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GLM 4.7 vs Nemotron 3 Nano 30B A3B

GLM 4.7 leads Nemotron 3 Nano 30B A3B on the Artificial Analysis Intelligence Index, 22.2 to 8.9, and Nemotron 3 Nano 30B A3B costs 10.0x less per output token ($0.22 vs $2.20 per million). Updated October 22, 2026; 40 benchmarks have a result for both.

Replace GLM 4.7 Replace Nemotron 3 Nano 30B A3B
GLM 4.7Z.ai
Coding
55.1
Overall
56.9
Output $/M
$2.20
39
Nemotron 3 Nano 30B A3BNVIDIA
Coding
No data
Overall
No data
Output $/M
$0.22
1
vs boards won of 40 shared

GLM 4.7 or Nemotron 3 Nano 30B A3B: which to pick

Only GLM 4.7 has a coding score, 55.1 on the Vibe Coding Index; Nemotron 3 Nano 30B A3B has none, so the two cannot be ranked on coding.

Pick Nemotron 3 Nano 30B A3B for output tokens 10.0x cheaper ($0.22 vs $2.20 per million) and a larger context window (262K against 205K tokens).

Model AGLM 4.7Z.ai55.1/1002 independent benchmarks$0.29 per solved taskModel BNemotron 3 Nano 30B A3BNVIDIANot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
40
GLM 4.7 only
42
Nemotron 3 Nano 30B A3B only
2
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 4.7 55.1 from 2 benchmarks, Nemotron 3 Nano 30B A3B not benchmarked.
Widest category
Agentic work, 55.0 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GLM 4.7 95.9% against Nemotron 3 Nano 30B A3B 40.9%, 55.0 points apart on a 0 to 100 scale.
Output price
GLM 4.7 $2.20 against Nemotron 3 Nano 30B A3B $0.22 per million output tokens, 10.0x apart.
Context window
GLM 4.7 takes 205K tokens, Nemotron 3 Nano 30B A3B 262K.

