GLM 5.2 vs Nemotron 3.5 Super VL
Updated October 21, 2026. 9 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Nemotron 3.5 Super VL for coding: it scores 65.5 on the Vibe Coding Index against 57.7 for GLM 5.2.
Pick GLM 5.2 when what matters is SciCode or AA Intelligence Index, where it leads.
- Shared results
- 9
- GLM 5.2 only
- 88
- Nemotron 3.5 Super VL only
- 7
- Like-for-like categories
- 5 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.
Coding
Vibe Coding Index, four public coding benchmarks
Nemotron 3.5 Super VL
Nemotron 3.5 Super VL scores 65.5 against 57.7.
One benchmark behind each score
Intelligence
AA Intelligence Index
GLM 5.2
GLM 5.2 leads, 33.7 against 26.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GLM 5.2 has a AA Agentic Index result, 38.4.
Directional only
Reasoning
GPQA Diamond
No call
Only GLM 5.2 has a GPQA Diamond result, 85.6%.
Directional only
Knowledge
MMLU Pro
No call
Only GLM 5.2 has a MMLU Pro result, 86.7%.
Directional only
Web design
Design Arena: websites
GLM 5.2
GLM 5.2 leads, 1285 against 1171.
Same board, both measured
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nemotron 3.5 Super VL
GLM 5.2 $0.0035, Nemotron 3.5 Super VL $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GLM 5.2 has the number, $0.86.
Directional only
At a glance
- Coding index
- GLM 5.2 57.7 from 1 benchmark, Nemotron 3.5 Super VL 65.5 from 1 benchmark.
- Widest category
- Web design, 17.8 points apart on average over 5 shared benchmarks.
- Widest single gap
- Design Arena: game dev: GLM 5.2 1268 against Nemotron 3.5 Super VL 1108, 20.0 points apart on a 0 to 100 scale.
- Output price
- GLM 5.2 $7.00 against Nemotron 3.5 Super VL $0.50 per million output tokens, 14.0x apart.
- Context window
- Both take 1.05M 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.
| Category | GLM 5.2 | Bars | Nemotron 3.5 Super VL | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 1 | 0 | ||
| Web design | 5 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 9 | 0 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index10
| Benchmark | GLM 5.2 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 65.5% | Only Nemotron 3.5 Super VL measured |
| LMArena WebDev | 1604 | Not measured | Only GLM 5.2 measured |
| AA Coding Index | 68.8 | Not measured | Only GLM 5.2 measured |
| LiveCodeBench (Vals AI) | 69.5% | Not measured | Only GLM 5.2 measured |
| SWE-bench Verified (Vals AI) | 82.8% | Not measured | Only GLM 5.2 measured |
| Vibe Code Bench (Vals AI) | 64.0% | Not measured | Only GLM 5.2 measured |
| Code migration (Vals AI) | 37.9% | Not measured | Only GLM 5.2 measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only GLM 5.2 measured |
| Terminal-Bench 2.1 (Vals AI) | 67.8% | Not measured | Only GLM 5.2 measured |
| SkillsBench (Vals AI) | 45.1% | Not measured | Only GLM 5.2 measured |
| SciCode | 51.2% | 47.8% | GLM 5.2 |
| Terminal-Bench Hard (Artificial Analysis run) | 50.8% | Not measured | Only GLM 5.2 measured |
| FrontierCode | 24.5% | Not measured | Only GLM 5.2 measured |
| WeirdML | 70.1% | Not measured | Only GLM 5.2 measured |
| ALE-Bench | 1047.0 | Not measured | Only GLM 5.2 measured |
| LMArena Text: coding | 1487 | Not measured | Only GLM 5.2 measured |
| LMArena Text: software and IT | 1486 | Not measured | Only GLM 5.2 measured |
| LMArena WebDev: React | 1617 | Not measured | Only GLM 5.2 measured |
| LMArena WebDev: HTML | 1565 | Not measured | Only GLM 5.2 measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5.2 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| AA Intelligence Index | 33.7 | 26.5 | GLM 5.2 |
| Epoch Capabilities Index | 151.9 | Not measured | Only GLM 5.2 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index20 boards, none shared
| Benchmark | GLM 5.2 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| AA Agentic Index | 38.4 | Not measured | Only GLM 5.2 measured |
| Design Arena: agents building web apps | 1222 | Not measured | Only GLM 5.2 measured |
| Design Arena: agents building full-stack apps | 1241 | Not measured | Only GLM 5.2 measured |
