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GLM 4.5V vs gpt-oss-120b

gpt-oss-120b leads GLM 4.5V on the Artificial Analysis Intelligence Index, 11.6 to 7.6, and gpt-oss-120b costs 3.6x less per output token ($0.50 vs $1.80 per million). Updated October 22, 2026; 36 benchmarks have a result for both.

Replace GLM 4.5V Replace gpt-oss-120b
GLM 4.5VZ.ai
Coding
No data
Overall
No data
Output $/M
$1.80
3
gpt-oss-120bOpenAI
Coding
No data
Overall
50.0
Output $/M
$0.50
33
vs boards won of 36 shared

GLM 4.5V or gpt-oss-120b: which to pick

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

Pick GLM 4.5V for work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Model AGLM 4.5VZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel Bgpt-oss-120bOpenAINot benchmarked1 independent benchmark$0.51 per solved task
Shared results
36
GLM 4.5V only
5
gpt-oss-120b only
45
Like-for-like categories
7 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
GLM 4.5V not benchmarked, gpt-oss-120b not benchmarked.
Widest category
Agentic work, 43.3 points apart on average over 1 shared benchmark.
Widest single gap
Long context reasoning (AA-LCR): GLM 4.5V 0.0% against gpt-oss-120b 52.0%, 52.0 points apart on a 0 to 100 scale.
Output price
GLM 4.5V $1.80 against gpt-oss-120b $0.50 per million output tokens, 3.6x apart.
Context window
GLM 4.5V takes 66K 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
CategoryGLM 4.5VBarsgpt-oss-120bTies
Coding04
Intelligence01
Agentic work01
Reasoning15
Math04
Knowledge05
General213
All shared boards333
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for GLM 4.5V and gpt-oss-120b
BenchmarkGLM 4.5Vgpt-oss-120bLeader
Aider polyglotNot measured41.8%Only gpt-oss-120b measured
SWE-bench VerifiedNot measured26.0%Only gpt-oss-120b measured
AA Coding IndexNot measured30.4Only gpt-oss-120b measured
LiveCodeBench (Vals AI)Not measured83.2%Only gpt-oss-120b measured
SWE-bench Verified (Vals AI)Not measured33.6%Only gpt-oss-120b measured
LiveCodeBench (Artificial Analysis run)60.4%87.8%gpt-oss-120b
SciCodeNot measured34.0%Only gpt-oss-120b measured
Terminal-Bench Hard (Artificial Analysis run)6.8%23.5%gpt-oss-120b
Terminal-BenchNot measured18.7%Only gpt-oss-120b measured
WeirdMLNot measured48.2%Only gpt-oss-120b measured
ALE-BenchNot measured575.6Only gpt-oss-120b measured
LMArena Text: coding13471379gpt-oss-120b
LMArena Text: software and IT13531387gpt-oss-120b
SciCodeNot measured7.7%Only gpt-oss-120b measured
Neither model has a result on the other 25 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.5V and gpt-oss-120b
BenchmarkGLM 4.5Vgpt-oss-120bLeader
AA Intelligence Index7.611.6gpt-oss-120b
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 GLM 4.5V and gpt-oss-120b
BenchmarkGLM 4.5Vgpt-oss-120bLeader
AA Agentic IndexNot measured3.7Only gpt-oss-120b measured
τ²-Bench Telecom22.5%65.8%gpt-oss-120b
APEX-AgentsNot measured4.4%Only gpt-oss-120b measured
METR time horizonsNot measured56.6%Only gpt-oss-120b 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 35 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index15
Reasoning benchmarks for GLM 4.5V and gpt-oss-120b
BenchmarkGLM 4.5Vgpt-oss-120bLeader
GPQA DiamondNot measured78.5%Only gpt-oss-120b measured
GPQA Diamond (Artificial Analysis run)68.4%78.2%gpt-oss-120b
Humanity's Last Exam (Artificial Analysis run)6.3%19.6%gpt-oss-120b
GPQA Diamond (Epoch AI run)Not measured75.8%Only gpt-oss-120b measured
SimpleBenchNot measured22.1%Only gpt-oss-120b measured
Mystery game puzzlesNot measured2.0%Only gpt-oss-120b measured
LMArena Text: hard prompts13351364gpt-oss-120b
LMArena Text: expert13531356gpt-oss-120b
LMArena Text: hard prompts in English13571368gpt-oss-120b
LMArena Vision: diagrams1151Not measuredOnly GLM 4.5V measured
LMArena Vision: homework1163Not measuredOnly GLM 4.5V measured
Kagi LLM Benchmark59.8%58.6%GLM 4.5V
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for GLM 4.5V and gpt-oss-120b
BenchmarkGLM 4.5Vgpt-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 Index73.093.4gpt-oss-120b
AIME 2025 (Artificial Analysis run)73.0%93.4%gpt-oss-120b
OTIS Mock AIMENot measured88.9%Only gpt-oss-120b measured
LMArena Text: math13541389gpt-oss-120b
LMArena Text: mathematical work13361386gpt-oss-120b
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for GLM 4.5V and gpt-oss-120b
BenchmarkGLM 4.5Vgpt-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)78.8%80.8%gpt-oss-120b
LMArena Text: science13301382gpt-oss-120b
LMArena Text: medicine and healthcare13491388gpt-oss-120b
LMArena Text: legal and government13381355gpt-oss-120b
LMArena Text: business and finance13091359gpt-oss-120b
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 GLM 4.5V and gpt-oss-120b
BenchmarkGLM 4.5Vgpt-oss-120bLeader
Design Arena: websitesNot measured967Only gpt-oss-120b measured
Design Arena: UI componentsNot measured924Only 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 measured962Only 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 index213
General benchmarks for GLM 4.5V and gpt-oss-120b
BenchmarkGLM 4.5Vgpt-oss-120bLeader
IFBench34.2%69.0%gpt-oss-120b
Long context reasoning (AA-LCR)0.0%52.0%gpt-oss-120b
DTBenchNot measured76.3%Only gpt-oss-120b measured
LMCANot measured22.1%Only gpt-oss-120b measured
Fiction.LiveBenchNot measured44.4%Only gpt-oss-120b measured
Creative writing (Lech Mazur)Not measured77.1%Only gpt-oss-120b measured
Surface Evolver BenchNot measured25.0%Only gpt-oss-120b measured
LMArena Text13331366gpt-oss-120b
LMArena Text: instruction following13111318gpt-oss-120b
LMArena Text: creative writing12941274GLM 4.5V
LMArena Vision1154Not measuredOnly GLM 4.5V measured
LMArena Text: English13621375gpt-oss-120b
LMArena Text: non-English13031351gpt-oss-120b
LMArena Text: Chinese13371385gpt-oss-120b
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: Spanish13361389gpt-oss-120b
LMArena Text: Russian12981343gpt-oss-120b
LMArena Text: Polish13021353gpt-oss-120b
LMArena Text: multi-turn13331340gpt-oss-120b
LMArena Text: longer queries13051319gpt-oss-120b
LMArena Text: writing and language13021306gpt-oss-120b
LMArena Text: entertainment and media13031292GLM 4.5V
LMArena Vision: English1183Not measuredOnly GLM 4.5V measured
LMArena Vision: reading text1151Not measuredOnly GLM 4.5V measured
Neither model has a result on the other 19 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 4.5V and gpt-oss-120b
BenchmarkGLM 4.5Vgpt-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

