Nova Premier 1.0 vs GPT-4o (2024-08-06)
Nova Premier 1.0 leads GPT-4o (2024-08-06) on the Artificial Analysis Intelligence Index, 9.2 to 7.7, and GPT-4o (2024-08-06) costs 1.3x less per output token ($10.00 vs $12.50 per million). Updated October 22, 2026; 8 benchmarks have a result for both.
Nova Premier 1.0 or GPT-4o (2024-08-06): which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Nova Premier 1.0 for a larger context window (1M against 128K tokens) and work measured by Terminal-Bench Hard (Artificial Analysis run) or Long context reasoning (AA-LCR), where it leads.
- Shared results
- 8
- Nova Premier 1.0 only
- 6
- GPT-4o (2024-08-06) only
- 50
- 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
Nova Premier 1.0
Nova Premier 1.0 leads, 9.2 against 7.7.
Same board, both measured
Math
AIME
No call
Only GPT-4o (2024-08-06) has a AIME result, 14.0%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4o (2024-08-06) has a MMLU Pro result, 74.1%.
Directional only
Web design
Design Arena: websites
No call
Only Nova Premier 1.0 has a Design Arena: websites result, 835.
Directional only
Long documents
Listed context window
Nova Premier 1.0
Nova Premier 1.0 takes 1M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-4o (2024-08-06)
Nova Premier 1.0 $0.0088, GPT-4o (2024-08-06) $0.0075 per turn.
List prices
At a glance
- Coding index
- Nova Premier 1.0 not benchmarked, GPT-4o (2024-08-06) not benchmarked.
- Widest category
- Agentic work, 9.4 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Nova Premier 1.0 38.3% against GPT-4o (2024-08-06) 28.9%, 9.4 points apart on a 0 to 100 scale.
- Output price
- Nova Premier 1.0 $12.50 against GPT-4o (2024-08-06) $10.00 per million output tokens, 1.3x apart.
- Context window
- Nova Premier 1.0 takes 1M tokens, GPT-4o (2024-08-06) 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 Premier 1.0 | Bars | GPT-4o (2024-08-06) | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | 1 tie | |
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 1 | 1 | ||
| All shared boards | 5 | 2 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Nova Premier 1.0 | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 23.1% | Only GPT-4o (2024-08-06) measured |
| SWE-bench Lite | Not measured | 21.7% | Only GPT-4o (2024-08-06) measured |
| LiveCodeBench (Artificial Analysis run) | 31.7% | 31.7% | Tie |
| Terminal-Bench Hard (Artificial Analysis run) | 6.8% | 8.3% | GPT-4o (2024-08-06) |
| ALE-Bench | 147.4 | Not measured | Only Nova Premier 1.0 measured |
| LMArena Text: coding | Not measured | 1283 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: software and IT | Not measured | 1278 | Only GPT-4o (2024-08-06) measured |
| Neither model has a result on the other 32 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Nova Premier 1.0 | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.2 | 7.7 | Nova Premier 1.0 |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Nova Premier 1.0 | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 38.3% | 28.9% | Nova Premier 1.0 |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Nova Premier 1.0 | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| MMMU Pro (Vals AI) | Not measured | 64.0% | Only GPT-4o (2024-08-06) measured |
| GPQA Diamond (Artificial Analysis run) | 56.9% | 52.1% | Nova Premier 1.0 |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | 2.3% | Nova Premier 1.0 |
| GPQA Diamond (Epoch AI run) | Not measured | 49.2% | Only GPT-4o (2024-08-06) measured |
| SimpleBench | Not measured | 17.8% | Only GPT-4o (2024-08-06) measured |
| Chess puzzles | Not measured | 6.0% | Only GPT-4o (2024-08-06) measured |
| LMArena Text: hard prompts | Not measured | 1264 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: expert | Not measured | 1241 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: hard prompts in English | Not measured | 1277 | Only GPT-4o (2024-08-06) measured |
| Kagi LLM Benchmark | 44.8% | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 12 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | Nova Premier 1.0 | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| AIME | Not measured | 14.0% | Only GPT-4o (2024-08-06) measured |
| MATH 500 (Vals AI) | Not measured | 75.2% | Only GPT-4o (2024-08-06) measured |
| MGSM (Vals AI) | Not measured | 90.7% | Only GPT-4o (2024-08-06) measured |
| AA Math Index | 17.3 | Not measured | Only Nova Premier 1.0 measured |
| AIME 2025 (Artificial Analysis run) | 17.3% | Not measured | Only Nova Premier 1.0 measured |
| OTIS Mock AIME | Not measured | 6.4% | Only GPT-4o (2024-08-06) measured |
| FrontierMath, tiers 1 to 3 | Not measured | 0.4% | Only GPT-4o (2024-08-06) measured |
| MATH level 5 | Not measured | 53.3% | Only GPT-4o (2024-08-06) measured |
| LMArena Text: math | Not measured | 1285 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: mathematical work | Not measured | 1283 | Only GPT-4o (2024-08-06) measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
