GPT-6 Sol vs Nemotron 3.5 Lightning
GPT-6 Sol leads Nemotron 3.5 Lightning on coding, 76.0 to 22.6 on the Vibe Coding Index, and Nemotron 3.5 Lightning costs 68.0x less per output token ($0.147 vs $10.00 per million). Updated October 21, 2026; 15 benchmarks have a result for both.
GPT-6 Sol or Nemotron 3.5 Lightning: which to pick
Pick GPT-6 Sol for coding: it scores 76.0 on the Vibe Coding Index against 22.6 for Nemotron 3.5 Lightning.
Pick Nemotron 3.5 Lightning for output tokens 68.0x cheaper ($0.147 vs $10.00 per million).
- Shared results
- 15
- GPT-6 Sol only
- 86
- Nemotron 3.5 Lightning only
- 5
- 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
GPT-6 Sol
GPT-6 Sol scores 76.0 against 22.6.
5 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-6 Sol
GPT-6 Sol leads, 47.6 against 12.9.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Nemotron 3.5 Lightning has a AA Agentic Index result, 3.5.
Directional only
Web design
Design Arena: websites
No call
Only GPT-6 Sol has a Design Arena: websites result, 1292.
Directional only
Long documents
Listed context window
GPT-6 Sol
GPT-6 Sol takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nemotron 3.5 Lightning
GPT-6 Sol $0.0070, 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
- GPT-6 Sol 76.0 from 5 benchmarks, Nemotron 3.5 Lightning 22.6 from 2 benchmarks.
- Widest category
- General, 50.5 points apart on average over 2 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): GPT-6 Sol 87.8% against Nemotron 3.5 Lightning 0.0%, 87.8 points apart on a 0 to 100 scale.
- Output price
- GPT-6 Sol $10.00 against Nemotron 3.5 Lightning $0.147 per million output tokens, 68.0x apart.
- Context window
- GPT-6 Sol takes 1.05M 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 | GPT-6 Sol | Bars | Nemotron 3.5 Lightning | Ties |
|---|---|---|---|---|
| Coding | 7 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 4 | 0 | ||
| Reasoning | 1 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 15 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
| Benchmark | GPT-6 Sol | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| LiveBench coding | 93.1% | Not measured | Only GPT-6 Sol measured |
| LMArena WebDev | 1683 | Not measured | Only GPT-6 Sol measured |
| AA Coding Index | Not measured | 26.8 | Only Nemotron 3.5 Lightning measured |
| SWE-bench Verified (Vals AI) | Not measured | 52.8% | Only Nemotron 3.5 Lightning measured |
| Terminal-Bench 4 (Vals AI) | 44.4% | Not measured | Only GPT-6 Sol measured |
| Vibe Code Bench (Vals AI) | 87.8% | 0.0% | GPT-6 Sol |
| Code migration (Vals AI) | 57.2% | 3.0% | GPT-6 Sol |
| ProgramBench (Vals AI) | 2.0% | 0.0% | GPT-6 Sol |
| IOI (Vals AI) | 82.6% | Not measured | Only GPT-6 Sol measured |
| Terminal-Bench 2.1 (Vals AI) | 83.2% | 10.9% | GPT-6 Sol |
| CyberBench (Vals AI) | 78.0% | 29.5% | GPT-6 Sol |
| SciCode | 57.6% | 32.1% | GPT-6 Sol |
| FrontierCode | 49.3% | Not measured | Only GPT-6 Sol measured |
| ALE-Bench | 2462.0 | 769.2 | GPT-6 Sol |
| LMArena Text: coding | 1448 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: software and IT | 1433 | Not measured | Only GPT-6 Sol measured |
| LMArena WebDev: React | 1685 | Not measured | Only GPT-6 Sol measured |
| LMArena WebDev: HTML | 1685 | Not measured | Only GPT-6 Sol measured |
| LMArena WebDev: from an image | 1660 | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6 Sol | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| AA Intelligence Index | 47.6 | 12.9 | GPT-6 Sol |
| Epoch Capabilities Index | 163.7 | Not measured | Only GPT-6 Sol measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GPT-6 Sol | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 3.5 | Only Nemotron 3.5 Lightning measured |
| Design Arena: agents building web apps | 1231 | Not measured | Only GPT-6 Sol measured |
| Design Arena: agents building full-stack apps | 1238 | Not measured | Only GPT-6 Sol measured |
