Gemma 4 31B vs Nemotron 3 Super
Gemma 4 31B leads Nemotron 3 Super on the Artificial Analysis Intelligence Index, 14.7 to 12.8, at about the same output price ($0.40 vs $0.45 per million). Updated October 22, 2026; 37 benchmarks have a result for both.
Gemma 4 31B or Nemotron 3 Super: which to pick
Only Gemma 4 31B has a coding score, 39.0 on the Vibe Coding Index; Nemotron 3 Super has none, so the two cannot be ranked on coding.
Pick Nemotron 3 Super for work measured by τ²-Bench Telecom, where it leads.
- Shared results
- 37
- Gemma 4 31B only
- 35
- Nemotron 3 Super 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Gemma 4 31B has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Gemma 4 31B
Gemma 4 31B leads, 14.7 against 12.8.
Same board, both measured
Agentic work
AA Agentic Index
Gemma 4 31B
Gemma 4 31B leads, 4.2 against 1.7.
Same board, both measured
Long documents
Listed context window
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nemotron 3 Super
Gemma 4 31B $0.0003, Nemotron 3 Super $0.0003 per turn.
List prices
At a glance
- Coding index
- Gemma 4 31B 39.0 from 2 benchmarks, Nemotron 3 Super not benchmarked.
- Widest category
- Math, 11.8 points apart on average over 2 shared benchmarks.
- Widest single gap
- ALE-Bench: Gemma 4 31B 925.5 against Nemotron 3 Super 213.9, 23.7 points apart on a 0 to 100 scale.
- Output price
- Gemma 4 31B $0.40 against Nemotron 3 Super $0.45 per million output tokens, 1.1x apart.
- Context window
- Both take 262K 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 | Gemma 4 31B | Bars | Nemotron 3 Super | Ties |
|---|---|---|---|---|
| Coding | 7 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 1 | ||
| Reasoning | 5 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 16 | 0 | ||
| All shared boards | 36 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
| Benchmark | Gemma 4 31B | Nemotron 3 Super | Leader |
|---|---|---|---|
| LiveBench coding | 49.0% | Not measured | Only Gemma 4 31B measured |
| LMArena WebDev | 1367 | Not measured | Only Gemma 4 31B measured |
| AA Coding Index | 43.4 | 37.7 | Gemma 4 31B |
| SciCode | 45.5% | 36.2% | Gemma 4 31B |
| Terminal-Bench Hard (Artificial Analysis run) | 36.4% | 28.8% | Gemma 4 31B |
| WeirdML | 52.3% | 38.0% | Gemma 4 31B |
| ALE-Bench | 925.5 | 213.9 | Gemma 4 31B |
| LMArena Text: coding | 1459 | 1403 | Gemma 4 31B |
| LMArena Text: software and IT | 1463 | 1409 | Gemma 4 31B |
| LMArena WebDev: React | 1359 | Not measured | Only Gemma 4 31B measured |
| LMArena WebDev: HTML | 1380 | Not measured | Only Gemma 4 31B measured |
| SciCode | 8.9% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemma 4 31B | Nemotron 3 Super | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.7 | 12.8 | Gemma 4 31B |
| Epoch Capabilities Index | 143.0 | Not measured | Only Gemma 4 31B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Gemma 4 31B | Nemotron 3 Super | Leader |
|---|---|---|---|
| AA Agentic Index | 4.2 | 1.7 | Gemma 4 31B |
| LiveBench research | 44.4% | Not measured | Only Gemma 4 31B measured |
| LiveBench browser | 4.0% | Not measured | Only Gemma 4 31B measured |
| LiveBench long agentic | 13.3% | Not measured | Only Gemma 4 31B measured |
| τ²-Bench Telecom | 65.5% | 67.8% | Nemotron 3 Super |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Gemma 4 31B | Nemotron 3 Super | Leader |
|---|---|---|---|
| LiveBench reasoning | 68.3% | Not measured | Only Gemma 4 31B measured |
| GPQA Diamond (Artificial Analysis run) | 85.7% | 80.0% | Gemma 4 31B |
| Humanity's Last Exam (Artificial Analysis run) | 23.6% | 20.8% | Gemma 4 31B |
| GPQA Diamond (Epoch AI run) | 75.8% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: hard prompts | 1448 | 1386 | Gemma 4 31B |
| LMArena Text: expert | 1464 | 1398 | Gemma 4 31B |
| LMArena Text: hard prompts in English | 1456 | 1397 | Gemma 4 31B |
| LMArena Vision: diagrams | 1283 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: homework | 1310 | Not measured | Only Gemma 4 31B measured |
| Kagi LLM Benchmark | 63.5% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemma 4 31B | Nemotron 3 Super | Leader |
|---|---|---|---|
| OTIS Mock AIME | 73.3% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: math | 1463 | 1380 | Gemma 4 31B |
| LMArena Text: mathematical work | 1465 | 1405 | Gemma 4 31B |
| MathArena | Not measured | 16.6% | Only Nemotron 3 Super measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Gemma 4 31B | Nemotron 3 Super | Leader |
