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GPT-4o (2024-08-06) vs o3

o3 leads GPT-4o (2024-08-06) on the Artificial Analysis Intelligence Index, 20.2 to 7.7, and o3 costs 1.3x less per output token ($8.00 vs $10.00 per million). Updated October 22, 2026; 56 benchmarks have a result for both.

Replace GPT-4o (2024-08-06) Replace o3
GPT-4o (2024-08-06)OpenAI
Coding
No data
Overall
26.3
Output $/M
$10.00
0
o3OpenAI
Coding
No data
Overall
51.1
Output $/M
$8.00
56
vs boards won of 56 shared

GPT-4o (2024-08-06) or o3: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick GPT-4o (2024-08-06) for work measured by Aider polyglot or LiveCodeBench (Artificial Analysis run), where it leads.

Model AGPT-4o (2024-08-06)OpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel Bo3OpenAINot benchmarkedNo coding benchmark$0.571 per solved task
Shared results
56
GPT-4o (2024-08-06) only
2
o3 only
46
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.

At a glance

Coding index
GPT-4o (2024-08-06) not benchmarked, o3 not benchmarked.
Widest category
Agentic work, 51.8 points apart on average over 1 shared benchmark.
Widest single gap
OTIS Mock AIME: GPT-4o (2024-08-06) 6.4% against o3 84.4%, 78.1 points apart on a 0 to 100 scale.
Output price
GPT-4o (2024-08-06) $10.00 against o3 $8.00 per million output tokens, 1.3x apart.
Context window
GPT-4o (2024-08-06) takes 128K tokens, o3 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.

