Nova Pro 1.0 vs GPT-4o (2024-05-13)
GPT-4o (2024-05-13) leads Nova Pro 1.0 on the Artificial Analysis Intelligence Index, 7.3 to 7.0, and Nova Pro 1.0 costs 4.7x less per output token ($3.20 vs $15.00 per million). Updated October 22, 2026; 35 benchmarks have a result for both.
Nova Pro 1.0 or GPT-4o (2024-05-13): which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Nova Pro 1.0 for output tokens 4.7x cheaper ($3.20 vs $15.00 per million) and a larger context window (300K against 128K tokens).
- Shared results
- 35
- Nova Pro 1.0 only
- 7
- GPT-4o (2024-05-13) only
- 9
- Like-for-like categories
- 6 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
GPT-4o (2024-05-13)
GPT-4o (2024-05-13) leads, 7.3 against 7.0.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-4o (2024-05-13) has a GPQA Diamond result, 50.2%.
Directional only
Web design
Design Arena: websites
No call
Only Nova Pro 1.0 has a Design Arena: websites result, 796.
Directional only
Long documents
Listed context window
Nova Pro 1.0
Nova Pro 1.0 takes 300K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nova Pro 1.0
Nova Pro 1.0 $0.0024, GPT-4o (2024-05-13) $0.013 per turn.
List prices
At a glance
- Coding index
- Nova Pro 1.0 not benchmarked, GPT-4o (2024-05-13) not benchmarked.
- Widest category
- General, 10.2 points apart on average over 18 shared benchmarks.
- Widest single gap
- LMArena Vision: English: Nova Pro 1.0 987 against GPT-4o (2024-05-13) 1147, 24.5 points apart on a 0 to 100 scale.
- Output price
- Nova Pro 1.0 $3.20 against GPT-4o (2024-05-13) $15.00 per million output tokens, 4.7x apart.
- Context window
- Nova Pro 1.0 takes 300K tokens, GPT-4o (2024-05-13) 128K.
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 | Nova Pro 1.0 | Bars | GPT-4o (2024-05-13) | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 1 | 4 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 6 | ||
| General | 0 | 18 | ||
| All shared boards | 1 | 34 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Nova Pro 1.0 | GPT-4o (2024-05-13) | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 24.2 | Only GPT-4o (2024-05-13) measured |
| LiveCodeBench (Artificial Analysis run) | 23.3% | 33.4% | GPT-4o (2024-05-13) |
| Terminal-Bench Hard (Artificial Analysis run) | 6.1% | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: coding | 1270 | 1297 | GPT-4o (2024-05-13) |
| LMArena Text: software and IT | 1271 | 1297 | GPT-4o (2024-05-13) |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Pro 1.0 | GPT-4o (2024-05-13) | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.0 | 7.3 | GPT-4o (2024-05-13) |
| 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 | Nova Pro 1.0 | GPT-4o (2024-05-13) | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 14.0% | Not measured | Only Nova Pro 1.0 measured |
| METR time horizons | Not measured | 40.8% | Only GPT-4o (2024-05-13) measured |
| BALROG | Not measured | 32.3% | Only GPT-4o (2024-05-13) measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index14
| Benchmark | Nova Pro 1.0 | GPT-4o (2024-05-13) | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 50.2% | Only GPT-4o (2024-05-13) measured |
| GPQA Diamond (Artificial Analysis run) | 49.9% | 52.6% | GPT-4o (2024-05-13) |
| Humanity's Last Exam (Artificial Analysis run) | 3.2% | 1.8% | Nova Pro 1.0 |
| GPQA Diamond (Epoch AI run) | Not measured | 48.9% | Only GPT-4o (2024-05-13) measured |
| LMArena Text: hard prompts | 1246 | 1281 | GPT-4o (2024-05-13) |
| LMArena Text: expert | 1211 | 1250 | GPT-4o (2024-05-13) |
| LMArena Text: hard prompts in English | 1259 | 1293 | GPT-4o (2024-05-13) |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Nova Pro 1.0 | GPT-4o (2024-05-13) | Leader |
|---|---|---|---|
| AA Math Index | 7.0 | Not measured | Only Nova Pro 1.0 measured |
| AIME 2025 (Artificial Analysis run) | 7.0% | Not measured | Only Nova Pro 1.0 measured |
| OTIS Mock AIME | Not measured | 6.3% | Only GPT-4o (2024-05-13) measured |
| MATH level 5 | Not measured | 51.0% | Only GPT-4o (2024-05-13) measured |