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 4.7BarsNemotron 3 Nano 30B A3BTies
Coding50
Intelligence10
Agentic work10
Reasoning50
Math40
Knowledge50
General181
All shared boards391
CodingLike-for-likeSix of these boards feed the Vibe Coding Index50
Coding benchmarks for GLM 4.7 and Nemotron 3 Nano 30B A3B
BenchmarkGLM 4.7Nemotron 3 Nano 30B A3BLeader
LMArena WebDev1435Not measuredOnly GLM 4.7 measured
AA Coding Index45.314.4GLM 4.7
LiveCodeBench (Vals AI)82.2%Not measuredOnly GLM 4.7 measured
SWE-bench Verified (Vals AI)69.4%Not measuredOnly GLM 4.7 measured
LiveCodeBench (Artificial Analysis run)89.4%74.1%GLM 4.7
SciCodeNot measured30.6%Only Nemotron 3 Nano 30B A3B measured
Terminal-Bench Hard (Artificial Analysis run)31.8%13.6%GLM 4.7
Terminal-Bench33.4%Not measuredOnly GLM 4.7 measured
ALE-Bench399.5Not measuredOnly GLM 4.7 measured
LMArena Text: coding14541378GLM 4.7
LMArena Text: software and IT14531383GLM 4.7
LMArena WebDev: React1420Not measuredOnly GLM 4.7 measured
LMArena WebDev: HTML1447Not measuredOnly GLM 4.7 measured
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 4.7 and Nemotron 3 Nano 30B A3B
BenchmarkGLM 4.7Nemotron 3 Nano 30B A3BLeader
AA Intelligence Index22.28.9GLM 4.7
Epoch Capabilities Index143.6Not measuredOnly GLM 4.7 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 4.7 and Nemotron 3 Nano 30B A3B
BenchmarkGLM 4.7Nemotron 3 Nano 30B A3BLeader
AA Agentic IndexNot measured1.0Only Nemotron 3 Nano 30B A3B measured
Design Arena: agents building full-stack apps1050Not measuredOnly GLM 4.7 measured
Design Arena: agents building mobile apps1105Not measuredOnly GLM 4.7 measured
Design Arena: agents building Android apps1112Not measuredOnly GLM 4.7 measured
Design Arena: agents building Godot games1058Not measuredOnly GLM 4.7 measured
τ²-Bench Telecom95.9%40.9%GLM 4.7
Vending-Bench 2$2,377Not measuredOnly GLM 4.7 measured
BrowseComp-Plus64.7%Not measuredOnly GLM 4.7 measured
MCP Atlas58.1%Not measuredOnly GLM 4.7 measured
Neither model has a result on the other 33 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for GLM 4.7 and Nemotron 3 Nano 30B A3B
BenchmarkGLM 4.7Nemotron 3 Nano 30B A3BLeader
GPQA Diamond80.0%Not measuredOnly GLM 4.7 measured
GPQA Diamond (Artificial Analysis run)85.9%75.7%GLM 4.7
Humanity's Last Exam (Artificial Analysis run)27.4%11.4%GLM 4.7
GPQA Diamond (Epoch AI run)83.3%Not measuredOnly GLM 4.7 measured
SimpleBench47.7%Not measuredOnly GLM 4.7 measured
Chess puzzles21.0%Not measuredOnly GLM 4.7 measured
LMArena Text: hard prompts14431348GLM 4.7
LMArena Text: expert14241355GLM 4.7
LMArena Text: hard prompts in English14521376GLM 4.7
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index40
Math benchmarks for GLM 4.7 and Nemotron 3 Nano 30B A3B
BenchmarkGLM 4.7Nemotron 3 Nano 30B A3BLeader
AIME93.3%Not measuredOnly GLM 4.7 measured
MGSM (Vals AI)88.2%Not measuredOnly GLM 4.7 measured
AA Math Index95.091.0GLM 4.7
AIME 2025 (Artificial Analysis run)95.0%91.0%GLM 4.7
OTIS Mock AIME83.3%Not measuredOnly GLM 4.7 measured
ProofBench6.0%Not measuredOnly GLM 4.7 measured
LMArena Text: math14241371GLM 4.7
LMArena Text: mathematical work14111375GLM 4.7
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
Knowledge benchmarks for GLM 4.7 and Nemotron 3 Nano 30B A3B
BenchmarkGLM 4.7Nemotron 3 Nano 30B A3BLeader
MMLU Pro82.7%Not measuredOnly GLM 4.7 measured
LegalBench (Vals AI)83.4%Not measuredOnly GLM 4.7 measured
CaseLaw (Vals AI)54.9%Not measuredOnly GLM 4.7 measured
CorpFin (Vals AI)46.4%Not measuredOnly GLM 4.7 measured
TaxEval (Vals AI)68.8%Not measuredOnly GLM 4.7 measured
MedQA (Vals AI)93.7%Not measuredOnly GLM 4.7 measured
MedCode (Vals AI)32.8%Not measuredOnly GLM 4.7 measured
MMLU Pro (Artificial Analysis run)85.6%79.4%GLM 4.7
SimpleQA Verified32.2%Not measuredOnly GLM 4.7 measured
LMArena Text: science14571353GLM 4.7
LMArena Text: medicine and healthcare14691349GLM 4.7
LMArena Text: legal and government14441341GLM 4.7
LMArena Text: business and finance14291346GLM 4.7
Neither model has a result on the other 7 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for GLM 4.7 and Nemotron 3 Nano 30B A3B
BenchmarkGLM 4.7Nemotron 3 Nano 30B A3BLeader
Design Arena: websites1225Not measuredOnly GLM 4.7 measured
Design Arena: UI components1197Not measuredOnly GLM 4.7 measured
Design Arena: game dev1188Not measuredOnly GLM 4.7 measured
Design Arena: data viz1196Not measuredOnly GLM 4.7 measured
Design Arena: 3D1190Not measuredOnly GLM 4.7 measured
Design Arena: all code categories1216Not measuredOnly GLM 4.7 measured
Design Arena: SVG1142Not measuredOnly GLM 4.7 measured
Design Arena: ASCII art1165Not measuredOnly GLM 4.7 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index181
General benchmarks for GLM 4.7 and Nemotron 3 Nano 30B A3B
BenchmarkGLM 4.7Nemotron 3 Nano 30B A3BLeader
MedScribe (Vals AI)68.6%Not measuredOnly GLM 4.7 measured
IFBench67.9%71.1%Nemotron 3 Nano 30B A3B
Long context reasoning (AA-LCR)71.0%38.0%GLM 4.7
CL-bench15.9%Not measuredOnly GLM 4.7 measured
CL-bench Life10.9%Not measuredOnly GLM 4.7 measured
LMArena Text14351348GLM 4.7
LMArena Text: instruction following14121303GLM 4.7
LMArena Text: creative writing14011269GLM 4.7
LMArena Text: English14531377GLM 4.7
LMArena Text: non-English14171320GLM 4.7
LMArena Text: Chinese14951383GLM 4.7
LMArena Text: German14261348GLM 4.7
LMArena Text: Japanese14391268GLM 4.7
LMArena Text: Korean13991269GLM 4.7
LMArena Text: French14321396GLM 4.7
LMArena Text: Spanish14341376GLM 4.7
LMArena Text: Russian14231304GLM 4.7
LMArena Text: Polish14351303GLM 4.7
LMArena Text: multi-turn14461319GLM 4.7
LMArena Text: longer queries14321300GLM 4.7
LMArena Text: writing and language14111283GLM 4.7
LMArena Text: entertainment and media14001293GLM 4.7
Neither model has a result on the other 26 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 4.7 and Nemotron 3 Nano 30B A3B
BenchmarkGLM 4.7Nemotron 3 Nano 30B A3BLeader
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$0.0017Fits in one request
Nemotron 3 Nano 30B A3B$0.0002Fits in one request

