Nemotron 3.5 Lightning vs Qwen3 235B A22B Instruct 2507
Nemotron 3.5 Lightning leads Qwen3 235B A22B Instruct 2507 on the Artificial Analysis Intelligence Index, 12.9 to 12.0, and Nemotron 3.5 Lightning costs 5.3x less per output token ($0.147 vs $0.775 per million). Updated October 23, 2026; 5 benchmarks have a result for both.
Nemotron 3.5 Lightning or Qwen3 235B A22B Instruct 2507: which to pick
Only Nemotron 3.5 Lightning has a coding score, 22.6 on the Vibe Coding Index; Qwen3 235B A22B Instruct 2507 has none, so the two cannot be ranked on coding.
Pick Qwen3 235B A22B Instruct 2507 for work measured by SciCode or GPQA Diamond (Artificial Analysis run), where it leads.
- Shared results
- 5
- Nemotron 3.5 Lightning only
- 15
- Qwen3 235B A22B Instruct 2507 only
- 19
- 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
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 12.0.
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 Qwen3 235B A22B Instruct 2507 has a Design Arena: websites result, 1058.
Directional only
Long documents
Listed context window
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nemotron 3.5 Lightning
Nemotron 3.5 Lightning $0.0001, Qwen3 235B A22B Instruct 2507 $0.0005 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
- Nemotron 3.5 Lightning 22.6 from 2 benchmarks, Qwen3 235B A22B Instruct 2507 not benchmarked.
- Widest category
- General, 11.7 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Nemotron 3.5 Lightning 60.3% against Qwen3 235B A22B Instruct 2507 72.0%, 11.7 points apart on a 0 to 100 scale.
- Output price
- Nemotron 3.5 Lightning $0.147 against Qwen3 235B A22B Instruct 2507 $0.775 per million output tokens, 5.3x 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 | Nemotron 3.5 Lightning | Bars | Qwen3 235B A22B Instruct 2507 | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 0 | 2 | ||
| General | 0 | 1 | ||
| All shared boards | 1 | 4 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Nemotron 3.5 Lightning | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| AA Coding Index | 26.8 | Not measured | Only Nemotron 3.5 Lightning measured |
| SWE-bench Verified (Vals AI) | 52.8% | Not measured | Only Nemotron 3.5 Lightning measured |
| Vibe Code Bench (Vals AI) | 0.0% | Not measured | Only Nemotron 3.5 Lightning measured |
| Code migration (Vals AI) | 3.0% | Not measured | Only Nemotron 3.5 Lightning measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only Nemotron 3.5 Lightning measured |
| Terminal-Bench 2.1 (Vals AI) | 10.9% | Not measured | Only Nemotron 3.5 Lightning measured |
| CyberBench (Vals AI) | 29.5% | Not measured | Only Nemotron 3.5 Lightning measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 78.8% | Only Qwen3 235B A22B Instruct 2507 measured |
| SciCode | 32.1% | 41.4% | Qwen3 235B A22B Instruct 2507 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 15.2% | Only Qwen3 235B A22B Instruct 2507 measured |
| WeirdML | Not measured | 38.7% | Only Qwen3 235B A22B Instruct 2507 measured |
| ALE-Bench | 769.2 | Not measured | Only Nemotron 3.5 Lightning 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 | Nemotron 3.5 Lightning | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.9 | 12.0 | Nemotron 3.5 Lightning |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Nemotron 3.5 Lightning | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| AA Agentic Index | 3.5 | Not measured | Only Nemotron 3.5 Lightning measured |
| Finance Agent (Vals AI) | 18.5% | Not measured | Only Nemotron 3.5 Lightning measured |
| Tax Agent Bench (Vals AI) | 2.6% | Not measured | Only Nemotron 3.5 Lightning measured |
| Legal Research Bench (Vals AI) | 2.9% | Not measured | Only Nemotron 3.5 Lightning measured |
| Excel Modeling Benchmark (Vals AI) | 17.0% | Not measured | Only Nemotron 3.5 Lightning measured |