| Design Arena: agents building mobile apps | 1160 | Not measured | Only GLM 5.2 measured |
| Design Arena: agents building Android apps | 1184 | Not measured | Only GLM 5.2 measured |
| Design Arena: agents building Godot games | 1142 | Not measured | Only GLM 5.2 measured |
| Design Arena: agents building games | 1206 | Not measured | Only GLM 5.2 measured |
| Design Arena: HTML slides | 1175 | Not measured | Only GLM 5.2 measured |
| Design Arena: PowerPoint slides | 1195 | Not measured | Only GLM 5.2 measured |
| LiveBench research | Not measured | 70.9% | Only Nemotron 3.5 Super VL measured |
| LiveBench browser | Not measured | 4.0% | Only Nemotron 3.5 Super VL measured |
| LiveBench long agentic | Not measured | 15.8% | Only Nemotron 3.5 Super VL measured |
| SREBench (Vals AI) | 0.0% | Not measured | Only GLM 5.2 measured |
| Finance Agent (Vals AI) | 49.7% | Not measured | Only GLM 5.2 measured |
| Legal Research Bench (Vals AI) | 31.3% | Not measured | Only GLM 5.2 measured |
| Excel Modeling Benchmark (Vals AI) | 61.5% | Not measured | Only GLM 5.2 measured |
| τ²-Bench Telecom | 99.1% | Not measured | Only GLM 5.2 measured |
| APEX-Agents | 45.2% | Not measured | Only GLM 5.2 measured |
| PostTrainBench | 31.7% | Not measured | Only GLM 5.2 measured |
| Vending-Bench 2 | $8,314 | Not measured | Only GLM 5.2 measured |
| Neither model has a result on the other 19 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5.2 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| GPQA Diamond | 85.6% | Not measured | Only GLM 5.2 measured |
| LiveBench reasoning | Not measured | 78.8% | Only Nemotron 3.5 Super VL measured |
| GPQA Diamond (Artificial Analysis run) | 89.5% | Not measured | Only GLM 5.2 measured |
| Humanity's Last Exam (Artificial Analysis run) | 41.1% | 30.7% | GLM 5.2 |
| GPQA Diamond (Epoch AI run) | 91.9% | Not measured | Only GLM 5.2 measured |
| ARC-AGI | 77.0% | Not measured | Only GLM 5.2 measured |
| ARC-AGI-2 | 22.8% | Not measured | Only GLM 5.2 measured |
| SimpleBench | 58.8% | Not measured | Only GLM 5.2 measured |
| Chess puzzles | 22.0% | Not measured | Only GLM 5.2 measured |
| Mystery game puzzles | 19.0% | Not measured | Only GLM 5.2 measured |
| EBR-bench | 9.5% | Not measured | Only GLM 5.2 measured |
| LMArena Text: hard prompts | 1481 | Not measured | Only GLM 5.2 measured |
| LMArena Text: expert | 1487 | Not measured | Only GLM 5.2 measured |
| LMArena Text: hard prompts in English | 1481 | Not measured | Only GLM 5.2 measured |
| Neither model has a result on the other 7 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GLM 5.2 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| OTIS Mock AIME | 86.4% | Not measured | Only GLM 5.2 measured |
| FrontierMath, tiers 1 to 3 | 59.2% | Not measured | Only GLM 5.2 measured |
| FrontierMath, tier 4 | 29.3% | Not measured | Only GLM 5.2 measured |
| ProofBench | 35.0% | Not measured | Only GLM 5.2 measured |
| LMArena Text: math | 1483 | Not measured | Only GLM 5.2 measured |
| LMArena Text: mathematical work | 1489 | Not measured | Only GLM 5.2 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | GLM 5.2 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| MMLU Pro | 86.7% | Not measured | Only GLM 5.2 measured |
| LegalBench (Vals AI) | 84.1% | Not measured | Only GLM 5.2 measured |
| CorpFin (Vals AI) | 66.1% | Not measured | Only GLM 5.2 measured |
| TaxEval (Vals AI) | 73.3% | Not measured | Only GLM 5.2 measured |
| MedCode (Vals AI) | 40.8% | Not measured | Only GLM 5.2 measured |
| SimpleQA Verified | 34.2% | Not measured | Only GLM 5.2 measured |
| LMArena Text: science | 1489 | Not measured | Only GLM 5.2 measured |
| LMArena Text: medicine and healthcare | 1475 | Not measured | Only GLM 5.2 measured |
| LMArena Text: legal and government | 1486 | Not measured | Only GLM 5.2 measured |
| LMArena Text: business and finance | 1451 | Not measured | Only GLM 5.2 measured |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | GLM 5.2 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| Design Arena: websites | 1285 | 1171 | GLM 5.2 |
