Mercury 2.5 vs Nemotron 3.5 Lightning
Nemotron 3.5 Lightning leads Mercury 2.5 on coding, 22.6 to 1.6 on the Vibe Coding Index, at about the same output price ($0.147 vs $0.15 per million). Updated October 22, 2026; 14 benchmarks have a result for both.
Mercury 2.5 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 1.6 for Mercury 2.5.
Pick Mercury 2.5 for work measured by Vibe Code Bench (Vals AI) or Code migration (Vals AI), where it leads.
- Shared results
- 14
- Mercury 2.5 only
- 8
- Nemotron 3.5 Lightning only
- 6
- 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
Nemotron 3.5 Lightning
Nemotron 3.5 Lightning scores 22.6 against 1.6.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
Nemotron 3.5 Lightning
Nemotron 3.5 Lightning leads, 12.9 against 12.3.
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
Long documents
Listed context window
Nemotron 3.5 Lightning
Nemotron 3.5 Lightning takes 262K tokens against 260K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2.5
Mercury 2.5 $0.0001, 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
- Mercury 2.5 1.6 from 2 benchmarks, Nemotron 3.5 Lightning 22.6 from 2 benchmarks.
- Widest category
- General, 31.1 points apart on average over 2 shared benchmarks.
- Widest single gap
- MedScribe (Vals AI): Mercury 2.5 55.1% against Nemotron 3.5 Lightning 4.3%, 50.8 points apart on a 0 to 100 scale.
- Output price
- Mercury 2.5 $0.15 against Nemotron 3.5 Lightning $0.147 per million output tokens, 1.0x apart.
- Context window
- Mercury 2.5 takes 260K 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 | Mercury 2.5 | Bars | Nemotron 3.5 Lightning | Ties |
|---|---|---|---|---|
| Coding | 5 | 1 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 2 | 2 | ||
| Reasoning | 1 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 10 | 4 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index51
| Benchmark | Mercury 2.5 | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| 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) | 0.0% | Not measured | Only Mercury 2.5 measured |
| Vibe Code Bench (Vals AI) | 3.7% | 0.0% | Mercury 2.5 |
| Code migration (Vals AI) | 4.5% | 3.0% | Mercury 2.5 |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Nemotron 3.5 Lightning measured |
| IOI (Vals AI) | 2.4% | Not measured | Only Mercury 2.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 34.5% | 10.9% | Mercury 2.5 |
| SkillsBench (Vals AI) | 18.1% | Not measured | Only Mercury 2.5 measured |
| CyberBench (Vals AI) | 45.5% | 29.5% | Mercury 2.5 |
| SciCode | 38.5% | 32.1% | Mercury 2.5 |
| ALE-Bench | 301.6 | 769.2 | Nemotron 3.5 Lightning |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mercury 2.5 | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.3 | 12.9 | Nemotron 3.5 Lightning |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | Mercury 2.5 | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 3.5 | Only Nemotron 3.5 Lightning measured |
| Finance Agent (Vals AI) | 18.9% | 18.5% | Mercury 2.5 |
| Tax Agent Bench (Vals AI) | 2.5% | 2.6% | Nemotron 3.5 Lightning |
| Legal Research Bench (Vals AI) | 4.3% | 2.9% | Mercury 2.5 |
| Excel Modeling Benchmark (Vals AI) | 8.8% | 17.0% | Nemotron 3.5 Lightning |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only Mercury 2.5 measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mercury 2.5 | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 74.3% | Only Nemotron 3.5 Lightning measured |
| Humanity's Last Exam (Artificial Analysis run) | 11.8% | 10.6% | Mercury 2.5 |
| Neither model has a result on the other 20 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Mercury 2.5 | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| ProofBench | 3.0% | Not measured | Only Mercury 2.5 measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Mercury 2.5 | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 83.1% | Not measured | Only Mercury 2.5 measured |
| CorpFin (Vals AI) | Not measured | 54.2% | Only Nemotron 3.5 Lightning measured |
| MedCode (Vals AI) | 31.3% | Not measured | Only Mercury 2.5 measured |
| Neither model has a result on the other 15 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mercury 2.5 | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Mercury 2.5 | Nemotron 3.5 Lightning | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 45.3% | Not measured | Only Mercury 2.5 measured |
| MedScribe (Vals AI) | 55.1% | 4.3% | Mercury 2.5 |
| Long context reasoning (AA-LCR) | 71.7% | 60.3% | Mercury 2.5 |
| 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 | Mercury 2.5 | 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
Mercury 2.5 costs less
Repository review
50K input + 3K output tokens
Mercury 2.5 costs less
Agent loop
200K input + 10K output tokens
Mercury 2.5 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 | Inception Mercury 2.5 | NVIDIA Nemotron 3.5 Lightning |
|---|---|---|
| Maker | Inception | NVIDIA |
| Weights | No public weights listed | Open weights |
| Released | September 8, 2026 | August 11, 2026 |
| Context window | 260K | 262K |
| Input $/Mtok | $0.04 | $0.0534 |
| Output $/Mtok | $0.15 | $0.147 |
| Coding index | 1.6 | 22.6 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | Not computable | $0.06 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mercury 2.5 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 1.6 for Mercury 2.5. Pick Mercury 2.5 for work measured by Vibe Code Bench (Vals AI) or Code migration (Vals AI), where it leads.
Which is cheaper, Mercury 2.5 or Nemotron 3.5 Lightning?
Mercury 2.5 costs $0.04 per million input tokens and $0.15 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, Mercury 2.5 or Nemotron 3.5 Lightning?
Nemotron 3.5 Lightning, with 262K tokens against 260K.
How many benchmarks is the Mercury 2.5 vs Nemotron 3.5 Lightning comparison based on?
14 benchmarks have a result for both models as of October 22, 2026. Mercury 2.5'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.