Gemma 2 27B vs Nemotron 3.5 Super VL
Nemotron 3.5 Super VL costs 1.3x less per output token than Gemma 2 27B ($0.50 vs $0.65 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.65
- Coding
- No data
- Overall
- 35.6
- Output $/M
- $0.50
Gemma 2 27B or Nemotron 3.5 Super VL: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. Gemma 2 27B has results on LMArena Text: coding, LMArena Text: software and IT and Epoch Capabilities Index; Nemotron 3.5 Super VL on LiveBench coding, SciCode and AA Intelligence Index. Compare them on price and context instead.
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
No call
Only Nemotron 3.5 Super VL has a AA Intelligence Index result, 26.5.
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 8K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nemotron 3.5 Super VL
Gemma 2 27B $0.0010, Nemotron 3.5 Super VL $0.0004 per turn.
List prices
At a glance
- Coding index
- Gemma 2 27B not benchmarked, Nemotron 3.5 Super VL not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- Gemma 2 27B $0.65 against Nemotron 3.5 Super VL $0.50 per million output tokens, 1.3x apart.
- Context window
- Gemma 2 27B takes 8K tokens, Nemotron 3.5 Super VL 1.05M.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards measured
| Benchmark | Gemma 2 27B | 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 |
| LMArena Text: coding | 1211 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: software and IT | 1228 | Not measured | Only Gemma 2 27B measured |
| Neither model has a result on the other 39 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Gemma 2 27B | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 26.5 | Only Nemotron 3.5 Super VL measured |
| Epoch Capabilities Index | 122.1 | Not measured | Only Gemma 2 27B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Gemma 2 27B | 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 |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Gemma 2 27B | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 78.8% | Only Nemotron 3.5 Super VL measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 30.7% | Only Nemotron 3.5 Super VL measured |
| GPQA Diamond (Epoch AI run) | 36.5% | Not measured | Only Gemma 2 27B measured |
| LMArena Text: hard prompts | 1198 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: expert | 1171 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: hard prompts in English | 1206 | Not measured | Only Gemma 2 27B measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Gemma 2 27B | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| OTIS Mock AIME | 1.4% | Not measured | Only Gemma 2 27B measured |
| MATH level 5 | 27.9% | Not measured | Only Gemma 2 27B measured |
| LMArena Text: math | 1212 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: mathematical work | 1221 | Not measured | Only Gemma 2 27B measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Gemma 2 27B | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 68.0% | Not measured | Only Gemma 2 27B measured |
| MMLU | 75.7% | Not measured | Only Gemma 2 27B measured |
| LMArena Text: science | 1228 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: medicine and healthcare | 1198 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: legal and government | 1241 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: business and finance | 1208 | Not measured | Only Gemma 2 27B measured |
| Neither model has a result on the other 14 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Gemma 2 27B | 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 | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index21 boards measured
| Benchmark | Gemma 2 27B | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 64.6% | Only Nemotron 3.5 Super VL measured |
| Long context reasoning (AA-LCR) | Not measured | 69.0% | Only Nemotron 3.5 Super VL measured |
| DTBench | 48.0% | Not measured | Only Gemma 2 27B measured |
| LMCA | 7.1% | Not measured | Only Gemma 2 27B measured |
| LMArena Text | 1231 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: instruction following | 1206 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: creative writing | 1240 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: English | 1242 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: non-English | 1217 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: Chinese | 1221 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: German | 1209 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: Japanese | 1175 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: Korean | 1174 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: French | 1248 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: Spanish | 1228 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: Russian | 1234 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: Polish | 1277 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: multi-turn | 1224 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: longer queries | 1230 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: writing and language | 1249 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: entertainment and media | 1212 | Not measured | Only Gemma 2 27B measured |
| Neither model has a result on the other 27 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 2 27B | NVIDIA Nemotron 3.5 Super VL |
|---|---|---|
| Maker | NVIDIA | |
| Weights | Open weights | Open weights |
| Released | July 13, 2024 | October 15, 2026 |
| Context window | 8K | 1.05M |
| Input $/Mtok | $0.65 | $0.15 |
| Output $/Mtok | $0.65 | $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 Gemma 2 27B better than Nemotron 3.5 Super VL for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Gemma 2 27B or Nemotron 3.5 Super VL?
Gemma 2 27B costs $0.65 per million input tokens and $0.65 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 2 27B or Nemotron 3.5 Super VL?
Nemotron 3.5 Super VL, with 1.05M tokens against 8K.
Has any benchmark tested both Gemma 2 27B and Nemotron 3.5 Super VL?
No benchmark has tested both yet. Gemma 2 27B has results on LMArena Text: coding, LMArena Text: software and IT and Epoch Capabilities Index; Nemotron 3.5 Super VL on LiveBench coding, SciCode and AA Intelligence Index. Compare them on price and context instead. Data as of October 22, 2026.