Gemma 4 26B A4B vs Nemotron 3.5 Super VL
Nemotron 3.5 Super VL leads Gemma 4 26B A4B on the Artificial Analysis Intelligence Index, 26.5 to 16.7, and Nemotron 3.5 Super VL costs 1.2x less per output token ($0.50 vs $0.60 per million). Updated October 22, 2026; 4 benchmarks have a result for both.
Gemma 4 26B A4B 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 Gemma 4 26B A4B for work measured by SciCode or AA Intelligence Index, where it leads.
- Shared results
- 4
- Gemma 4 26B A4B only
- 51
- Nemotron 3.5 Super VL only
- 12
- 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 16.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Gemma 4 26B A4B has a AA Agentic Index result, 2.9.
Directional only
Web design
Design Arena: websites
No call
Only Nemotron 3.5 Super VL has a Design Arena: websites result, 1173.
Directional only
Long documents
Listed context window
Nemotron 3.5 Super VL
Nemotron 3.5 Super VL takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nemotron 3.5 Super VL
Gemma 4 26B A4B $0.0004, Nemotron 3.5 Super VL $0.0004 per turn.
List prices
At a glance
- Coding index
- Gemma 4 26B A4B not benchmarked, Nemotron 3.5 Super VL not benchmarked.
- Widest category
- Reasoning, 11.4 points apart on average over 1 shared benchmark.
- Widest single gap
- Humanity's Last Exam (Artificial Analysis run): Gemma 4 26B A4B 19.3% against Nemotron 3.5 Super VL 30.7%, 11.4 points apart on a 0 to 100 scale.
- Output price
- Gemma 4 26B A4B $0.60 against Nemotron 3.5 Super VL $0.50 per million output tokens, 1.2x apart.
- Context window
- Gemma 4 26B A4B takes 262K 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 | Gemma 4 26B A4B | Bars | Nemotron 3.5 Super VL | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 4 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Gemma 4 26B A4B | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 65.5% | Only Nemotron 3.5 Super VL measured |
| LMArena WebDev | 1360 | Not measured | Only Gemma 4 26B A4B measured |
| AA Coding Index | 39.3 | Not measured | Only Gemma 4 26B A4B measured |
| SciCode | 40.0% | 47.8% | Nemotron 3.5 Super VL |
| Terminal-Bench Hard (Artificial Analysis run) | 25.0% | Not measured | Only Gemma 4 26B A4B measured |
| WeirdML | 35.2% | Not measured | Only Gemma 4 26B A4B measured |
| ALE-Bench | 927.2 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: coding | 1446 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: software and IT | 1454 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena WebDev: React | 1351 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena WebDev: HTML | 1362 | Not measured | Only Gemma 4 26B A4B measured |
| Neither model has a result on the other 32 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 4 26B A4B | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.7 | 26.5 | Nemotron 3.5 Super VL |
| Epoch Capabilities Index | 141.9 | Not measured | Only Gemma 4 26B A4B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Gemma 4 26B A4B | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| AA Agentic Index | 2.9 | Not measured | Only Gemma 4 26B A4B 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 |
| τ²-Bench Telecom | 43.6% | Not measured | Only Gemma 4 26B A4B 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 | Gemma 4 26B A4B | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 78.8% | Only Nemotron 3.5 Super VL measured |
| GPQA Diamond (Artificial Analysis run) | 79.2% | Not measured | Only Gemma 4 26B A4B measured |
| Humanity's Last Exam (Artificial Analysis run) | 19.3% | 30.7% | Nemotron 3.5 Super VL |
| GPQA Diamond (Epoch AI run) | 73.2% | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: hard prompts | 1438 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: expert | 1447 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: hard prompts in English | 1448 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: diagrams | 1264 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: homework | 1293 | Not measured | Only Gemma 4 26B A4B measured |
| Neither model has a result on the other 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Gemma 4 26B A4B | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| OTIS Mock AIME | 82.2% | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: math | 1470 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: mathematical work | 1475 | Not measured | Only Gemma 4 26B A4B measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Gemma 4 26B A4B | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LMArena Text: science | 1446 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: medicine and healthcare | 1428 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: legal and government | 1457 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: business and finance | 1429 | Not measured | Only Gemma 4 26B A4B measured |
| FACTS Benchmark Suite | 42.7% | Not measured | Only Gemma 4 26B A4B measured |
| Neither model has a result on the other 15 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Gemma 4 26B A4B | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1173 | Only Nemotron 3.5 Super VL measured |
| Design Arena: UI components | Not measured | 1149 | Only Nemotron 3.5 Super VL measured |
| Design Arena: game dev | Not measured | 1110 | Only Nemotron 3.5 Super VL measured |
| Design Arena: 3D | Not measured | 1128 | Only Nemotron 3.5 Super VL measured |
| Design Arena: all code categories | Not measured | 1154 | Only Nemotron 3.5 Super VL measured |
| LiveBench design | Not measured | 60.7% | Only Nemotron 3.5 Super VL measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 4 26B A4B | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 64.6% | Only Nemotron 3.5 Super VL measured |
| IFBench | 72.4% | Not measured | Only Gemma 4 26B A4B measured |
| Long context reasoning (AA-LCR) | 65.7% | 69.0% | Nemotron 3.5 Super VL |
| DTBench | 74.9% | Not measured | Only Gemma 4 26B A4B measured |
| LMCA | 29.7% | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text | 1434 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: instruction following | 1420 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: creative writing | 1400 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision | 1260 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: English | 1444 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: non-English | 1421 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: Chinese | 1495 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: French | 1460 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: Spanish | 1415 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: Russian | 1434 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: multi-turn | 1441 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: longer queries | 1427 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: writing and language | 1405 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Text: entertainment and media | 1403 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: English | 1256 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: Chinese | 1312 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: reading text | 1268 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: humor | 1272 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: captioning | 1297 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: recognizing things | 1191 | Not measured | Only Gemma 4 26B A4B measured |
| LMArena Vision: creative writing | 1256 | Not measured | Only Gemma 4 26B A4B 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 | Gemma 4 26B A4B | 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 | Google Gemma 4 26B A4B | NVIDIA Nemotron 3.5 Super VL |
|---|---|---|
| Maker | NVIDIA | |
| Weights | Open weights | Open weights |
| Released | April 3, 2026 | October 15, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $0.15 | $0.15 |
| Output $/Mtok | $0.60 | $0.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 4 26B A4B 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 Gemma 4 26B A4B for work measured by SciCode or AA Intelligence Index, where it leads.
Which is cheaper, Gemma 4 26B A4B or Nemotron 3.5 Super VL?
Gemma 4 26B A4B costs $0.15 per million input tokens and $0.60 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, Gemma 4 26B A4B or Nemotron 3.5 Super VL?
Nemotron 3.5 Super VL, with 1.05M tokens against 262K.
How many benchmarks is the Gemma 4 26B A4B vs Nemotron 3.5 Super VL comparison based on?
4 benchmarks have a result for both models as of October 22, 2026. Gemma 4 26B A4B'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.