Nova Micro 1.0 vs GPT-4o (2024-08-06)
GPT-4o (2024-08-06) leads Nova Micro 1.0 on the Artificial Analysis Intelligence Index, 7.7 to 5.9, and Nova Micro 1.0 costs 71.4x less per output token ($0.14 vs $10.00 per million). Updated October 22, 2026; 36 benchmarks have a result for both.
Nova Micro 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 Micro 1.0 for output tokens 71.4x cheaper ($0.14 vs $10.00 per million) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.
- Shared results
- 36
- Nova Micro 1.0 only
- 3
- GPT-4o (2024-08-06) only
- 22
- Like-for-like categories
- 7 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 (2024-08-06)
GPT-4o (2024-08-06) leads, 7.7 against 5.9.
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
Long documents
Listed context window
No call
Both take 128K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nova Micro 1.0
Nova Micro 1.0 $0.0001, GPT-4o (2024-08-06) $0.0075 per turn.
List prices
At a glance
- Coding index
- Nova Micro 1.0 not benchmarked, GPT-4o (2024-08-06) not benchmarked.
- Widest category
- Agentic work, 14.9 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Nova Micro 1.0 13.0% against GPT-4o (2024-08-06) 41.0%, 28.0 points apart on a 0 to 100 scale.
- Output price
- Nova Micro 1.0 $0.14 against GPT-4o (2024-08-06) $10.00 per million output tokens, 71.4x apart.
- Context window
- Both take 128K 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 | Nova Micro 1.0 | Bars | GPT-4o (2024-08-06) | Ties |
|---|---|---|---|---|
| Coding | 0 | 4 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 1 | 4 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 5 | ||
| General | 0 | 18 | ||
| All shared boards | 1 | 35 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
| Benchmark | Nova Micro 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) | 14.0% | 31.7% | GPT-4o (2024-08-06) |
| Terminal-Bench Hard (Artificial Analysis run) | 1.5% | 8.3% | GPT-4o (2024-08-06) |
| LMArena Text: coding | 1218 | 1283 | GPT-4o (2024-08-06) |
| LMArena Text: software and IT | 1215 | 1278 | GPT-4o (2024-08-06) |
| Neither model has a result on the other 33 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Micro 1.0 | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| AA Intelligence Index | 5.9 | 7.7 | GPT-4o (2024-08-06) |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Micro 1.0 | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 14.0% | 28.9% | GPT-4o (2024-08-06) |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index14
| Benchmark | Nova Micro 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) | 35.8% | 52.1% | GPT-4o (2024-08-06) |
| Humanity's Last Exam (Artificial Analysis run) | 4.6% | 2.3% | Nova Micro 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 | 1191 | 1264 | GPT-4o (2024-08-06) |
| LMArena Text: expert | 1183 | 1241 | GPT-4o (2024-08-06) |
| LMArena Text: hard prompts in English | 1203 | 1277 | GPT-4o (2024-08-06) |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Nova Micro 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 | 6.0 | Not measured | Only Nova Micro 1.0 measured |
| AIME 2025 (Artificial Analysis run) | 6.0% | Not measured | Only Nova Micro 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 | 1206 | 1285 | GPT-4o (2024-08-06) |
| LMArena Text: mathematical work | 1212 | 1283 | GPT-4o (2024-08-06) |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Nova Micro 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) | 53.1% | Not measured | Only Nova Micro 1.0 measured |
| SimpleQA Verified | Not measured | 26.0% | Only GPT-4o (2024-08-06) measured |
| MMLU | 70.8% | 84.3% | GPT-4o (2024-08-06) |
| LMArena Text: science | 1210 | 1274 | GPT-4o (2024-08-06) |
| LMArena Text: medicine and healthcare | 1207 | 1252 | GPT-4o (2024-08-06) |
| LMArena Text: legal and government | 1221 | 1275 | GPT-4o (2024-08-06) |
| LMArena Text: business and finance | 1182 | 1232 | GPT-4o (2024-08-06) |
| Neither model has a result on the other 5 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Nova Micro 1.0 | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index018
| Benchmark | Nova Micro 1.0 | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| IFBench | 29.4% | 36.0% | GPT-4o (2024-08-06) |
| Long context reasoning (AA-LCR) | 13.0% | 41.0% | GPT-4o (2024-08-06) |
| LMArena Text | 1208 | 1283 | GPT-4o (2024-08-06) |
| LMArena Text: instruction following | 1174 | 1267 | GPT-4o (2024-08-06) |
| LMArena Text: creative writing | 1172 | 1274 | GPT-4o (2024-08-06) |
| LMArena Vision | Not measured | 1065 | Only GPT-4o (2024-08-06) measured |
| LMArena Text: English | 1224 | 1297 | GPT-4o (2024-08-06) |
| LMArena Text: non-English | 1186 | 1262 | GPT-4o (2024-08-06) |
| LMArena Text: Chinese | 1209 | 1254 | GPT-4o (2024-08-06) |
| LMArena Text: German | 1192 | 1257 | GPT-4o (2024-08-06) |
| LMArena Text: Japanese | 1154 | 1234 | GPT-4o (2024-08-06) |
| LMArena Text: Korean | 1150 | 1218 | GPT-4o (2024-08-06) |
| LMArena Text: French | 1238 | 1263 | GPT-4o (2024-08-06) |
| LMArena Text: Spanish | 1225 | 1269 | GPT-4o (2024-08-06) |
| LMArena Text: Russian | 1185 | 1272 | GPT-4o (2024-08-06) |
| LMArena Text: multi-turn | 1178 | 1279 | GPT-4o (2024-08-06) |
| LMArena Text: longer queries | 1205 | 1283 | GPT-4o (2024-08-06) |
| LMArena Text: writing and language | 1192 | 1290 | GPT-4o (2024-08-06) |
| LMArena Text: entertainment and media | 1163 | 1267 | GPT-4o (2024-08-06) |
| 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 Micro 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
Nova Micro 1.0 costs less
Repository review
50K input + 3K output tokens
Nova Micro 1.0 costs less
Agent loop
200K input + 10K output tokens
Nova Micro 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 Micro 1.0 | OpenAI GPT-4o (2024-08-06) |
|---|---|---|
| Maker | Amazon | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | December 5, 2024 | August 6, 2024 |
| Context window | 128K | 128K |
| Input $/Mtok | $0.035 | $2.50 |
| Output $/Mtok | $0.14 | $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 Micro 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 Micro 1.0 for output tokens 71.4x cheaper ($0.14 vs $10.00 per million) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.
Which is cheaper, Nova Micro 1.0 or GPT-4o (2024-08-06)?
Nova Micro 1.0 costs $0.035 per million input tokens and $0.14 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 Micro 1.0 or GPT-4o (2024-08-06)?
Neither: both take 128K tokens.
How many benchmarks is the Nova Micro 1.0 vs GPT-4o (2024-08-06) comparison based on?
36 benchmarks have a result for both models as of October 22, 2026. Nova Micro 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.