GPT-4o (2024-05-13) vs o3 Pro
o3 Pro leads GPT-4o (2024-05-13) on the Artificial Analysis Intelligence Index, 21.9 to 7.3, and GPT-4o (2024-05-13) costs 5.3x less per output token ($15.00 vs $80.00 per million). Updated October 22, 2026; 2 benchmarks have a result for both.
GPT-4o (2024-05-13) or o3 Pro: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-4o (2024-05-13) for output tokens 5.3x cheaper ($15.00 vs $80.00 per million) and work measured by AA Intelligence Index or GPQA Diamond (Artificial Analysis run), where it leads.
- Shared results
- 2
- GPT-4o (2024-05-13) only
- 42
- o3 Pro only
- 10
- Like-for-like categories
- 2 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
o3 Pro
o3 Pro leads, 21.9 against 7.3.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-4o (2024-05-13) has a GPQA Diamond result, 50.2%.
Directional only
Long documents
Listed context window
o3 Pro
o3 Pro takes 200K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-4o (2024-05-13)
GPT-4o (2024-05-13) $0.013, o3 Pro $0.060 per turn.
List prices
At a glance
- Coding index
- GPT-4o (2024-05-13) not benchmarked, o3 Pro not benchmarked.
- Widest category
- Reasoning, 31.9 points apart on average over 1 shared benchmark.
- Widest single gap
- GPQA Diamond (Artificial Analysis run): GPT-4o (2024-05-13) 52.6% against o3 Pro 84.5%, 31.9 points apart on a 0 to 100 scale.
- Output price
- GPT-4o (2024-05-13) $15.00 against o3 Pro $80.00 per million output tokens, 5.3x apart.
- Context window
- GPT-4o (2024-05-13) takes 128K tokens, o3 Pro 200K.
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 (2024-05-13) | Bars | o3 Pro | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| All shared boards | 0 | 2 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index6 boards, none shared
| Benchmark | GPT-4o (2024-05-13) | o3 Pro | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 84.9% | Only o3 Pro measured |
| AA Coding Index | 24.2 | Not measured | Only GPT-4o (2024-05-13) measured |
| LiveCodeBench (Artificial Analysis run) | 33.4% | Not measured | Only GPT-4o (2024-05-13) measured |
| WeirdML | Not measured | 58.2% | Only o3 Pro measured |
| LMArena Text: coding | 1297 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: software and IT | 1297 | Not measured | Only GPT-4o (2024-05-13) measured |
| Neither model has a result on the other 33 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4o (2024-05-13) | o3 Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.3 | 21.9 | o3 Pro |
| Epoch Capabilities Index | Not measured | 147.3 | Only o3 Pro measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-4o (2024-05-13) | o3 Pro | Leader |
|---|---|---|---|
| METR time horizons | 40.8% | Not measured | Only GPT-4o (2024-05-13) measured |
| BALROG | 32.3% | Not measured | Only GPT-4o (2024-05-13) measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4o (2024-05-13) | o3 Pro | Leader |
|---|---|---|---|
| GPQA Diamond | 50.2% | Not measured | Only GPT-4o (2024-05-13) measured |
| GPQA Diamond (Artificial Analysis run) | 52.6% | 84.5% | o3 Pro |
| Humanity's Last Exam (Artificial Analysis run) | 1.8% | Not measured | Only GPT-4o (2024-05-13) measured |
| GPQA Diamond (Epoch AI run) | 48.9% | Not measured | Only GPT-4o (2024-05-13) measured |
| ARC-AGI | Not measured | 59.3% | Only o3 Pro measured |
| ARC-AGI-2 | Not measured | 4.9% | Only o3 Pro measured |
| LMArena Text: hard prompts | 1281 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: expert | 1250 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: hard prompts in English | 1293 | Not measured | Only GPT-4o (2024-05-13) measured |
| Kagi LLM Benchmark | Not measured | 72.1% | Only o3 Pro measured |
| Neither model has a result on the other 12 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GPT-4o (2024-05-13) | o3 Pro | Leader |
|---|---|---|---|
| OTIS Mock AIME | 6.3% | Not measured | Only GPT-4o (2024-05-13) measured |
| MATH level 5 | 51.0% | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: math | 1284 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: mathematical work | 1284 | Not measured | Only GPT-4o (2024-05-13) measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-4o (2024-05-13) | o3 Pro | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 74.0% | Not measured | Only GPT-4o (2024-05-13) measured |
| MMLU | 84.2% | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: science | 1295 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: medicine and healthcare | 1278 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: legal and government | 1314 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: business and finance | 1262 | Not measured | Only GPT-4o (2024-05-13) measured |
| Neither model has a result on the other 12 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o (2024-05-13) | o3 Pro | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index24 boards, none shared
| Benchmark | GPT-4o (2024-05-13) | o3 Pro | Leader |
|---|---|---|---|
| DTBench | Not measured | 86.9% | Only o3 Pro measured |
| LMCA | Not measured | 38.5% | Only o3 Pro measured |
| Fiction.LiveBench | Not measured | 97.2% | Only o3 Pro measured |
| Creative writing (Lech Mazur) | Not measured | 84.4% | Only o3 Pro measured |
| LMArena Text | 1300 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: instruction following | 1278 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: creative writing | 1291 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Vision | 1137 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: English | 1312 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: non-English | 1283 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: Chinese | 1277 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: German | 1283 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: Japanese | 1257 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: Korean | 1234 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: French | 1304 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: Spanish | 1292 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: Russian | 1285 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: Polish | 1365 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: multi-turn | 1302 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: longer queries | 1288 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: writing and language | 1298 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: entertainment and media | 1289 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Vision: English | 1147 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Vision: Chinese | 1132 | Not measured | Only GPT-4o (2024-05-13) measured |
| Neither model has a result on the other 22 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o (2024-05-13) | o3 Pro | 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 (2024-05-13) costs less
Repository review
50K input + 3K output tokens
GPT-4o (2024-05-13) costs less
Agent loop
200K input + 10K output tokens
GPT-4o (2024-05-13) 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 (2024-05-13) | OpenAI o3 Pro |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | May 13, 2024 | June 10, 2025 |
| Context window | 128K | 200K |
| Input $/Mtok | $5.00 | $20.00 |
| Output $/Mtok | $15.00 | $80.00 |
| 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 GPT-4o (2024-05-13) better than o3 Pro for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4o (2024-05-13) for output tokens 5.3x cheaper ($15.00 vs $80.00 per million) and work measured by AA Intelligence Index or GPQA Diamond (Artificial Analysis run), where it leads.
Which is cheaper, GPT-4o (2024-05-13) or o3 Pro?
GPT-4o (2024-05-13) costs $5.00 per million input tokens and $15.00 per million output tokens; o3 Pro costs $20.00 and $80.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4o (2024-05-13) or o3 Pro?
o3 Pro, with 200K tokens against 128K.
How many benchmarks is the GPT-4o (2024-05-13) vs o3 Pro comparison based on?
2 benchmarks have a result for both models as of October 22, 2026. GPT-4o (2024-05-13)'s coding index rests on 0 independent benchmarks and o3 Pro's on 0. Where only one model has a result, the page says so instead of naming a winner.