Gemma 3 12B vs Nemotron 3.5 Lightning
Nemotron 3.5 Lightning leads Gemma 3 12B on the Artificial Analysis Intelligence Index, 12.9 to 3.8, at about the same output price ($0.147 vs $0.1625 per million). Updated October 22, 2026; 7 benchmarks have a result for both.
Gemma 3 12B or Nemotron 3.5 Lightning: which to pick
Only Nemotron 3.5 Lightning has a coding score, 22.6 on the Vibe Coding Index; Gemma 3 12B has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 7
- Gemma 3 12B only
- 36
- Nemotron 3.5 Lightning only
- 13
- Like-for-like categories
- 5 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 Nemotron 3.5 Lightning has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Nemotron 3.5 Lightning
Nemotron 3.5 Lightning leads, 12.9 against 3.8.
Same board, both measured
Agentic work
AA Agentic Index
Nemotron 3.5 Lightning
Nemotron 3.5 Lightning leads, 3.5 against 0.1.
Same board, both measured
Long documents
Listed context window
Nemotron 3.5 Lightning
Nemotron 3.5 Lightning takes 262K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nemotron 3.5 Lightning
Gemma 3 12B $0.0002, Nemotron 3.5 Lightning $0.0001 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Nemotron 3.5 Lightning has the number, $0.06.
Directional only
At a glance
- Coding index
- Gemma 3 12B not benchmarked, Nemotron 3.5 Lightning 22.6 from 2 benchmarks.
- Widest category
- General, 52.0 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Gemma 3 12B 8.3% against Nemotron 3.5 Lightning 60.3%, 52.0 points apart on a 0 to 100 scale.
- Output price
- Gemma 3 12B $0.1625 against Nemotron 3.5 Lightning $0.147 per million output tokens, 1.1x apart.
- Context window
- Gemma 3 12B takes 131K tokens, Nemotron 3.5 Lightning 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.
| Category | Gemma 3 12B | Bars | Nemotron 3.5 Lightning | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 7 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | Gemma 3 12B | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| AA Coding Index | 5.8 | 26.8 | Nemotron 3.5 Lightning |
| SWE-bench Verified (Vals AI) | Not measured | 52.8% | Only Nemotron 3.5 Lightning measured |
| Vibe Code Bench (Vals AI) | Not measured | 0.0% | Only Nemotron 3.5 Lightning measured |
| Code migration (Vals AI) | Not measured | 3.0% | Only Nemotron 3.5 Lightning measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Nemotron 3.5 Lightning measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 10.9% | Only Nemotron 3.5 Lightning measured |
| CyberBench (Vals AI) | Not measured | 29.5% | Only Nemotron 3.5 Lightning measured |
| LiveCodeBench (Artificial Analysis run) | 13.7% | Not measured | Only Gemma 3 12B measured |
| SciCode | 16.4% | 32.1% | Nemotron 3.5 Lightning |
| Terminal-Bench Hard (Artificial Analysis run) | 0.8% | Not measured | Only Gemma 3 12B measured |
| ALE-Bench | Not measured | 769.2 | Only Nemotron 3.5 Lightning measured |
| LMArena Text: coding | 1281 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: software and IT | 1313 | Not measured | Only Gemma 3 12B measured |
| SciCode | 0.0% | Not measured | Only Gemma 3 12B measured |
| Neither model has a result on the other 25 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 3 12B | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| AA Intelligence Index | 3.8 | 12.9 | Nemotron 3.5 Lightning |
| Epoch Capabilities Index | 123.5 | Not measured | Only Gemma 3 12B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 3 12B | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| AA Agentic Index | 0.1 | 3.5 | Nemotron 3.5 Lightning |
| Finance Agent (Vals AI) | Not measured | 18.5% | Only Nemotron 3.5 Lightning measured |
| Tax Agent Bench (Vals AI) | Not measured | 2.6% | Only Nemotron 3.5 Lightning measured |
| Legal Research Bench (Vals AI) | Not measured | 2.9% | Only Nemotron 3.5 Lightning measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 17.0% | Only Nemotron 3.5 Lightning measured |
| τ²-Bench Telecom | 10.8% | Not measured | Only Gemma 3 12B measured |
| Berkeley Function Calling Leaderboard (BFCL) | 30.4% | Not measured | Only Gemma 3 12B measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemma 3 12B | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 34.9% | 74.3% | Nemotron 3.5 Lightning |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | 10.6% | Nemotron 3.5 Lightning |
| GPQA Diamond (Epoch AI run) | 39.5% | Not measured | Only Gemma 3 12B measured |