| LMArena Text: math | 1252 | 1284 | GPT-4o (2024-05-13) |
| LMArena Text: mathematical work | 1261 | 1284 | GPT-4o (2024-05-13) |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Nova Pro 1.0 | GPT-4o (2024-05-13) | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 69.1% | 74.0% | GPT-4o (2024-05-13) |
| MMLU | 82.0% | 84.2% | GPT-4o (2024-05-13) |
| LMArena Text: science | 1255 | 1295 | GPT-4o (2024-05-13) |
| LMArena Text: medicine and healthcare | 1260 | 1278 | GPT-4o (2024-05-13) |
| LMArena Text: legal and government | 1281 | 1314 | GPT-4o (2024-05-13) |
| LMArena Text: business and finance | 1229 | 1262 | GPT-4o (2024-05-13) |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Nova Pro 1.0 | GPT-4o (2024-05-13) | Leader |
|---|---|---|---|
| Design Arena: websites | 796 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 8 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index018
| Benchmark | Nova Pro 1.0 | GPT-4o (2024-05-13) | Leader |
|---|---|---|---|
| IFBench | 38.1% | Not measured | Only Nova Pro 1.0 measured |
| Long context reasoning (AA-LCR) | 21.0% | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text | 1259 | 1300 | GPT-4o (2024-05-13) |
| LMArena Text: instruction following | 1235 | 1278 | GPT-4o (2024-05-13) |
| LMArena Text: creative writing | 1212 | 1291 | GPT-4o (2024-05-13) |
| LMArena Vision | 980 | 1137 | GPT-4o (2024-05-13) |
| LMArena Text: English | 1276 | 1312 | GPT-4o (2024-05-13) |
| LMArena Text: non-English | 1233 | 1283 | GPT-4o (2024-05-13) |
| LMArena Text: Chinese | 1244 | 1277 | GPT-4o (2024-05-13) |
| LMArena Text: German | 1243 | 1283 | GPT-4o (2024-05-13) |
| LMArena Text: Japanese | 1200 | 1257 | GPT-4o (2024-05-13) |
| LMArena Text: Korean | 1203 | 1234 | GPT-4o (2024-05-13) |
| LMArena Text: French | 1271 | 1304 | GPT-4o (2024-05-13) |
| LMArena Text: Spanish | 1182 | 1292 | GPT-4o (2024-05-13) |
| LMArena Text: Russian | 1240 | 1285 | GPT-4o (2024-05-13) |
| LMArena Text: Polish | Not measured | 1365 | Only GPT-4o (2024-05-13) measured |
| LMArena Text: multi-turn | 1246 | 1302 | GPT-4o (2024-05-13) |
| LMArena Text: longer queries | 1255 | 1288 | GPT-4o (2024-05-13) |
| LMArena Text: writing and language | 1247 | 1298 | GPT-4o (2024-05-13) |
| LMArena Text: entertainment and media | 1210 | 1289 | GPT-4o (2024-05-13) |
| LMArena Vision: English | 987 | 1147 | GPT-4o (2024-05-13) |
| LMArena Vision: Chinese | Not measured | 1132 | Only GPT-4o (2024-05-13) measured |
| Neither model has a result on the other 24 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Nova Pro 1.0 | GPT-4o (2024-05-13) | 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
Nova Pro 1.0 costs less
Repository review
50K input + 3K output tokens
Nova Pro 1.0 costs less
Agent loop
200K input + 10K output tokens
Nova Pro 1.0 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 | Amazon Nova Pro 1.0 | OpenAI GPT-4o (2024-05-13) |
|---|---|---|
| Maker | Amazon | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | December 5, 2024 | May 13, 2024 |
| Context window | 300K | 128K |
| Input $/Mtok | $0.80 | $5.00 |
| Output $/Mtok | $3.20 | $15.00 |
| 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 Nova Pro 1.0 better than GPT-4o (2024-05-13) for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nova Pro 1.0 for output tokens 4.7x cheaper ($3.20 vs $15.00 per million) and a larger context window (300K against 128K tokens).
Which is cheaper, Nova Pro 1.0 or GPT-4o (2024-05-13)?
Nova Pro 1.0 costs $0.80 per million input tokens and $3.20 per million output tokens; GPT-4o (2024-05-13) costs $5.00 and $15.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Nova Pro 1.0 or GPT-4o (2024-05-13)?
Nova Pro 1.0, with 300K tokens against 128K.
How many benchmarks is the Nova Pro 1.0 vs GPT-4o (2024-05-13) comparison based on?
35 benchmarks have a result for both models as of October 22, 2026. Nova Pro 1.0's coding index rests on 0 independent benchmarks and GPT-4o (2024-05-13)'s on 0. Where only one model has a result, the page says so instead of naming a winner.