| Design Arena: agents building mobile apps | 1214 | Not measured | Only GPT-6 Sol measured |
| LiveBench research | 69.3% | Not measured | Only GPT-6 Sol measured |
| LiveBench browser | 92.0% | Not measured | Only GPT-6 Sol measured |
| LiveBench long agentic | 66.9% | Not measured | Only GPT-6 Sol measured |
| SREBench (Vals AI) | 30.5% | Not measured | Only GPT-6 Sol measured |
| Finance Agent (Vals AI) | 49.0% | 18.5% | GPT-6 Sol |
| Tax Agent Bench (Vals AI) | 15.0% | 2.6% | GPT-6 Sol |
| Legal Research Bench (Vals AI) | 28.9% | 2.9% | GPT-6 Sol |
| Excel Modeling Benchmark (Vals AI) | 71.5% | 17.0% | GPT-6 Sol |
| BioMysteryBench (Vals AI) | 74.8% | Not measured | Only GPT-6 Sol measured |
| Terminal-Bench-Science (Vals AI) | 30.0% | Not measured | Only GPT-6 Sol measured |
| Vals Science Index | 45.0% | Not measured | Only GPT-6 Sol measured |
| APEX-Agents | 54.3% | Not measured | Only GPT-6 Sol measured |
| SpireClimb | 7.5% | Not measured | Only GPT-6 Sol measured |
| Vending-Bench 2 | $14,428 | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 23 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6 Sol | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| LiveBench reasoning | 88.7% | Not measured | Only GPT-6 Sol measured |
| MysteryMechanism (Vals AI) | 30.2% | Not measured | Only GPT-6 Sol measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 74.3% | Only Nemotron 3.5 Lightning measured |
| Humanity's Last Exam (Artificial Analysis run) | 47.9% | 10.6% | GPT-6 Sol |
| GPQA Diamond (Epoch AI run) | 94.3% | Not measured | Only GPT-6 Sol measured |
| ARC-AGI | 95.5% | Not measured | Only GPT-6 Sol measured |
| ARC-AGI-2 | 89.6% | Not measured | Only GPT-6 Sol measured |
| Chess puzzles | 56.0% | Not measured | Only GPT-6 Sol measured |
| Mystery game puzzles | 56.0% | Not measured | Only GPT-6 Sol measured |
| EBR-bench | 53.3% | Not measured | Only GPT-6 Sol measured |
| LMArena Text: hard prompts | 1422 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: expert | 1437 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: hard prompts in English | 1420 | Not measured | Only GPT-6 Sol measured |
| LMArena Vision: diagrams | 1270 | Not measured | Only GPT-6 Sol measured |
| LMArena Vision: homework | 1286 | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 7 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-6 Sol | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | Not measured | Only GPT-6 Sol measured |
| FrontierMath, tiers 1 to 3 | 89.8% | Not measured | Only GPT-6 Sol measured |
| FrontierMath, tier 4 | 90.0% | Not measured | Only GPT-6 Sol measured |
| ProofBench | 83.0% | Not measured | Only GPT-6 Sol measured |
| LMArena Text: math | 1407 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: mathematical work | 1424 | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-6 Sol | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| CorpFin (Vals AI) | Not measured | 54.2% | Only Nemotron 3.5 Lightning measured |
| MedCode (Vals AI) | 47.1% | Not measured | Only GPT-6 Sol measured |
| SimpleQA Verified | 60.7% | Not measured | Only GPT-6 Sol measured |
| LMArena Text: science | 1389 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: medicine and healthcare | 1366 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: legal and government | 1396 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: business and finance | 1380 | Not measured | Only GPT-6 Sol measured |
| FACTS Benchmark Suite | 72.5% | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 10 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-6 Sol | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| Design Arena: websites | 1292 | Not measured | Only GPT-6 Sol measured |
| Design Arena: UI components | 1292 | Not measured | Only GPT-6 Sol measured |
| Design Arena: game dev | 1314 | Not measured | Only GPT-6 Sol measured |
