GLM 4.7 Flash vs Nemotron 3.5 Super VL
Nemotron 3.5 Super VL leads GLM 4.7 Flash on the Artificial Analysis Intelligence Index, 26.5 to 14.9, and GLM 4.7 Flash costs 1.3x less per output token ($0.40 vs $0.50 per million). Updated October 22, 2026; 8 benchmarks have a result for both.
GLM 4.7 Flash or Nemotron 3.5 Super VL: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GLM 4.7 Flash for output tokens 1.3x cheaper ($0.40 vs $0.50 per million) and work measured by AA Intelligence Index or Humanity's Last Exam (Artificial Analysis run), where it leads.
- Shared results
- 8
- GLM 4.7 Flash only
- 35
- Nemotron 3.5 Super VL only
- 8
- Like-for-like categories
- 4 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Nemotron 3.5 Super VL
Nemotron 3.5 Super VL leads, 26.5 against 14.9.
Same board, both measured
Web design
Design Arena: websites
GLM 4.7 Flash
GLM 4.7 Flash leads, 1194 against 1172.
Same board, both measured
Long documents
Listed context window
Nemotron 3.5 Super VL
Nemotron 3.5 Super VL takes 1.05M tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 4.7 Flash
GLM 4.7 Flash $0.0003, Nemotron 3.5 Super VL $0.0004 per turn.
List prices
At a glance
- Coding index
- GLM 4.7 Flash not benchmarked, Nemotron 3.5 Super VL not benchmarked.
- Widest category
- General, 27.3 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): GLM 4.7 Flash 41.7% against Nemotron 3.5 Super VL 69.0%, 27.3 points apart on a 0 to 100 scale.
- Output price
- GLM 4.7 Flash $0.40 against Nemotron 3.5 Super VL $0.50 per million output tokens, 1.3x apart.
- Context window
- GLM 4.7 Flash takes 200K tokens, Nemotron 3.5 Super VL 1.05M.
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 4.7 Flash | Bars | Nemotron 3.5 Super VL | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| Web design | 4 | 1 | ||
| General | 0 | 1 | ||
| All shared boards | 4 | 4 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index5 boards, none shared
| Benchmark | GLM 4.7 Flash | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 65.5% | Only Nemotron 3.5 Super VL measured |
| SciCode | Not measured | 47.8% | Only Nemotron 3.5 Super VL measured |
| Terminal-Bench Hard (Artificial Analysis run) | 22.0% | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: coding | 1382 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: software and IT | 1389 | Not measured | Only GLM 4.7 Flash measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 4.7 Flash | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.9 | 26.5 | Nemotron 3.5 Super VL |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GLM 4.7 Flash | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| 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 |
| τ²-Bench Telecom | 98.8% | Not measured | Only GLM 4.7 Flash measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 4.7 Flash | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 78.8% | Only Nemotron 3.5 Super VL measured |
| GPQA Diamond (Artificial Analysis run) | 58.1% | Not measured | Only GLM 4.7 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | 7.6% | 30.7% | Nemotron 3.5 Super VL |
| GPQA Diamond (Epoch AI run) | 60.5% | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: hard prompts | 1356 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: expert | 1357 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: hard prompts in English | 1369 | Not measured | Only GLM 4.7 Flash measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GLM 4.7 Flash | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| OTIS Mock AIME | 58.3% | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: math | 1355 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: mathematical work | 1369 | Not measured | Only GLM 4.7 Flash measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GLM 4.7 Flash | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LMArena Text: science | 1358 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: medicine and healthcare | 1343 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: legal and government | 1357 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: business and finance | 1343 | Not measured | Only GLM 4.7 Flash measured |
| Neither model has a result on the other 14 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | GLM 4.7 Flash | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| Design Arena: websites | 1194 | 1172 | GLM 4.7 Flash |
| Design Arena: UI components | 1205 | 1153 | GLM 4.7 Flash |
| Design Arena: game dev | 1134 | 1110 | GLM 4.7 Flash |
| Design Arena: data viz | 1123 | Not measured | Only GLM 4.7 Flash measured |
| Design Arena: 3D | 1120 | 1127 | Nemotron 3.5 Super VL |
| Design Arena: all code categories | 1177 | 1155 | GLM 4.7 Flash |
| Design Arena: SVG | 1037 | Not measured | Only GLM 4.7 Flash measured |
| LiveBench design | Not measured | 60.7% | Only Nemotron 3.5 Super VL measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 4.7 Flash | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 64.6% | Only Nemotron 3.5 Super VL measured |
| IFBench | 60.8% | Not measured | Only GLM 4.7 Flash measured |
| Long context reasoning (AA-LCR) | 41.7% | 69.0% | Nemotron 3.5 Super VL |
| LMArena Text | 1351 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: instruction following | 1327 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: creative writing | 1296 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: English | 1373 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: non-English | 1330 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: Chinese | 1403 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: German | 1336 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: Korean | 1283 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: French | 1332 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: Spanish | 1350 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: Russian | 1333 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: Polish | 1291 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: multi-turn | 1342 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: longer queries | 1345 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: writing and language | 1320 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: entertainment and media | 1304 | Not measured | Only GLM 4.7 Flash measured |
| Neither model has a result on the other 27 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 4.7 Flash | 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
GLM 4.7 Flash costs less
Repository review
50K input + 3K output tokens
GLM 4.7 Flash costs less
Agent loop
200K input + 10K output tokens
GLM 4.7 Flash 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 4.7 Flash | NVIDIA Nemotron 3.5 Super VL |
|---|---|---|
| Maker | Z.ai | NVIDIA |
| Weights | Open weights | Open weights |
| Released | January 19, 2026 | October 15, 2026 |
| Context window | 200K | 1.05M |
| Input $/Mtok | $0.0653 | $0.15 |
| Output $/Mtok | $0.40 | $0.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 4.7 Flash better than Nemotron 3.5 Super VL for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 4.7 Flash for output tokens 1.3x cheaper ($0.40 vs $0.50 per million) and work measured by AA Intelligence Index or Humanity's Last Exam (Artificial Analysis run), where it leads.
Which is cheaper, GLM 4.7 Flash or Nemotron 3.5 Super VL?
GLM 4.7 Flash costs $0.0653 per million input tokens and $0.40 per million output tokens; Nemotron 3.5 Super VL costs $0.15 and $0.50. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 4.7 Flash or Nemotron 3.5 Super VL?
Nemotron 3.5 Super VL, with 1.05M tokens against 200K.
How many benchmarks is the GLM 4.7 Flash vs Nemotron 3.5 Super VL comparison based on?
8 benchmarks have a result for both models as of October 22, 2026. GLM 4.7 Flash's coding index rests on 0 independent benchmarks 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.