GPT-5.1-Codex vs Nemotron 3.5 Lightning
Nemotron 3.5 Lightning leads GPT-5.1-Codex on coding, 22.6 to 15.3 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; 6 benchmarks have a result for both.
GPT-5.1-Codex or Nemotron 3.5 Lightning: which to pick
Pick Nemotron 3.5 Lightning for coding: it scores 22.6 on the Vibe Coding Index against 15.3 for GPT-5.1-Codex.
Pick GPT-5.1-Codex for a larger context window (400K against 262K tokens) and work measured by Vibe Code Bench (Vals AI) or ALE-Bench, where it leads.
- Shared results
- 6
- GPT-5.1-Codex only
- 20
- Nemotron 3.5 Lightning only
- 14
- 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
Nemotron 3.5 Lightning
Nemotron 3.5 Lightning scores 22.6 against 15.3.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
GPT-5.1-Codex
GPT-5.1-Codex leads, 23.7 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-5.1-Codex has a Design Arena: websites result, 1162.
Directional only
Long documents
Listed context window
GPT-5.1-Codex
GPT-5.1-Codex takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nemotron 3.5 Lightning
GPT-5.1-Codex $0.0063, Nemotron 3.5 Lightning $0.0001 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Nemotron 3.5 Lightning
GPT-5.1-Codex $0.892, Nemotron 3.5 Lightning $0.06.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.1-Codex 15.3 from 2 benchmarks, Nemotron 3.5 Lightning 22.6 from 2 benchmarks.
- Widest category
- Coding, 14.5 points apart on average over 2 shared benchmarks.
- Widest single gap
- ALE-Bench: GPT-5.1-Codex 1244.9 against Nemotron 3.5 Lightning 769.2, 15.9 points apart on a 0 to 100 scale.
- Output price
- GPT-5.1-Codex $10.00 against Nemotron 3.5 Lightning $0.147 per million output tokens, 68.0x apart.
- Context window
- GPT-5.1-Codex takes 400K 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-5.1-Codex | Bars | Nemotron 3.5 Lightning | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 6 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | GPT-5.1-Codex | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| SWE-bench Verified | 66.0% | Not measured | Only GPT-5.1-Codex measured |
| LMArena WebDev | 1337 | Not measured | Only GPT-5.1-Codex measured |
| AA Coding Index | Not measured | 26.8 | Only Nemotron 3.5 Lightning measured |
| LiveCodeBench (Vals AI) | 85.5% | Not measured | Only GPT-5.1-Codex measured |
| SWE-bench Verified (Vals AI) | Not measured | 52.8% | Only Nemotron 3.5 Lightning measured |
| Vibe Code Bench (Vals AI) | 13.1% | 0.0% | GPT-5.1-Codex |
| 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) | 84.9% | Not measured | Only GPT-5.1-Codex measured |
| SciCode | Not measured | 32.1% | Only Nemotron 3.5 Lightning measured |
| Terminal-Bench Hard (Artificial Analysis run) | 34.8% | Not measured | Only GPT-5.1-Codex measured |
| Terminal-Bench | 57.8% | Not measured | Only GPT-5.1-Codex measured |
| ALE-Bench | 1244.9 | 769.2 | GPT-5.1-Codex |
| LMArena WebDev: HTML | 1346 | Not measured | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1-Codex | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.7 | 12.9 | GPT-5.1-Codex |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-5.1-Codex | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 3.5 | Only Nemotron 3.5 Lightning measured |
| Design Arena: agents building web apps | 1018 | Not measured | Only GPT-5.1-Codex measured |
| Design Arena: agents building full-stack apps | 1086 | Not measured | Only GPT-5.1-Codex measured |
| Design Arena: agents building mobile apps | 1191 | Not measured | Only GPT-5.1-Codex measured |
| 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 | 83.0% | Not measured | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 32 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.1-Codex | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 86.0% | 74.3% | GPT-5.1-Codex |
| Humanity's Last Exam (Artificial Analysis run) | 25.7% | 10.6% | GPT-5.1-Codex |
| Neither model has a result on the other 20 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.1-Codex | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| AA Math Index | 95.7 | Not measured | Only GPT-5.1-Codex measured |
| AIME 2025 (Artificial Analysis run) | 95.7% | Not measured | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.1-Codex | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| CorpFin (Vals AI) | Not measured | 54.2% | Only Nemotron 3.5 Lightning measured |
| MMLU Pro (Artificial Analysis run) | 86.0% | Not measured | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 16 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | GPT-5.1-Codex | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| Design Arena: websites | 1162 | Not measured | Only GPT-5.1-Codex measured |
| Design Arena: UI components | 1237 | Not measured | Only GPT-5.1-Codex measured |
| Design Arena: game dev | 1138 | Not measured | Only GPT-5.1-Codex measured |
| Design Arena: data viz | 1213 | Not measured | Only GPT-5.1-Codex measured |
| Design Arena: all code categories | 1152 | Not measured | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 4 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1-Codex | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | Not measured | 4.3% | Only Nemotron 3.5 Lightning measured |
| IFBench | 70.0% | Not measured | Only GPT-5.1-Codex measured |
| Long context reasoning (AA-LCR) | 69.3% | 60.3% | GPT-5.1-Codex |
| Neither model has a result on the other 43 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.1-Codex | 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-5.1-Codex | NVIDIA Nemotron 3.5 Lightning |
|---|---|---|
| Maker | OpenAI | NVIDIA |
| Weights | No public weights listed | Open weights |
| Released | November 13, 2025 | August 11, 2026 |
| Context window | 400K | 262K |
| Input $/Mtok | $1.25 | $0.0534 |
| Output $/Mtok | $10.00 | $0.147 |
| Coding index | 15.3 | 22.6 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | $0.892 | $0.06 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.1-Codex better than Nemotron 3.5 Lightning for coding?
Pick Nemotron 3.5 Lightning for coding: it scores 22.6 on the Vibe Coding Index against 15.3 for GPT-5.1-Codex. Pick GPT-5.1-Codex for a larger context window (400K against 262K tokens) and work measured by Vibe Code Bench (Vals AI) or ALE-Bench, where it leads.
Which is cheaper, GPT-5.1-Codex or Nemotron 3.5 Lightning?
GPT-5.1-Codex costs $1.25 per million input tokens and $10.00 per million output tokens; Nemotron 3.5 Lightning costs $0.0534 and $0.147. Per solved SWE-bench Verified task, GPT-5.1-Codex costs $0.892 and Nemotron 3.5 Lightning $0.06.
Which has the bigger context window, GPT-5.1-Codex or Nemotron 3.5 Lightning?
GPT-5.1-Codex, with 400K tokens against 262K.
How many benchmarks is the GPT-5.1-Codex vs Nemotron 3.5 Lightning comparison based on?
6 benchmarks have a result for both models as of October 21, 2026. GPT-5.1-Codex's coding index rests on 2 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.