| LMArena Text: hard prompts | 1309 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: expert | 1248 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: hard prompts in English | 1318 | Not measured | Only Gemma 3 12B measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Gemma 3 12B | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| AA Math Index | 18.3 | Not measured | Only Gemma 3 12B measured |
| AIME 2025 (Artificial Analysis run) | 18.3% | Not measured | Only Gemma 3 12B measured |
| OTIS Mock AIME | 16.7% | Not measured | Only Gemma 3 12B measured |
| LMArena Text: math | 1307 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: mathematical work | 1336 | Not measured | Only Gemma 3 12B measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Gemma 3 12B | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| CorpFin (Vals AI) | Not measured | 54.2% | Only Nemotron 3.5 Lightning measured |
| MMLU Pro (Artificial Analysis run) | 59.5% | Not measured | Only Gemma 3 12B measured |
| LMArena Text: science | 1366 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: medicine and healthcare | 1334 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: legal and government | 1381 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: business and finance | 1376 | Not measured | Only Gemma 3 12B measured |
| Neither model has a result on the other 12 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 3 12B | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 3 12B | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | Not measured | 4.3% | Only Nemotron 3.5 Lightning measured |
| IFBench | 36.7% | Not measured | Only Gemma 3 12B measured |
| Long context reasoning (AA-LCR) | 8.3% | 60.3% | Nemotron 3.5 Lightning |
| DTBench | 48.8% | Not measured | Only Gemma 3 12B measured |
| LMCA | 4.5% | Not measured | Only Gemma 3 12B measured |
| LMArena Text | 1334 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: instruction following | 1299 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: creative writing | 1331 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: English | 1349 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: non-English | 1318 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: German | 1370 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: Russian | 1335 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: multi-turn | 1334 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: longer queries | 1317 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: writing and language | 1307 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: entertainment and media | 1297 | Not measured | Only Gemma 3 12B measured |
| Neither model has a result on the other 30 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 3 12B | Nemotron 3.5 Lightning | 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 Lightning costs less
Repository review
50K input + 3K output tokens
Nemotron 3.5 Lightning costs less
Agent loop
200K input + 10K output tokens
Nemotron 3.5 Lightning 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 3 12B | NVIDIA Nemotron 3.5 Lightning |
|---|---|---|
| Maker | NVIDIA | |
| Weights | Open weights | Open weights |
| Released | March 13, 2025 | August 11, 2026 |
| Context window | 131K | 262K |
| Input $/Mtok | $0.075 | $0.0534 |
| Output $/Mtok | $0.1625 | $0.147 |
| Coding index | Not benchmarked | 22.6 |
| Independent measurements behind it | 0 | 2 |
| Cost per solved task | Not computable | $0.06 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 3 12B better than Nemotron 3.5 Lightning for coding?
Only Nemotron 3.5 Lightning has a coding score, 22.6 on the Vibe Coding Index; Gemma 3 12B has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Gemma 3 12B or Nemotron 3.5 Lightning?
Gemma 3 12B costs $0.075 per million input tokens and $0.1625 per million output tokens; Nemotron 3.5 Lightning costs $0.0534 and $0.147. Cost per solved task is known for Nemotron 3.5 Lightning only.
Which has the bigger context window, Gemma 3 12B or Nemotron 3.5 Lightning?
Nemotron 3.5 Lightning, with 262K tokens against 131K.
How many benchmarks is the Gemma 3 12B vs Nemotron 3.5 Lightning comparison based on?
7 benchmarks have a result for both models as of October 22, 2026. Gemma 3 12B's coding index rests on 0 independent benchmarks and Nemotron 3.5 Lightning's on 2. Where only one model has a result, the page says so instead of naming a winner.