Enter opens the highlighted result. Esc closes.

GLM 4.7 Flash vs gpt-oss-20b

Updated October 21, 2026. 37 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GLM 4.7 Flash Replace gpt-oss-20b
GLM 4.7 FlashZ.ai
Coding
No data
Overall
14.9
Output $/M
$0.40
32
gpt-oss-20bOpenAI
Coding
No data
Overall
10.0
Output $/M
$0.15
5
vs boards won of 37 shared

Decision reading

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

GLM 4.7 Flash has the edge where the context window is larger, 200K against 131K tokens, and where what matters is GPQA Diamond (Artificial Analysis run) or Humanity's Last Exam (Artificial Analysis run), where it leads.

Model AGLM 4.7 FlashZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel Bgpt-oss-20bOpenAINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
37
GLM 4.7 Flash only
6
gpt-oss-20b only
23
Like-for-like categories
8 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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 4.7 Flash not benchmarked, gpt-oss-20b not benchmarked.
Widest category
Agentic work, 38.6 points apart on average over 1 shared benchmark.
Widest single gap
Design Arena: websites: GLM 4.7 Flash 1194 against gpt-oss-20b 853, 42.6 points apart on a 0 to 100 scale.
Output price
GLM 4.7 Flash $0.40 against gpt-oss-20b $0.15 per million output tokens, 2.7x apart.
Context window
GLM 4.7 Flash takes 200K tokens, gpt-oss-20b 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 4.7 FlashBarsgpt-oss-20bTies
Coding30
Intelligence10
Agentic work10
Reasoning33
Math21
Knowledge40
Web design20
General161
All shared boards325
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
Coding benchmarks for GLM 4.7 Flash and gpt-oss-20b
BenchmarkGLM 4.7 Flashgpt-oss-20bLeader
LiveCodeBench (Vals AI)Not measured80.4%Only gpt-oss-20b measured
LiveCodeBench (Artificial Analysis run)Not measured77.7%Only gpt-oss-20b measured
SciCodeNot measured38.9%Only gpt-oss-20b measured
Terminal-Bench Hard (Artificial Analysis run)22.0%10.6%GLM 4.7 Flash
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: coding13821307GLM 4.7 Flash
LMArena Text: software and IT13891311GLM 4.7 Flash
Neither model has a result on the other 29 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 4.7 Flash and gpt-oss-20b
BenchmarkGLM 4.7 Flashgpt-oss-20bLeader
AA Intelligence Index14.910.0GLM 4.7 Flash
Epoch Capabilities IndexNot measured137.7Only gpt-oss-20b measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 4.7 Flash and gpt-oss-20b
BenchmarkGLM 4.7 Flashgpt-oss-20bLeader
τ²-Bench Telecom98.8%60.2%GLM 4.7 Flash
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index33
Reasoning benchmarks for GLM 4.7 Flash and gpt-oss-20b
BenchmarkGLM 4.7 Flashgpt-oss-20bLeader
GPQA DiamondNot measured68.9%Only gpt-oss-20b measured
GPQA Diamond (Artificial Analysis run)58.1%68.8%gpt-oss-20b
Humanity's Last Exam (Artificial Analysis run)7.6%11.0%gpt-oss-20b
GPQA Diamond (Epoch AI run)60.5%60.8%gpt-oss-20b
LMArena Text: hard prompts13561274GLM 4.7 Flash
LMArena Text: expert13571258GLM 4.7 Flash
LMArena Text: hard prompts in English13691292GLM 4.7 Flash
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index21
Math benchmarks for GLM 4.7 Flash and gpt-oss-20b
BenchmarkGLM 4.7 Flashgpt-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 IndexNot measured89.3Only gpt-oss-20b measured
AIME 2025 (Artificial Analysis run)Not measured89.3%Only gpt-oss-20b measured
OTIS Mock AIME58.3%65.3%gpt-oss-20b
LMArena Text: math13551317GLM 4.7 Flash
LMArena Text: mathematical work13691305GLM 4.7 Flash
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for GLM 4.7 Flash and gpt-oss-20b
BenchmarkGLM 4.7 Flashgpt-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)Not measured74.8%Only gpt-oss-20b measured
LMArena Text: science13581296GLM 4.7 Flash
LMArena Text: medicine and healthcare13431310GLM 4.7 Flash
LMArena Text: legal and government13571280GLM 4.7 Flash
LMArena Text: business and finance13431284GLM 4.7 Flash
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index20
Web design benchmarks for GLM 4.7 Flash and gpt-oss-20b
BenchmarkGLM 4.7 Flashgpt-oss-20bLeader
Design Arena: websites1194853GLM 4.7 Flash
Design Arena: UI components1208Not measuredOnly GLM 4.7 Flash measured
Design Arena: game dev1135Not measuredOnly GLM 4.7 Flash measured
Design Arena: data viz1123933GLM 4.7 Flash
Design Arena: 3D1121Not measuredOnly GLM 4.7 Flash measured
Design Arena: all code categories1178Not measuredOnly GLM 4.7 Flash measured
Design Arena: SVG1038Not measuredOnly GLM 4.7 Flash measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index161
General benchmarks for GLM 4.7 Flash and gpt-oss-20b
BenchmarkGLM 4.7 Flashgpt-oss-20bLeader
IFBench60.8%65.1%gpt-oss-20b
Long context reasoning (AA-LCR)41.7%34.7%GLM 4.7 Flash
DTBenchNot measured68.0%Only gpt-oss-20b measured
LMCANot measured14.5%Only gpt-oss-20b measured
LMArena Text13511288GLM 4.7 Flash
LMArena Text: instruction following13271236GLM 4.7 Flash
LMArena Text: creative writing12961201GLM 4.7 Flash
LMArena Text: English13731303GLM 4.7 Flash
LMArena Text: non-English13301269GLM 4.7 Flash
LMArena Text: Chinese14031315GLM 4.7 Flash
LMArena Text: German13361255GLM 4.7 Flash
LMArena Text: JapaneseNot measured1244Only gpt-oss-20b measured
LMArena Text: Korean12831236GLM 4.7 Flash
LMArena Text: French1332Not measuredOnly GLM 4.7 Flash measured
LMArena Text: Spanish13501267GLM 4.7 Flash
LMArena Text: Russian13331278GLM 4.7 Flash
LMArena Text: Polish12911252GLM 4.7 Flash
LMArena Text: multi-turn13421268GLM 4.7 Flash
LMArena Text: longer queries13451250GLM 4.7 Flash
LMArena Text: writing and language13201238GLM 4.7 Flash
LMArena Text: entertainment and media13041216GLM 4.7 Flash
Neither model has a result on the other 25 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 4.7 Flash and gpt-oss-20b
BenchmarkGLM 4.7 Flashgpt-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 4.7 Flash$0.0003Fits in one request
gpt-oss-20b$0.0001Fits in one request

