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GLM 4.6V vs gpt-oss-20b

GLM 4.6V leads gpt-oss-20b on the Artificial Analysis Intelligence Index, 11.2 to 10.0, and gpt-oss-20b costs 6.0x less per output token ($0.15 vs $0.90 per million). Updated October 22, 2026; 31 benchmarks have a result for both.

Replace GLM 4.6V Replace gpt-oss-20b
GLM 4.6VZ.ai
Coding
No data
Overall
No data
Output $/M
$0.90
25
gpt-oss-20bOpenAI
Coding
No data
Overall
38.5
Output $/M
$0.15
6
vs boards won of 31 shared

GLM 4.6V or gpt-oss-20b: which to pick

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

Pick GLM 4.6V for work measured by LiveCodeBench (Artificial Analysis run) or τ²-Bench Telecom, where it leads.

Model AGLM 4.6VZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel Bgpt-oss-20bOpenAINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
31
GLM 4.6V only
7
gpt-oss-20b only
31
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 4.6V not benchmarked, gpt-oss-20b not benchmarked.
Widest category
Agentic work, 28.7 points apart on average over 1 shared benchmark.
Widest single gap
LiveCodeBench (Artificial Analysis run): GLM 4.6V 41.1% against gpt-oss-20b 77.7%, 36.6 points apart on a 0 to 100 scale.
Output price
GLM 4.6V $0.90 against gpt-oss-20b $0.15 per million output tokens, 6.0x apart.
Context window
Both take 131K tokens.

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 4.6VBarsgpt-oss-20bTies
Coding31
Intelligence10
Agentic work01
Reasoning41
Math02
Knowledge50
General121
All shared boards256
CodingLike-for-likeSix of these boards feed the Vibe Coding Index31
Coding benchmarks for GLM 4.6V and gpt-oss-20b
BenchmarkGLM 4.6Vgpt-oss-20bLeader
LiveCodeBench (Vals AI)Not measured80.4%Only gpt-oss-20b measured
LiveCodeBench (Artificial Analysis run)41.1%77.7%gpt-oss-20b
SciCodeNot measured38.9%Only gpt-oss-20b measured
Terminal-Bench Hard (Artificial Analysis run)14.4%10.6%GLM 4.6V
Terminal-BenchNot measured3.4%Only gpt-oss-20b measured
WeirdMLNot measured40.9%Only gpt-oss-20b measured
ALE-BenchNot measured566.0Only gpt-oss-20b measured
LMArena Text: coding13891307GLM 4.6V
LMArena Text: software and IT13911311GLM 4.6V
Neither model has a result on the other 30 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 4.6V and gpt-oss-20b
BenchmarkGLM 4.6Vgpt-oss-20bLeader
AA Intelligence Index11.210.0GLM 4.6V
Epoch Capabilities IndexNot measured137.7Only gpt-oss-20b measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GLM 4.6V and gpt-oss-20b
BenchmarkGLM 4.6Vgpt-oss-20bLeader
τ²-Bench Telecom31.6%60.2%gpt-oss-20b
BrowseComp-PlusNot measured50.6%Only gpt-oss-20b measured
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index41
Reasoning benchmarks for GLM 4.6V and gpt-oss-20b
BenchmarkGLM 4.6Vgpt-oss-20bLeader
GPQA DiamondNot measured68.9%Only gpt-oss-20b measured
GPQA Diamond (Artificial Analysis run)71.9%68.8%GLM 4.6V
Humanity's Last Exam (Artificial Analysis run)9.6%11.0%gpt-oss-20b
GPQA Diamond (Epoch AI run)Not measured60.8%Only gpt-oss-20b measured
LMArena Text: hard prompts13671274GLM 4.6V
LMArena Text: expert13711258GLM 4.6V
LMArena Text: hard prompts in English13911292GLM 4.6V
LMArena Vision: diagrams1182Not measuredOnly GLM 4.6V measured
LMArena Vision: homework1155Not measuredOnly GLM 4.6V measured
Kagi LLM BenchmarkNot measured53.2%Only gpt-oss-20b measured
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for GLM 4.6V and gpt-oss-20b
BenchmarkGLM 4.6Vgpt-oss-20bLeader
AIMENot measured86.0%Only gpt-oss-20b measured
MATH 500 (Vals AI)Not measured94.2%Only gpt-oss-20b measured
MGSM (Vals AI)Not measured89.0%Only gpt-oss-20b measured
AA Math Index85.389.3gpt-oss-20b
AIME 2025 (Artificial Analysis run)85.3%89.3%gpt-oss-20b
OTIS Mock AIMENot measured65.3%Only gpt-oss-20b measured
LMArena Text: mathNot measured1317Only gpt-oss-20b measured
LMArena Text: mathematical workNot measured1305Only gpt-oss-20b measured
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
Knowledge benchmarks for GLM 4.6V and gpt-oss-20b
BenchmarkGLM 4.6Vgpt-oss-20bLeader
MMLU ProNot measured71.6%Only gpt-oss-20b measured
LegalBench (Vals AI)Not measured70.8%Only gpt-oss-20b measured
CaseLaw (Vals AI)Not measured43.8%Only gpt-oss-20b measured
CorpFin (Vals AI)Not measured53.1%Only gpt-oss-20b measured
TaxEval (Vals AI)Not measured63.7%Only gpt-oss-20b measured
MedQA (Vals AI)Not measured82.9%Only gpt-oss-20b measured
MMLU Pro (Artificial Analysis run)79.9%74.8%GLM 4.6V
LMArena Text: science13891296GLM 4.6V
LMArena Text: medicine and healthcare13891310GLM 4.6V
LMArena Text: legal and government13931280GLM 4.6V
LMArena Text: business and finance13591284GLM 4.6V
Neither model has a result on the other 7 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Web design benchmarks for GLM 4.6V and gpt-oss-20b
BenchmarkGLM 4.6Vgpt-oss-20bLeader
Design Arena: websitesNot measured852Only gpt-oss-20b measured
Design Arena: data vizNot measured933Only gpt-oss-20b measured
Neither model has a result on the other 7 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index121
General benchmarks for GLM 4.6V and gpt-oss-20b
BenchmarkGLM 4.6Vgpt-oss-20bLeader
IFBench30.1%65.1%gpt-oss-20b
Long context reasoning (AA-LCR)48.7%34.7%GLM 4.6V
DTBenchNot measured68.0%Only gpt-oss-20b measured
LMCANot measured14.5%Only gpt-oss-20b measured
LMArena Text13761288GLM 4.6V
LMArena Text: instruction following13501236GLM 4.6V
LMArena Text: creative writing13471201GLM 4.6V
LMArena Vision1164Not measuredOnly GLM 4.6V measured
LMArena Text: English13951303GLM 4.6V
LMArena Text: non-English13581269GLM 4.6V
LMArena Text: Chinese14251315GLM 4.6V
LMArena Text: GermanNot measured1255Only gpt-oss-20b measured
LMArena Text: JapaneseNot measured1244Only gpt-oss-20b measured
LMArena Text: KoreanNot measured1236Only gpt-oss-20b measured
LMArena Text: SpanishNot measured1267Only gpt-oss-20b measured
LMArena Text: Russian13391278GLM 4.6V
LMArena Text: PolishNot measured1252Only gpt-oss-20b measured
LMArena Text: multi-turn13591268GLM 4.6V
LMArena Text: longer queries13571250GLM 4.6V
LMArena Text: writing and language13471238GLM 4.6V
LMArena Text: entertainment and media13431216GLM 4.6V
LMArena Vision: English1179Not measuredOnly GLM 4.6V measured
LMArena Vision: Chinese1217Not measuredOnly GLM 4.6V measured
LMArena Vision: reading text1171Not measuredOnly GLM 4.6V measured
LMArena Vision: creative writing1113Not measuredOnly GLM 4.6V measured
Neither model has a result on the other 21 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 4.6V and gpt-oss-20b
BenchmarkGLM 4.6Vgpt-oss-20bLeader
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 4.6V$0.0008Fits in one request
gpt-oss-20b$0.0001Fits in one request