GLM 4.5V$0.0015Fits in one request
gpt-oss-120b$0.0003Fits in one request

gpt-oss-120b costs less

Repository review

50K input + 3K output tokens

GLM 4.5V$0.035Fits in one request
gpt-oss-120b$0.0065Fits in one request

gpt-oss-120b costs less

Agent loop

200K input + 10K output tokens

GLM 4.5V$0.138Exceeds the context window
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 GLM 4.5V and gpt-oss-120b
SpecificationZ.ai GLM 4.5VOpenAI gpt-oss-120b
MakerZ.aiOpenAI
WeightsOpen weightsOpen weights
ReleasedAugust 11, 2025August 5, 2025
Context window66K131K
Input $/Mtok$0.60$0.10
Output $/Mtok$1.80$0.50
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computable$0.51
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.5V better than gpt-oss-120b for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 4.5V for work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Which is cheaper, GLM 4.5V or gpt-oss-120b?

GLM 4.5V costs $0.60 per million input tokens and $1.80 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, GLM 4.5V or gpt-oss-120b?

gpt-oss-120b, with 131K tokens against 66K.

How many benchmarks is the GLM 4.5V vs gpt-oss-120b comparison based on?

36 benchmarks have a result for both models as of October 22, 2026. GLM 4.5V'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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