Boards won, where both have a result
CategoryGPT-4o (2024-08-06)Barso3Ties
Coding05
Intelligence01
Agentic work01
Reasoning09
Math08
Knowledge011
General021
All shared boards056
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
Coding benchmarks for GPT-4o (2024-08-06) and o3
BenchmarkGPT-4o (2024-08-06)o3Leader
Aider polyglot23.1%81.3%o3
SWE-bench VerifiedNot measured58.4%Only o3 measured
SWE-bench Lite21.7%Not measuredOnly GPT-4o (2024-08-06) measured
SWE-bench MultimodalNot measured36.0%Only o3 measured
LiveCodeBench (Vals AI)Not measured83.9%Only o3 measured
LiveCodeBench (Artificial Analysis run)31.7%80.8%o3
Terminal-Bench Hard (Artificial Analysis run)8.3%37.1%o3
GSO-BenchNot measured8.8%Only o3 measured
WeirdMLNot measured52.4%Only o3 measured
ALE-BenchNot measured933.5Only o3 measured
LMArena Text: coding12831407o3
LMArena Text: software and IT12781415o3
SciCodeNot measured9.2%Only o3 measured
Neither model has a result on the other 26 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GPT-4o (2024-08-06) and o3
BenchmarkGPT-4o (2024-08-06)o3Leader
AA Intelligence Index7.720.2o3
Epoch Capabilities IndexNot measured146.7Only o3 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GPT-4o (2024-08-06) and o3
BenchmarkGPT-4o (2024-08-06)o3Leader
τ²-Bench Telecom28.9%80.7%o3
METR time horizonsNot measured65.4%Only o3 measured
GDPvalNot measured30.8%Only o3 measured
DeepResearch BenchNot measured45.2%Only o3 measured
OSWorldNot measured23.0%Only o3 measured
Berkeley Function Calling Leaderboard (BFCL)Not measured63.0%Only o3 measured
BrowseComp-PlusNot measured65.9%Only o3 measured
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index09
Reasoning benchmarks for GPT-4o (2024-08-06) and o3
BenchmarkGPT-4o (2024-08-06)o3Leader
GPQA DiamondNot measured84.1%Only o3 measured
MMMU Pro (Vals AI)64.0%80.4%o3
GPQA Diamond (Artificial Analysis run)52.1%82.7%o3
Humanity's Last Exam (Artificial Analysis run)2.3%20.1%o3
GPQA Diamond (Epoch AI run)49.2%81.8%o3
ARC-AGINot measured60.8%Only o3 measured
ARC-AGI-2Not measured6.5%Only o3 measured
SimpleBench17.8%53.1%o3
Chess puzzles6.0%37.0%o3
Mystery game puzzlesNot measured29.0%Only o3 measured
VPCTNot measured52.0%Only o3 measured
LMArena Text: hard prompts12641402o3
LMArena Text: expert12411402o3
LMArena Text: hard prompts in English12771411o3
LMArena Vision: diagramsNot measured1220Only o3 measured
LMArena Vision: homeworkNot measured1234Only o3 measured
Kagi LLM BenchmarkNot measured67.6%Only o3 measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index08
Math benchmarks for GPT-4o (2024-08-06) and o3
BenchmarkGPT-4o (2024-08-06)o3Leader
AIME14.0%85.3%o3
MATH 500 (Vals AI)75.2%94.6%o3
MGSM (Vals AI)90.7%91.8%o3
AA Math IndexNot measured88.3Only o3 measured
AIME 2025 (Artificial Analysis run)Not measured88.3%Only o3 measured
OTIS Mock AIME6.4%84.4%o3
FrontierMath, tiers 1 to 30.4%33.3%o3
MATH level 553.3%97.8%o3
LMArena Text: math12851426o3
LMArena Text: mathematical work12831423o3
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index011
Knowledge benchmarks for GPT-4o (2024-08-06) and o3
BenchmarkGPT-4o (2024-08-06)o3Leader
MMLU Pro74.1%85.6%o3
LegalBench (Vals AI)80.1%83.8%o3
CorpFin (Vals AI)39.4%59.7%o3
TaxEval (Vals AI)71.1%74.6%o3
MortgageTax (Vals AI)61.0%65.7%o3
MedQA (Vals AI)88.2%96.1%o3
MedCode (Vals AI)Not measured47.3%Only o3 measured
MMLU Pro (Artificial Analysis run)Not measured85.3%Only o3 measured
SimpleQA Verified26.0%49.4%o3
MMLU84.3%Not measuredOnly GPT-4o (2024-08-06) measured
GeoBenchNot measured74.0%Only o3 measured
LMArena Text: science12741429o3
LMArena Text: medicine and healthcare12521448o3
LMArena Text: legal and government12751428o3
LMArena Text: business and finance12321393o3
FACTS Benchmark SuiteNot measured44.4%Only o3 measured
Neither model has a result on the other 2 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Web design benchmarks for GPT-4o (2024-08-06) and o3
BenchmarkGPT-4o (2024-08-06)o3Leader
Design Arena: websitesNot measured1036Only o3 measured
Design Arena: UI componentsNot measured1017Only o3 measured
Design Arena: game devNot measured1034Only o3 measured
Design Arena: data vizNot measured1200Only o3 measured
Design Arena: all code categoriesNot measured1020Only o3 measured
Neither model has a result on the other 4 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index021
General benchmarks for GPT-4o (2024-08-06) and o3
BenchmarkGPT-4o (2024-08-06)o3Leader
SAGE (Vals AI)Not measured41.8%Only o3 measured
MedScribe (Vals AI)Not measured76.7%Only o3 measured
IFBench36.0%71.4%o3
Long context reasoning (AA-LCR)41.0%74.7%o3
DTBenchNot measured84.8%Only o3 measured
LMCANot measured39.7%Only o3 measured
Fiction.LiveBenchNot measured88.9%Only o3 measured
Creative writing (Lech Mazur)Not measured83.9%Only o3 measured
CL-benchNot measured17.8%Only o3 measured
LMArena Text12831410o3
LMArena Text: instruction following12671368o3
LMArena Text: creative writing12741359o3
LMArena Vision10651214o3
LMArena Text: English12971417o3
LMArena Text: non-English12621401o3
LMArena Text: Chinese12541437o3
LMArena Text: German12571420o3
LMArena Text: Japanese12341403o3
LMArena Text: Korean12181370o3
LMArena Text: French12631430o3
LMArena Text: Spanish12691395o3
LMArena Text: Russian12721406o3
LMArena Text: PolishNot measured1438Only o3 measured
LMArena Text: multi-turn12791405o3
LMArena Text: longer queries12831372o3
LMArena Text: writing and language12901372o3
LMArena Text: entertainment and media12671373o3
LMArena Vision: English10721221o3
LMArena Vision: Chinese10091237o3
LMArena Vision: reading textNot measured1218Only o3 measured
LMArena Vision: humorNot measured1222Only o3 measured
LMArena Vision: captioningNot measured1210Only o3 measured
LMArena Vision: recognizing thingsNot measured1234Only o3 measured
LMArena Vision: creative writingNot measured1201Only o3 measured
Neither model has a result on the other 12 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4o (2024-08-06) and o3
BenchmarkGPT-4o (2024-08-06)o3Leader
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)$0.0075Fits in one request
o3$0.0060Fits in one request

o3 costs less

Repository review

50K input + 3K output tokens

GPT-4o (2024-08-06)$0.155Fits in one request
o3$0.124Fits in one request

o3 costs less

Agent loop

200K input + 10K output tokens

GPT-4o (2024-08-06)$0.600Exceeds the context window
o3$0.480Exceeds the context window

o3 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.

Specifications of GPT-4o (2024-08-06) and o3
SpecificationOpenAI GPT-4o (2024-08-06)OpenAI o3
MakerOpenAIOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedAugust 6, 2024April 16, 2025
Context window128K200K
Input $/Mtok$2.50$2.00
Output $/Mtok$10.00$8.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computable$0.571
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4o (2024-08-06) better than o3 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4o (2024-08-06) for work measured by Aider polyglot or LiveCodeBench (Artificial Analysis run), where it leads.

Which is cheaper, GPT-4o (2024-08-06) or o3?

GPT-4o (2024-08-06) costs $2.50 per million input tokens and $10.00 per million output tokens; o3 costs $2.00 and $8.00. Cost per solved task is known for o3 only.

Which has the bigger context window, GPT-4o (2024-08-06) or o3?

o3, with 200K tokens against 128K.

How many benchmarks is the GPT-4o (2024-08-06) vs o3 comparison based on?

56 benchmarks have a result for both models as of October 22, 2026. GPT-4o (2024-08-06)'s coding index rests on 0 independent benchmarks and o3's on 0. Where only one model has a result, the page says so instead of naming a winner.

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