Nemotron 3 Nano 30B A3B costs less

Repository review

50K input + 3K output tokens

GLM 4.7$0.037Fits in one request
Nemotron 3 Nano 30B A3B$0.0034Fits in one request

Nemotron 3 Nano 30B A3B costs less

Agent loop

200K input + 10K output tokens

GLM 4.7$0.142Exceeds the context window
Nemotron 3 Nano 30B A3B$0.013Fits in one request

Nemotron 3 Nano 30B A3B 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 and Nemotron 3 Nano 30B A3B
SpecificationZ.ai GLM 4.7NVIDIA Nemotron 3 Nano 30B A3B
MakerZ.aiNVIDIA
WeightsOpen weightsOpen weights
ReleasedDecember 22, 2025December 14, 2025
Context window205K262K
Input $/Mtok$0.60$0.055
Output $/Mtok$2.20$0.22
Coding index55.1Not benchmarked
Independent measurements behind it20
Cost per solved task$0.29Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.7 better than Nemotron 3 Nano 30B A3B for coding?

Only GLM 4.7 has a coding score, 55.1 on the Vibe Coding Index; Nemotron 3 Nano 30B A3B has none, so the two cannot be ranked on coding. Pick Nemotron 3 Nano 30B A3B for output tokens 10.0x cheaper ($0.22 vs $2.20 per million) and a larger context window (262K against 205K tokens).

Which is cheaper, GLM 4.7 or Nemotron 3 Nano 30B A3B?

GLM 4.7 costs $0.60 per million input tokens and $2.20 per million output tokens; Nemotron 3 Nano 30B A3B costs $0.055 and $0.22. Cost per solved task is known for GLM 4.7 only.

Which has the bigger context window, GLM 4.7 or Nemotron 3 Nano 30B A3B?

Nemotron 3 Nano 30B A3B, with 262K tokens against 205K.

How many benchmarks is the GLM 4.7 vs Nemotron 3 Nano 30B A3B comparison based on?

40 benchmarks have a result for both models as of October 22, 2026. GLM 4.7's coding index rests on 2 independent benchmarks and Nemotron 3 Nano 30B A3B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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