GPT-4o-mini (2024-07-18) vs Nemotron 3 Super
Nemotron 3 Super costs 1.3x less per output token than GPT-4o-mini (2024-07-18) ($0.45 vs $0.60 per million). Updated October 23, 2026; 27 benchmarks have a result for both.
GPT-4o-mini (2024-07-18) or Nemotron 3 Super: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-4o-mini (2024-07-18) for work measured by WeirdML or LMArena Text: coding, where it leads.
- Shared results
- 27
- GPT-4o-mini (2024-07-18) only
- 19
- Nemotron 3 Super only
- 12
- 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
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Nemotron 3 Super has a AA Intelligence Index result, 12.8.
Directional only
Agentic work
AA Agentic Index
No call
Only Nemotron 3 Super has a AA Agentic Index result, 1.7.
Directional only
Long documents
Listed context window
Nemotron 3 Super
Nemotron 3 Super takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nemotron 3 Super
GPT-4o-mini (2024-07-18) $0.0004, Nemotron 3 Super $0.0003 per turn.
List prices
At a glance
- Coding index
- GPT-4o-mini (2024-07-18) not benchmarked, Nemotron 3 Super not benchmarked.
- Widest category
- Reasoning, 22.3 points apart on average over 3 shared benchmarks.
- Widest single gap
- LMArena Text: Chinese: GPT-4o-mini (2024-07-18) 1265 against Nemotron 3 Super 1432, 27.8 points apart on a 0 to 100 scale.
- Output price
- GPT-4o-mini (2024-07-18) $0.60 against Nemotron 3 Super $0.45 per million output tokens, 1.3x apart.
- Context window
- GPT-4o-mini (2024-07-18) takes 128K tokens, Nemotron 3 Super 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-4o-mini (2024-07-18) | Bars | Nemotron 3 Super | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 15 | ||
| All shared boards | 0 | 27 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | GPT-4o-mini (2024-07-18) | Nemotron 3 Super | Leader |
|---|---|---|---|
| Aider polyglot | 3.6% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| AA Coding Index | Not measured | 37.7 | Only Nemotron 3 Super measured |
| SciCode | Not measured | 36.2% | Only Nemotron 3 Super measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 28.8% | Only Nemotron 3 Super measured |
| WeirdML | 11.8% | 38.0% | Nemotron 3 Super |
| ALE-Bench | Not measured | 213.9 | Only Nemotron 3 Super measured |
| LMArena Text: coding | 1289 | 1404 | Nemotron 3 Super |
| LMArena Text: software and IT | 1291 | 1409 | Nemotron 3 Super |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-4o-mini (2024-07-18) | Nemotron 3 Super | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 12.8 | Only Nemotron 3 Super measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GPT-4o-mini (2024-07-18) | Nemotron 3 Super | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.7 | Only Nemotron 3 Super measured |
| τ²-Bench Telecom | Not measured | 67.8% | Only Nemotron 3 Super measured |
| BALROG | 17.4% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | GPT-4o-mini (2024-07-18) | Nemotron 3 Super | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 80.0% | Only Nemotron 3 Super measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 20.8% | Only Nemotron 3 Super measured |
| GPQA Diamond (Epoch AI run) | 37.7% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| SimpleBench | 10.7% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Chess puzzles | 3.0% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Mystery game puzzles | 12.0% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| VPCT | 34.0% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: hard prompts | 1267 | 1386 | Nemotron 3 Super |
| LMArena Text: expert | 1235 | 1398 | Nemotron 3 Super |
| LMArena Text: hard prompts in English | 1278 | 1397 | Nemotron 3 Super |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4o-mini (2024-07-18) | Nemotron 3 Super | Leader |
|---|---|---|---|
| OTIS Mock AIME | 6.9% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| FrontierMath, tiers 1 to 3 | 0.7% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| MATH level 5 | 52.6% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: math | 1267 | 1380 | Nemotron 3 Super |