gpt-oss-20b costs less

Repository review

50K input + 3K output tokens

GLM 4.7 Flash$0.0045Fits in one request
gpt-oss-20b$0.0019Fits in one request

gpt-oss-20b costs less

Agent loop

200K input + 10K output tokens

GLM 4.7 Flash$0.017Exceeds 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 4.7 Flash and gpt-oss-20b
SpecificationZ.ai GLM 4.7 FlashOpenAI gpt-oss-20b
MakerZ.aiOpenAI
WeightsOpen weightsOpen weights
ReleasedJanuary 19, 2026August 5, 2025
Context window200K131K
Input $/Mtok$0.0653$0.03
Output $/Mtok$0.40$0.15
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.7 Flash better than gpt-oss-20b for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. GLM 4.7 Flash has the edge where the context window is larger, 200K against 131K tokens, and where what matters is GPQA Diamond (Artificial Analysis run) or Humanity's Last Exam (Artificial Analysis run), where it leads.

Which is cheaper, GLM 4.7 Flash or gpt-oss-20b?

GLM 4.7 Flash costs $0.0653 per million input tokens and $0.40 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 4.7 Flash or gpt-oss-20b?

GLM 4.7 Flash, with 200K tokens against 131K.

How many benchmarks is the GLM 4.7 Flash vs gpt-oss-20b comparison based on?

37 benchmarks have a result for both models as of October 21, 2026. GLM 4.7 Flash'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.

Compare next