| Design Arena: data viz | 1269 | Not measured | Only GPT-6 Sol measured |
| Design Arena: 3D | 1318 | Not measured | Only GPT-6 Sol measured |
| Design Arena: all code categories | 1301 | Not measured | Only GPT-6 Sol measured |
| Design Arena: SVG | 1316 | Not measured | Only GPT-6 Sol measured |
| Design Arena: ASCII art | 1225 | Not measured | Only GPT-6 Sol measured |
| LiveBench design | 82.2% | Not measured | Only GPT-6 Sol measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-6 Sol | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| LiveBench data analysis | 81.2% | Not measured | Only GPT-6 Sol measured |
| Public Benefits Bench (Vals AI) | 56.6% | Not measured | Only GPT-6 Sol measured |
| SAGE (Vals AI) | 44.8% | Not measured | Only GPT-6 Sol measured |
| MedScribe (Vals AI) | 82.0% | 4.3% | GPT-6 Sol |
| Long context reasoning (AA-LCR) | 83.7% | 60.3% | GPT-6 Sol |
| DTBench | 97.3% | Not measured | Only GPT-6 Sol measured |
| LMCA | 59.1% | Not measured | Only GPT-6 Sol measured |
| Furniture assembly | 58.3% | Not measured | Only GPT-6 Sol measured |
| LMArena Text | 1398 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: instruction following | 1413 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: creative writing | 1378 | Not measured | Only GPT-6 Sol measured |
| LMArena Vision | 1240 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: English | 1396 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: non-English | 1388 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: Chinese | 1412 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: German | 1379 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: Japanese | 1377 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: Korean | 1336 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: French | 1399 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: Spanish | 1387 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: Russian | 1402 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: Polish | 1372 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: multi-turn | 1414 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: longer queries | 1416 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: writing and language | 1389 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: entertainment and media | 1373 | Not measured | Only GPT-6 Sol measured |
| LMArena Vision: English | 1229 | Not measured | Only GPT-6 Sol measured |
| LMArena Vision: reading text | 1258 | Not measured | Only GPT-6 Sol measured |
| LMArena Vision: creative writing | 1219 | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-6 Sol | 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 | OpenAI GPT-6 Sol | NVIDIA Nemotron 3.5 Lightning |
|---|---|---|
| Maker | OpenAI | NVIDIA |
| Weights | No public weights listed | Open weights |
| Released | September 22, 2026 | August 11, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $2.00 | $0.0534 |
| Output $/Mtok | $10.00 | $0.147 |
| Coding index | 76.0 | 22.6 |
| Independent measurements behind it | 5 | 2 |
| Cost per solved task | Not computable | $0.06 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6 Sol better than Nemotron 3.5 Lightning for coding?
Pick GPT-6 Sol for coding: it scores 76.0 on the Vibe Coding Index against 22.6 for Nemotron 3.5 Lightning. Pick Nemotron 3.5 Lightning for output tokens 68.0x cheaper ($0.147 vs $10.00 per million).
Which is cheaper, GPT-6 Sol or Nemotron 3.5 Lightning?
GPT-6 Sol costs $2.00 per million input tokens and $10.00 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, GPT-6 Sol or Nemotron 3.5 Lightning?
GPT-6 Sol, with 1.05M tokens against 262K.
How many benchmarks is the GPT-6 Sol vs Nemotron 3.5 Lightning comparison based on?
15 benchmarks have a result for both models as of October 21, 2026. GPT-6 Sol's coding index rests on 5 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.