| LMArena Text: mathematical work | 1271 | 1405 | Nemotron 3 Super |
| MathArena | Not measured | 16.6% | Only Nemotron 3 Super measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-4o-mini (2024-07-18) | Nemotron 3 Super | Leader |
|---|---|---|---|
| SimpleQA Verified | 8.3% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| MMLU | 76.7% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| GeoBench | 64.0% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: science | 1286 | 1388 | Nemotron 3 Super |
| LMArena Text: medicine and healthcare | 1282 | 1383 | Nemotron 3 Super |
| LMArena Text: legal and government | 1305 | 1392 | Nemotron 3 Super |
| LMArena Text: business and finance | 1265 | 1364 | Nemotron 3 Super |
| Neither model has a result on the other 13 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o-mini (2024-07-18) | Nemotron 3 Super | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index015
| Benchmark | GPT-4o-mini (2024-07-18) | Nemotron 3 Super | Leader |
|---|---|---|---|
| IFBench | Not measured | 71.5% | Only Nemotron 3 Super measured |
| Long context reasoning (AA-LCR) | Not measured | 65.7% | Only Nemotron 3 Super measured |
| Creative writing (Lech Mazur) | 67.2% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text | 1286 | 1378 | Nemotron 3 Super |
| LMArena Text: instruction following | 1258 | 1347 | Nemotron 3 Super |
| LMArena Text: creative writing | 1268 | 1317 | Nemotron 3 Super |
| LMArena Vision | 1066 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: English | 1301 | 1400 | Nemotron 3 Super |
| LMArena Text: non-English | 1266 | 1356 | Nemotron 3 Super |
| LMArena Text: Chinese | 1265 | 1432 | Nemotron 3 Super |
| LMArena Text: German | 1272 | 1341 | Nemotron 3 Super |
| LMArena Text: Japanese | 1216 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Korean | 1195 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: French | 1297 | 1403 | Nemotron 3 Super |
| LMArena Text: Spanish | 1276 | 1418 | Nemotron 3 Super |
| LMArena Text: Russian | 1275 | 1336 | Nemotron 3 Super |
| LMArena Text: Polish | 1244 | 1346 | Nemotron 3 Super |
| LMArena Text: multi-turn | 1285 | 1369 | Nemotron 3 Super |
| LMArena Text: longer queries | 1289 | 1362 | Nemotron 3 Super |
| LMArena Text: writing and language | 1282 | 1331 | Nemotron 3 Super |
| LMArena Text: entertainment and media | 1253 | 1336 | Nemotron 3 Super |
| LMArena Vision: English | 1072 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Vision: Chinese | 1033 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Neither model has a result on the other 25 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o-mini (2024-07-18) | Nemotron 3 Super | 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 Super costs less
Repository review
50K input + 3K output tokens
Nemotron 3 Super costs less
Agent loop
200K input + 10K output tokens
Nemotron 3 Super 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-4o-mini (2024-07-18) | NVIDIA Nemotron 3 Super |
|---|---|---|
| Maker | OpenAI | NVIDIA |
| Weights | No public weights listed | Open weights |
| Released | July 18, 2024 | March 11, 2026 |
| Context window | 128K | 262K |
| Input $/Mtok | $0.15 | $0.085 |
| Output $/Mtok | $0.60 | $0.45 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4o-mini (2024-07-18) better than Nemotron 3 Super for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4o-mini (2024-07-18) for work measured by WeirdML or LMArena Text: coding, where it leads.
Which is cheaper, GPT-4o-mini (2024-07-18) or Nemotron 3 Super?
GPT-4o-mini (2024-07-18) costs $0.15 per million input tokens and $0.60 per million output tokens; Nemotron 3 Super costs $0.085 and $0.45. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4o-mini (2024-07-18) or Nemotron 3 Super?
Nemotron 3 Super, with 262K tokens against 128K.
How many benchmarks is the GPT-4o-mini (2024-07-18) vs Nemotron 3 Super comparison based on?
27 benchmarks have a result for both models as of October 23, 2026. GPT-4o-mini (2024-07-18)'s coding index rests on 0 independent benchmarks and Nemotron 3 Super's on 0. Where only one model has a result, the page says so instead of naming a winner.