| Design Arena: UI components | 1296 | 1148 | GLM 5.2 |
| Design Arena: game dev | 1268 | 1108 | GLM 5.2 |
| Design Arena: data viz | 1285 | Not measured | Only GLM 5.2 measured |
| Design Arena: 3D | 1288 | 1132 | GLM 5.2 |
| Design Arena: all code categories | 1288 | 1155 | GLM 5.2 |
| Design Arena: SVG | 1214 | Not measured | Only GLM 5.2 measured |
| Design Arena: ASCII art | 1190 | Not measured | Only GLM 5.2 measured |
| LiveBench design | Not measured | 60.7% | Only Nemotron 3.5 Super VL measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5.2 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 64.6% | Only Nemotron 3.5 Super VL measured |
| MedScribe (Vals AI) | 83.5% | Not measured | Only GLM 5.2 measured |
| IFBench | 73.3% | Not measured | Only GLM 5.2 measured |
| Long context reasoning (AA-LCR) | 78.3% | 69.0% | GLM 5.2 |
| DTBench | 93.6% | Not measured | Only GLM 5.2 measured |
| LMCA | 45.8% | Not measured | Only GLM 5.2 measured |
| Surface Evolver Bench | 55.6% | Not measured | Only GLM 5.2 measured |
| LMArena Text | 1470 | Not measured | Only GLM 5.2 measured |
| LMArena Text: instruction following | 1466 | Not measured | Only GLM 5.2 measured |
| LMArena Text: creative writing | 1463 | Not measured | Only GLM 5.2 measured |
| LMArena Text: English | 1475 | Not measured | Only GLM 5.2 measured |
| LMArena Text: non-English | 1459 | Not measured | Only GLM 5.2 measured |
| LMArena Text: Chinese | 1522 | Not measured | Only GLM 5.2 measured |
| LMArena Text: German | 1470 | Not measured | Only GLM 5.2 measured |
| LMArena Text: Japanese | 1450 | Not measured | Only GLM 5.2 measured |
| LMArena Text: Korean | 1440 | Not measured | Only GLM 5.2 measured |
| LMArena Text: French | 1479 | Not measured | Only GLM 5.2 measured |
| LMArena Text: Spanish | 1478 | Not measured | Only GLM 5.2 measured |
| LMArena Text: Russian | 1468 | Not measured | Only GLM 5.2 measured |
| LMArena Text: Polish | 1456 | Not measured | Only GLM 5.2 measured |
| LMArena Text: multi-turn | 1469 | Not measured | Only GLM 5.2 measured |
| LMArena Text: longer queries | 1480 | Not measured | Only GLM 5.2 measured |
| LMArena Text: writing and language | 1463 | Not measured | Only GLM 5.2 measured |
| LMArena Text: entertainment and media | 1450 | Not measured | Only GLM 5.2 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
| Benchmark | GLM 5.2 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| 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
Nemotron 3.5 Super VL costs less
Repository review
50K input + 3K output tokens
Nemotron 3.5 Super VL costs less
Agent loop
200K input + 10K output tokens
Nemotron 3.5 Super VL 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.
| Specification | Z.ai GLM 5.2 | NVIDIA Nemotron 3.5 Super VL |
|---|---|---|
| Maker | Z.ai | NVIDIA |
| Weights | Open weights | Open weights |
| Released | June 16, 2026 | October 15, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.0341 | $0.15 |
| Output $/Mtok | $7.00 | $0.50 |
| Coding index | 57.7 | 65.5 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | $0.86 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5.2 better than Nemotron 3.5 Super VL for coding?
Pick Nemotron 3.5 Super VL for coding: it scores 65.5 on the Vibe Coding Index against 57.7 for GLM 5.2. Pick GLM 5.2 when what matters is SciCode or AA Intelligence Index, where it leads.
Which is cheaper, GLM 5.2 or Nemotron 3.5 Super VL?
GLM 5.2 costs $0.0341 per million input tokens and $7.00 per million output tokens; Nemotron 3.5 Super VL costs $0.15 and $0.50. Cost per solved task is known for GLM 5.2 only.
Which has the bigger context window, GLM 5.2 or Nemotron 3.5 Super VL?
Neither: both take 1.05M tokens.
How many benchmarks is the GLM 5.2 vs Nemotron 3.5 Super VL comparison based on?
9 benchmarks have a result for both models as of October 21, 2026. GLM 5.2's coding index rests on 1 independent benchmark and Nemotron 3.5 Super VL's on 1. Where only one model has a result, the page says so instead of naming a winner.