 06-05
Humanity's Last Exam (Artificial Analysis run)19.9%19.6%Gemini 2.5 Pro Preview 06-05
GPQA Diamond (Epoch AI run)84.8%75.8%Gemini 2.5 Pro Preview 06-05
SimpleBench62.4%22.1%Gemini 2.5 Pro Preview 06-05
Mystery game puzzlesNot measured2.0%Only gpt-oss-120b measured
VPCT46.4%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
LMArena Text: hard promptsNot measured1364Only gpt-oss-120b measured
LMArena Text: expertNot measured1356Only gpt-oss-120b measured
LMArena Text: hard prompts in EnglishNot measured1368Only gpt-oss-120b measured
Kagi LLM BenchmarkNot measured58.6%Only gpt-oss-120b measured
Neither model has a result on the other 11 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Math benchmarks for Gemini 2.5 Pro Preview 06-05 and gpt-oss-120b
BenchmarkGemini 2.5 Pro Preview 06-05gpt-oss-120bLeader
AIMENot measured92.6%Only gpt-oss-120b measured
MATH 500 (Vals AI)Not measured94.8%Only gpt-oss-120b measured
MGSM (Vals AI)Not measured92.0%Only gpt-oss-120b measured
AA Math IndexNot measured93.4Only gpt-oss-120b measured
AIME 2025 (Artificial Analysis run)Not measured93.4%Only gpt-oss-120b measured
OTIS Mock AIMENot measured88.9%Only gpt-oss-120b measured
LMArena Text: mathNot measured1389Only gpt-oss-120b measured
LMArena Text: mathematical workNot measured1386Only gpt-oss-120b measured
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for Gemini 2.5 Pro Preview 06-05 and gpt-oss-120b
BenchmarkGemini 2.5 Pro Preview 06-05gpt-oss-120bLeader
MMLU ProNot measured79.2%Only gpt-oss-120b measured
LegalBench (Vals AI)Not measured75.9%Only gpt-oss-120b measured
CaseLaw (Vals AI)Not measured48.8%Only gpt-oss-120b measured
CorpFin (Vals AI)Not measured58.2%Only gpt-oss-120b measured
TaxEval (Vals AI)Not measured71.6%Only gpt-oss-120b measured
MedQA (Vals AI)Not measured91.4%Only gpt-oss-120b measured
MMLU Pro (Artificial Analysis run)85.8%80.8%Gemini 2.5 Pro Preview 06-05
LMArena Text: scienceNot measured1382Only gpt-oss-120b measured
LMArena Text: medicine and healthcareNot measured1388Only gpt-oss-120b measured
LMArena Text: legal and governmentNot measured1355Only gpt-oss-120b measured
LMArena Text: business and financeNot measured1359Only gpt-oss-120b measured
Neither model has a result on the other 7 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for Gemini 2.5 Pro Preview 06-05 and gpt-oss-120b
BenchmarkGemini 2.5 Pro Preview 06-05gpt-oss-120bLeader
Design Arena: websitesNot measured968Only gpt-oss-120b measured
Design Arena: UI componentsNot measured927Only gpt-oss-120b measured
Design Arena: game devNot measured992Only gpt-oss-120b measured
Design Arena: data vizNot measured987Only gpt-oss-120b measured
Design Arena: 3DNot measured901Only gpt-oss-120b measured
Design Arena: all code categoriesNot measured963Only gpt-oss-120b measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
General benchmarks for Gemini 2.5 Pro Preview 06-05 and gpt-oss-120b
BenchmarkGemini 2.5 Pro Preview 06-05gpt-oss-120bLeader
IFBenchNot measured69.0%Only gpt-oss-120b measured
Long context reasoning (AA-LCR)Not measured52.0%Only gpt-oss-120b measured
DTBenchNot measured76.3%Only gpt-oss-120b measured
LMCANot measured22.1%Only gpt-oss-120b measured
Fiction.LiveBench91.7%44.4%Gemini 2.5 Pro Preview 06-05
Creative writing (Lech Mazur)Not measured77.1%Only gpt-oss-120b measured
Surface Evolver BenchNot measured25.0%Only gpt-oss-120b measured
LMArena TextNot measured1366Only gpt-oss-120b measured
LMArena Text: instruction followingNot measured1318Only gpt-oss-120b measured
LMArena Text: creative writingNot measured1274Only gpt-oss-120b measured
LMArena Text: EnglishNot measured1375Only gpt-oss-120b measured
LMArena Text: non-EnglishNot measured1351Only gpt-oss-120b measured
LMArena Text: ChineseNot measured1385Only gpt-oss-120b measured
LMArena Text: GermanNot measured1353Only gpt-oss-120b measured
LMArena Text: JapaneseNot measured1331Only gpt-oss-120b measured
LMArena Text: KoreanNot measured1282Only gpt-oss-120b measured
LMArena Text: FrenchNot measured1370Only gpt-oss-120b measured
LMArena Text: SpanishNot measured1389Only gpt-oss-120b measured
LMArena Text: RussianNot measured1343Only gpt-oss-120b measured
LMArena Text: PolishNot measured1353Only gpt-oss-120b measured
LMArena Text: multi-turnNot measured1340Only gpt-oss-120b measured
LMArena Text: longer queriesNot measured1319Only gpt-oss-120b measured
LMArena Text: writing and languageNot measured1306Only gpt-oss-120b measured
LMArena Text: entertainment and mediaNot measured1292Only gpt-oss-120b measured
Neither model has a result on the other 22 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 2.5 Pro Preview 06-05 and gpt-oss-120b
BenchmarkGemini 2.5 Pro Preview 06-05gpt-oss-120bLeader
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 2.5 Pro Preview 06-05$0.0063Fits in one request
gpt-oss-120b$0.0003Fits in one request

gpt-oss-120b costs less

Repository review

50K input + 3K output tokens

Gemini 2.5 Pro Preview 06-05$0.092Fits in one request
gpt-oss-120b$0.0065Fits in one request

gpt-oss-120b costs less

Agent loop

200K input + 10K output tokens

Gemini 2.5 Pro Preview 06-05$0.350Fits 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 2.5 Pro Preview 06-05 and gpt-oss-120b
SpecificationGoogle Gemini 2.5 Pro Preview 06-05OpenAI gpt-oss-120b
MakerGoogleOpenAI
WeightsNo public weights listedOpen weights
ReleasedJune 5, 2025August 5, 2025
Context window1.05M131K
Input $/Mtok$1.25$0.10
Output $/Mtok$10.00$0.50
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computable$0.51
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 2.5 Pro Preview 06-05 better than gpt-oss-120b for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemini 2.5 Pro Preview 06-05 for a larger context window (1.05M against 131K tokens) and work measured by LiveCodeBench (Vals AI) or LiveCodeBench (Artificial Analysis run), where it leads.

Which is cheaper, Gemini 2.5 Pro Preview 06-05 or gpt-oss-120b?

Gemini 2.5 Pro Preview 06-05 costs $1.25 per million input tokens and $10.00 per million output tokens; gpt-oss-120b costs $0.10 and $0.50. Cost per solved task is known for gpt-oss-120b only.

Which has the bigger context window, Gemini 2.5 Pro Preview 06-05 or gpt-oss-120b?

Gemini 2.5 Pro Preview 06-05, with 1.05M tokens against 131K.

How many benchmarks is the Gemini 2.5 Pro Preview 06-05 vs gpt-oss-120b comparison based on?

11 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Pro Preview 06-05's coding index rests on 0 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.

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