| Benchmark | Nova Premier 1.0 | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 74.1% | Only GPT-4o (2024-08-06) measured |
| LegalBench (Vals AI) | Not measured | 80.1% | Only GPT-4o (2024-08-06) measured |
| CorpFin (Vals AI) | Not measured | 39.4% | Only GPT-4o (2024-08-06) measured |
| TaxEval (Vals AI) | Not measured | 71.1% | Only GPT-4o (2024-08-06) measured |
| MortgageTax (Vals AI) | Not measured | 61.0% | Only GPT-4o (2024-08-06) measured |
| MedQA (Vals AI) | Not measured | 88.2% | Only GPT-4o (2024-08-06) measured |
| MMLU Pro (Artificial Analysis run) | 73.3% | Not measured | Only Nova Premier 1.0 measured |
| SimpleQA Verified | Not measured | 26.0% | Only GPT-4o (2024-08-06) measured |
| MMLU | Not measured | 84.3% | Only GPT-4o (2024-08-06) measured |
| LMArena Text: science | Not measured | 1274 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: medicine and healthcare | Not measured | 1252 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: legal and government | Not measured | 1275 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: business and finance | Not measured | 1232 | Only GPT-4o (2024-08-06) measured |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Nova Premier 1.0 | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| Design Arena: websites | 835 | Not measured | Only Nova Premier 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 index11
| Benchmark | Nova Premier 1.0 | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| IFBench | 36.2% | 36.0% | Nova Premier 1.0 |
| Long context reasoning (AA-LCR) | 34.3% | 41.0% | GPT-4o (2024-08-06) |
| LMArena Text | Not measured | 1283 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: instruction following | Not measured | 1267 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: creative writing | Not measured | 1274 | Only GPT-4o (2024-08-06) measured |
| LMArena Vision | Not measured | 1065 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: English | Not measured | 1297 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: non-English | Not measured | 1262 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: Chinese | Not measured | 1254 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: German | Not measured | 1257 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: Japanese | Not measured | 1234 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: Korean | Not measured | 1218 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: French | Not measured | 1263 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: Spanish | Not measured | 1269 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: Russian | Not measured | 1272 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: multi-turn | Not measured | 1279 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: longer queries | Not measured | 1283 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: writing and language | Not measured | 1290 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: entertainment and media | Not measured | 1267 | Only GPT-4o (2024-08-06) measured |
| LMArena Vision: English | Not measured | 1072 | Only GPT-4o (2024-08-06) measured |
| LMArena Vision: Chinese | Not measured | 1009 | Only GPT-4o (2024-08-06) 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 | Nova Premier 1.0 | GPT-4o (2024-08-06) | 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
GPT-4o (2024-08-06) costs less
Repository review
50K input + 3K output tokens
GPT-4o (2024-08-06) costs less
Agent loop
200K input + 10K output tokens
GPT-4o (2024-08-06) 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 Premier 1.0 | OpenAI GPT-4o (2024-08-06) |
|---|---|---|
| Maker | Amazon | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | October 31, 2025 | August 6, 2024 |
| Context window | 1M | 128K |
| Input $/Mtok | $2.50 | $2.50 |
| Output $/Mtok | $12.50 | $10.00 |
| 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 Premier 1.0 better than GPT-4o (2024-08-06) for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nova Premier 1.0 for a larger context window (1M against 128K tokens) and work measured by Terminal-Bench Hard (Artificial Analysis run) or Long context reasoning (AA-LCR), where it leads.
Which is cheaper, Nova Premier 1.0 or GPT-4o (2024-08-06)?
Nova Premier 1.0 costs $2.50 per million input tokens and $12.50 per million output tokens; GPT-4o (2024-08-06) costs $2.50 and $10.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Nova Premier 1.0 or GPT-4o (2024-08-06)?
Nova Premier 1.0, with 1M tokens against 128K.
How many benchmarks is the Nova Premier 1.0 vs GPT-4o (2024-08-06) comparison based on?
8 benchmarks have a result for both models as of October 22, 2026. Nova Premier 1.0's coding index rests on 0 independent benchmarks and GPT-4o (2024-08-06)'s on 0. Where only one model has a result, the page says so instead of naming a winner.