gpt-oss-20b costs less

Repository review

50K input + 3K output tokens

GLM 4.6V$0.018Fits in one request
gpt-oss-20b$0.0019Fits in one request

gpt-oss-20b costs less

Agent loop

200K input + 10K output tokens

GLM 4.6V$0.069Exceeds the context window
gpt-oss-20b$0.0075Exceeds the context window

gpt-oss-20b 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 4.6V and gpt-oss-20b
SpecificationZ.ai GLM 4.6VOpenAI gpt-oss-20b
MakerZ.aiOpenAI
WeightsOpen weightsOpen weights
ReleasedDecember 8, 2025August 5, 2025
Context window131K131K
Input $/Mtok$0.30$0.03
Output $/Mtok$0.90$0.15
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.6V better than gpt-oss-20b for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 4.6V for work measured by LiveCodeBench (Artificial Analysis run) or τ²-Bench Telecom, where it leads.

Which is cheaper, GLM 4.6V or gpt-oss-20b?

GLM 4.6V costs $0.30 per million input tokens and $0.90 per million output tokens; gpt-oss-20b costs $0.03 and $0.15. Cost per solved task is known for neither of them.

Which has the bigger context window, GLM 4.6V or gpt-oss-20b?

Neither: both take 131K tokens.

How many benchmarks is the GLM 4.6V vs gpt-oss-20b comparison based on?

31 benchmarks have a result for both models as of October 22, 2026. GLM 4.6V's coding index rests on 0 independent benchmarks and gpt-oss-20b's on 0. Where only one model has a result, the page says so instead of naming a winner.

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