GPT-4o vs GPT-4o (2024-08-06)
GPT-4o and GPT-4o (2024-08-06) cost about the same per output token ($10.00 vs $10.00 per million). Updated October 22, 2026; 9 benchmarks have a result for both.
GPT-4o 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 GPT-4o for work measured by LiveCodeBench (Artificial Analysis run) or τ²-Bench Telecom, where it leads.
- Shared results
- 9
- GPT-4o only
- 19
- GPT-4o (2024-08-06) only
- 49
- 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 GPT-4o (2024-08-06) has a AA Intelligence Index result, 7.7.
Directional only
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 GPT-4o has a Design Arena: websites result, 831.
Directional only
Long documents
Listed context window
No call
Both take 128K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
No call
GPT-4o $0.0075, GPT-4o (2024-08-06) $0.0075 per turn.
List prices
At a glance
- Coding index
- GPT-4o not benchmarked, GPT-4o (2024-08-06) not benchmarked.
- Widest category
- Coding, 5.7 points apart on average over 3 shared benchmarks.
- Widest single gap
- SWE-bench Lite: GPT-4o 38.0% against GPT-4o (2024-08-06) 21.7%, 16.3 points apart on a 0 to 100 scale.
- Output price
- Both cost $10.00 per million output tokens.
- 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 | GPT-4o | Bars | GPT-4o (2024-08-06) | Ties |
|---|---|---|---|---|
| Coding | 1 | 1 | 1 tie | |
| Agentic work | 0 | 1 | ||
| Reasoning | 2 | 0 | ||
| Knowledge | 1 | 0 | ||
| General | 1 | 1 | ||
| All shared boards | 5 | 3 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index11
| Benchmark | GPT-4o | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 23.1% | Only GPT-4o (2024-08-06) measured |
| SWE-bench Verified | 38.8% | Not measured | Only GPT-4o measured |
| SWE-bench Lite | 38.0% | 21.7% | GPT-4o |
| SWE-bench (full test set) | 18.8% | Not measured | Only GPT-4o measured |
| SWE-bench Multimodal | 30.4% | Not measured | Only GPT-4o measured |
| LiveCodeBench (Artificial Analysis run) | 30.9% | 31.7% | GPT-4o (2024-08-06) |
| Terminal-Bench Hard (Artificial Analysis run) | 8.3% | 8.3% | Tie |
| 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 |
| SciCode | 1.5% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 33 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-4o | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 7.7 | Only GPT-4o (2024-08-06) measured |
| 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 | GPT-4o | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 25.1% | 28.9% | GPT-4o (2024-08-06) |
| GDPval | 9.9% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-4o | 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) | 54.3% | 52.1% | GPT-4o |
| Humanity's Last Exam (Artificial Analysis run) | 2.4% | 2.3% | GPT-4o |
| GPQA Diamond (Epoch AI run) | Not measured | 49.2% | Only GPT-4o (2024-08-06) measured |
| ARC-AGI | 4.5% | Not measured | Only GPT-4o measured |
| ARC-AGI-2 | 0.0% | Not measured | Only GPT-4o 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 |
| Neither model has a result on the other 12 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | GPT-4o | 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 GPT-4o measured |
| AIME 2025 (Artificial Analysis run) | 6.0% | Not measured | Only GPT-4o 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 |
| MathArena | 3.6% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-4o | 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) | 74.8% | Not measured | Only GPT-4o measured |
| SimpleQA Verified | Not measured | 26.0% | Only GPT-4o (2024-08-06) measured |
| MMLU | 88.1% | 84.3% | GPT-4o |
| 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 7 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-4o | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| Design Arena: websites | 831 | Not measured | Only GPT-4o measured |
| Design Arena: UI components | 883 | Not measured | Only GPT-4o measured |
| Design Arena: game dev | 906 | Not measured | Only GPT-4o measured |
| Design Arena: data viz | 858 | Not measured | Only GPT-4o measured |
| Design Arena: 3D | 868 | Not measured | Only GPT-4o measured |
| Design Arena: all code categories | 860 | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | GPT-4o | GPT-4o (2024-08-06) | Leader |
|---|---|---|---|
| IFBench | 34.3% | 36.0% | GPT-4o (2024-08-06) |
| Long context reasoning (AA-LCR) | 49.3% | 41.0% | GPT-4o |
| DTBench | 64.5% | Not measured | Only GPT-4o measured |
| LMCA | 16.6% | Not measured | Only GPT-4o measured |
| 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 | GPT-4o | 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
Same cost
Repository review
50K input + 3K output tokens
Same cost
Agent loop
200K input + 10K output tokens
Same cost
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 | OpenAI GPT-4o (2024-08-06) |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | May 13, 2024 | August 6, 2024 |
| Context window | 128K | 128K |
| Input $/Mtok | $2.50 | $2.50 |
| Output $/Mtok | $10.00 | $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 GPT-4o 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 GPT-4o for work measured by LiveCodeBench (Artificial Analysis run) or τ²-Bench Telecom, where it leads.
Which is cheaper, GPT-4o or GPT-4o (2024-08-06)?
GPT-4o costs $2.50 per million input tokens and $10.00 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, GPT-4o or GPT-4o (2024-08-06)?
Neither: both take 128K tokens.
How many benchmarks is the GPT-4o vs GPT-4o (2024-08-06) comparison based on?
9 benchmarks have a result for both models as of October 22, 2026. GPT-4o'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.