| τ²-Bench Telecom | Not measured | 53.2% | Only Qwen3 235B A22B Instruct 2507 measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 52.1% | Only Qwen3 235B A22B Instruct 2507 measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Nemotron 3.5 Lightning | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 74.3% | 79.0% | Qwen3 235B A22B Instruct 2507 |
| Humanity's Last Exam (Artificial Analysis run) | 10.6% | 15.9% | Qwen3 235B A22B Instruct 2507 |
| ARC-AGI | Not measured | 11.0% | Only Qwen3 235B A22B Instruct 2507 measured |
| ARC-AGI-2 | Not measured | 1.3% | Only Qwen3 235B A22B Instruct 2507 measured |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Nemotron 3.5 Lightning | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 91.0 | Only Qwen3 235B A22B Instruct 2507 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 91.0% | Only Qwen3 235B A22B Instruct 2507 measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Nemotron 3.5 Lightning | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| CorpFin (Vals AI) | 54.2% | Not measured | Only Nemotron 3.5 Lightning measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 84.3% | Only Qwen3 235B A22B Instruct 2507 measured |
| Neither model has a result on the other 18 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Nemotron 3.5 Lightning | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1058 | Only Qwen3 235B A22B Instruct 2507 measured |
| Design Arena: UI components | Not measured | 963 | Only Qwen3 235B A22B Instruct 2507 measured |
| Design Arena: game dev | Not measured | 951 | Only Qwen3 235B A22B Instruct 2507 measured |
| Design Arena: data viz | Not measured | 1070 | Only Qwen3 235B A22B Instruct 2507 measured |
| Design Arena: 3D | Not measured | 995 | Only Qwen3 235B A22B Instruct 2507 measured |
| Design Arena: all code categories | Not measured | 1038 | Only Qwen3 235B A22B Instruct 2507 measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nemotron 3.5 Lightning | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | 4.3% | Not measured | Only Nemotron 3.5 Lightning measured |
| IFBench | Not measured | 51.2% | Only Qwen3 235B A22B Instruct 2507 measured |
| Long context reasoning (AA-LCR) | 60.3% | 72.0% | Qwen3 235B A22B Instruct 2507 |
| DTBench | Not measured | 78.4% | Only Qwen3 235B A22B Instruct 2507 measured |
| LMCA | Not measured | 23.5% | Only Qwen3 235B A22B Instruct 2507 measured |
| 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 | Nemotron 3.5 Lightning | Qwen3 235B A22B Instruct 2507 | 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 | NVIDIA Nemotron 3.5 Lightning | Qwen3 235B A22B Instruct 2507 |
|---|---|---|
| Maker | NVIDIA | Qwen |
| Weights | Open weights | Open weights |
| Released | August 11, 2026 | July 21, 2025 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.0534 | $0.145 |
| Output $/Mtok | $0.147 | $0.775 |
| Coding index | 22.6 | Not benchmarked |
| Independent measurements behind it | 2 | 0 |
| Cost per solved task | $0.06 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Nemotron 3.5 Lightning better than Qwen3 235B A22B Instruct 2507 for coding?
Only Nemotron 3.5 Lightning has a coding score, 22.6 on the Vibe Coding Index; Qwen3 235B A22B Instruct 2507 has none, so the two cannot be ranked on coding. Pick Qwen3 235B A22B Instruct 2507 for work measured by SciCode or GPQA Diamond (Artificial Analysis run), where it leads.
Which is cheaper, Nemotron 3.5 Lightning or Qwen3 235B A22B Instruct 2507?
Nemotron 3.5 Lightning costs $0.0534 per million input tokens and $0.147 per million output tokens; Qwen3 235B A22B Instruct 2507 costs $0.145 and $0.775. Cost per solved task is known for Nemotron 3.5 Lightning only.
Which has the bigger context window, Nemotron 3.5 Lightning or Qwen3 235B A22B Instruct 2507?
Neither: both take 262K tokens.
How many benchmarks is the Nemotron 3.5 Lightning vs Qwen3 235B A22B Instruct 2507 comparison based on?
5 benchmarks have a result for both models as of October 23, 2026. Nemotron 3.5 Lightning's coding index rests on 2 independent benchmarks and Qwen3 235B A22B Instruct 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.