Nemotron 3.5 Lightning vs Qwen3 Coder 30B A3B Instruct
Nemotron 3.5 Lightning leads Qwen3 Coder 30B A3B Instruct on the Artificial Analysis Intelligence Index, 12.9 to 9.6, and Nemotron 3.5 Lightning costs 3.0x less per output token ($0.147 vs $0.44 per million). Updated October 21, 2026; 4 benchmarks have a result for both.
Nemotron 3.5 Lightning or Qwen3 Coder 30B A3B Instruct: which to pick
Only Nemotron 3.5 Lightning has a coding score, 22.6 on the Vibe Coding Index; Qwen3 Coder 30B A3B Instruct has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 4
- Nemotron 3.5 Lightning only
- 16
- Qwen3 Coder 30B A3B Instruct only
- 12
- Like-for-like categories
- 3 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 9.6.
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 Coder 30B A3B Instruct has a Design Arena: websites result, 1087.
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 Coder 30B A3B Instruct $0.0003 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 Coder 30B A3B Instruct not benchmarked.
- Widest category
- General, 27.7 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Nemotron 3.5 Lightning 60.3% against Qwen3 Coder 30B A3B Instruct 32.7%, 27.7 points apart on a 0 to 100 scale.
- Output price
- Nemotron 3.5 Lightning $0.147 against Qwen3 Coder 30B A3B Instruct $0.44 per million output tokens, 3.0x 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 Coder 30B A3B Instruct | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 4 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index13 boards, none shared
| Benchmark | Nemotron 3.5 Lightning | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 60.4% | Only Qwen3 Coder 30B A3B Instruct measured |
| SWE-bench Lite | Not measured | 49.7% | Only Qwen3 Coder 30B A3B Instruct measured |
| 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 | 40.3% | Only Qwen3 Coder 30B A3B Instruct measured |
| SciCode | 32.1% | Not measured | Only Nemotron 3.5 Lightning measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 15.2% | Only Qwen3 Coder 30B A3B Instruct measured |
| ALE-Bench | 769.2 | Not measured | Only Nemotron 3.5 Lightning measured |
| Neither model has a result on the other 26 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Nemotron 3.5 Lightning | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.9 | 9.6 | 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 index6 boards, none shared
| Benchmark | Nemotron 3.5 Lightning | Qwen3 Coder 30B A3B Instruct | 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 | 34.5% | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Nemotron 3.5 Lightning | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 74.3% | 51.6% | Nemotron 3.5 Lightning |
| Humanity's Last Exam (Artificial Analysis run) | 10.6% | 3.8% | Nemotron 3.5 Lightning |
| 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 | Nemotron 3.5 Lightning | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 29.0 | Only Qwen3 Coder 30B A3B Instruct measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 29.0% | Only Qwen3 Coder 30B A3B Instruct 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 | Nemotron 3.5 Lightning | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| CorpFin (Vals AI) | 54.2% | Not measured | Only Nemotron 3.5 Lightning measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 70.6% | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 16 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Nemotron 3.5 Lightning | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1087 | Only Qwen3 Coder 30B A3B Instruct measured |
| Design Arena: UI components | Not measured | 1046 | Only Qwen3 Coder 30B A3B Instruct measured |
| Design Arena: data viz | Not measured | 1085 | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 6 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Nemotron 3.5 Lightning | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | 4.3% | Not measured | Only Nemotron 3.5 Lightning measured |
| IFBench | Not measured | 32.7% | Only Qwen3 Coder 30B A3B Instruct measured |
| Long context reasoning (AA-LCR) | 60.3% | 32.7% | Nemotron 3.5 Lightning |
| 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 Coder 30B A3B Instruct | 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 Coder 30B A3B Instruct |
|---|---|---|
| Maker | NVIDIA | Qwen |
| Weights | Open weights | Open weights |
| Released | August 11, 2026 | July 31, 2025 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.0534 | $0.11 |
| Output $/Mtok | $0.147 | $0.44 |
| 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 Coder 30B A3B Instruct for coding?
Only Nemotron 3.5 Lightning has a coding score, 22.6 on the Vibe Coding Index; Qwen3 Coder 30B A3B Instruct has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Nemotron 3.5 Lightning or Qwen3 Coder 30B A3B Instruct?
Nemotron 3.5 Lightning costs $0.0534 per million input tokens and $0.147 per million output tokens; Qwen3 Coder 30B A3B Instruct costs $0.11 and $0.44. Cost per solved task is known for Nemotron 3.5 Lightning only.
Which has the bigger context window, Nemotron 3.5 Lightning or Qwen3 Coder 30B A3B Instruct?
Neither: both take 262K tokens.
How many benchmarks is the Nemotron 3.5 Lightning vs Qwen3 Coder 30B A3B Instruct comparison based on?
4 benchmarks have a result for both models as of October 21, 2026. Nemotron 3.5 Lightning's coding index rests on 2 independent benchmarks and Qwen3 Coder 30B A3B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.