|---|---|---|---|
| CaseLaw (Vals AI) | 52.6% | Not measured | Only Gemma 4 31B measured |
| MortgageTax (Vals AI) | 61.4% | Not measured | Only Gemma 4 31B measured |
| SimpleQA Verified | 10.4% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: science | 1457 | 1387 | Gemma 4 31B |
| LMArena Text: medicine and healthcare | 1451 | 1383 | Gemma 4 31B |
| LMArena Text: legal and government | 1438 | 1392 | Gemma 4 31B |
| LMArena Text: business and finance | 1430 | 1364 | Gemma 4 31B |
| FACTS Benchmark Suite | 45.3% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Gemma 4 31B | Nemotron 3 Super | Leader |
|---|---|---|---|
| LiveBench design | 58.4% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 8 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index160
| Benchmark | Gemma 4 31B | Nemotron 3 Super | Leader |
|---|---|---|---|
| LiveBench data analysis | 53.3% | Not measured | Only Gemma 4 31B measured |
| SAGE (Vals AI) | 55.0% | Not measured | Only Gemma 4 31B measured |
| IFBench | 75.6% | 71.5% | Gemma 4 31B |
| Long context reasoning (AA-LCR) | 69.7% | 65.7% | Gemma 4 31B |
| DTBench | 82.7% | Not measured | Only Gemma 4 31B measured |
| LMCA | 39.3% | Not measured | Only Gemma 4 31B measured |
| Surface Evolver Bench | 30.6% | Not measured | Only Gemma 4 31B measured |
| LMArena Text | 1443 | 1378 | Gemma 4 31B |
| LMArena Text: instruction following | 1433 | 1347 | Gemma 4 31B |
| LMArena Text: creative writing | 1417 | 1317 | Gemma 4 31B |
| LMArena Vision | 1276 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: English | 1451 | 1400 | Gemma 4 31B |
| LMArena Text: non-English | 1430 | 1356 | Gemma 4 31B |
| LMArena Text: Chinese | 1475 | 1431 | Gemma 4 31B |
| LMArena Text: German | Not measured | 1341 | Only Nemotron 3 Super measured |
| LMArena Text: French | 1436 | 1403 | Gemma 4 31B |
| LMArena Text: Spanish | 1442 | 1418 | Gemma 4 31B |
| LMArena Text: Russian | 1460 | 1336 | Gemma 4 31B |
| LMArena Text: Polish | 1433 | 1346 | Gemma 4 31B |
| LMArena Text: multi-turn | 1452 | 1369 | Gemma 4 31B |
| LMArena Text: longer queries | 1446 | 1362 | Gemma 4 31B |
| LMArena Text: writing and language | 1432 | 1332 | Gemma 4 31B |
| LMArena Text: entertainment and media | 1405 | 1336 | Gemma 4 31B |
| LMArena Vision: English | 1271 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: Chinese | 1326 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: reading text | 1282 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: humor | 1280 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: captioning | 1218 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: recognizing things | 1226 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: creative writing | 1285 | Not measured | Only Gemma 4 31B measured |
| LMArena Document | 1425 | Not measured | Only Gemma 4 31B measured |
| EQ-Bench 4 | 1120 | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 4 31B | Nemotron 3 Super | 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 Super costs less
Repository review
50K input + 3K output tokens
Nemotron 3 Super costs less
Agent loop
200K input + 10K output tokens
Nemotron 3 Super 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 31B | NVIDIA Nemotron 3 Super |
|---|---|---|
| Maker | NVIDIA | |
| Weights | Open weights | Open weights |
| Released | April 2, 2026 | March 11, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.14 | $0.085 |
| Output $/Mtok | $0.40 | $0.45 |
| Coding index | 39.0 | Not benchmarked |
| Independent measurements behind it | 2 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 4 31B better than Nemotron 3 Super for coding?
Only Gemma 4 31B has a coding score, 39.0 on the Vibe Coding Index; Nemotron 3 Super has none, so the two cannot be ranked on coding. Pick Nemotron 3 Super for work measured by τ²-Bench Telecom, where it leads.
Which is cheaper, Gemma 4 31B or Nemotron 3 Super?
Gemma 4 31B costs $0.14 per million input tokens and $0.40 per million output tokens; Nemotron 3 Super costs $0.085 and $0.45. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemma 4 31B or Nemotron 3 Super?
Neither: both take 262K tokens.
How many benchmarks is the Gemma 4 31B vs Nemotron 3 Super comparison based on?
37 benchmarks have a result for both models as of October 22, 2026. Gemma 4 31B's coding index rests on 2 independent benchmarks and Nemotron 3 Super's on 0. Where only one model has a result, the page says so instead of naming a winner.