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R1 0528 vs GPT-4o (2024-08-06)

R1 0528 leads GPT-4o (2024-08-06) on the Artificial Analysis Intelligence Index, 13.1 to 7.7, and R1 0528 costs 4.6x less per output token ($2.18 vs $10.00 per million). Updated October 22, 2026; 40 benchmarks have a result for both.

Replace R1 0528 Replace GPT-4o (2024-08-06)
R1 0528DeepSeek
Coding
No data
Overall
46.8
Output $/M
$2.18
40
GPT-4o (2024-08-06)OpenAI
Coding
No data
Overall
26.3
Output $/M
$10.00
0
vs boards won of 40 shared

R1 0528 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 R1 0528 for output tokens 4.6x cheaper ($2.18 vs $10.00 per million) and a larger context window (164K against 128K tokens).

Model AR1 0528DeepSeekNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGPT-4o (2024-08-06)OpenAINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
40
R1 0528 only
23
GPT-4o (2024-08-06) only
18
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
R1 0528 not benchmarked, GPT-4o (2024-08-06) not benchmarked.
Widest category
Math, 36.1 points apart on average over 4 shared benchmarks.
Widest single gap
OTIS Mock AIME: R1 0528 66.4% against GPT-4o (2024-08-06) 6.4%, 60.0 points apart on a 0 to 100 scale.
Output price
R1 0528 $2.18 against GPT-4o (2024-08-06) $10.00 per million output tokens, 4.6x apart.
Context window
R1 0528 takes 164K 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.

Boards won, where both have a result
CategoryR1 0528BarsGPT-4o (2024-08-06)Ties
Coding50
Intelligence10
Agentic work10
Reasoning70
Math40
Knowledge40
General180
All shared boards400
CodingLike-for-likeSix of these boards feed the Vibe Coding Index50
Coding benchmarks for R1 0528 and GPT-4o (2024-08-06)
BenchmarkR1 0528GPT-4o (2024-08-06)Leader
Aider polyglot71.4%23.1%R1 0528
SWE-bench LiteNot measured21.7%Only GPT-4o (2024-08-06) measured
LiveCodeBench (Artificial Analysis run)77.0%31.7%R1 0528
Terminal-Bench Hard (Artificial Analysis run)15.9%8.3%R1 0528
WeirdML41.6%Not measuredOnly R1 0528 measured
ALE-Bench804.1Not measuredOnly R1 0528 measured
LMArena Text: coding14271283R1 0528
LMArena Text: software and IT14351278R1 0528
Neither model has a result on the other 35 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for R1 0528 and GPT-4o (2024-08-06)
BenchmarkR1 0528GPT-4o (2024-08-06)Leader
AA Intelligence Index13.17.7R1 0528
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for R1 0528 and GPT-4o (2024-08-06)
BenchmarkR1 0528GPT-4o (2024-08-06)Leader
τ²-Bench Telecom36.5%28.9%R1 0528
METR time horizons53.8%Not measuredOnly R1 0528 measured
DeepResearch Bench35.1%Not measuredOnly R1 0528 measured
BrowseComp-Plus16.4%Not measuredOnly R1 0528 measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index70
Reasoning benchmarks for R1 0528 and GPT-4o (2024-08-06)
BenchmarkR1 0528GPT-4o (2024-08-06)Leader
MMMU Pro (Vals AI)Not measured64.0%Only GPT-4o (2024-08-06) measured
GPQA Diamond (Artificial Analysis run)81.3%52.1%R1 0528
Humanity's Last Exam (Artificial Analysis run)15.8%2.3%R1 0528
GPQA Diamond (Epoch AI run)76.3%49.2%R1 0528
ARC-AGI21.2%Not measuredOnly R1 0528 measured
ARC-AGI-21.1%Not measuredOnly R1 0528 measured
SimpleBench40.8%17.8%R1 0528
Chess puzzlesNot measured6.0%Only GPT-4o (2024-08-06) measured
LMArena Text: hard prompts14151264R1 0528
LMArena Text: expert13941241R1 0528
LMArena Text: hard prompts in English14221277R1 0528
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index40
Math benchmarks for R1 0528 and GPT-4o (2024-08-06)
BenchmarkR1 0528GPT-4o (2024-08-06)Leader
AIMENot measured14.0%Only GPT-4o (2024-08-06) measured
MATH 500 (Vals AI)Not measured75.2%Only GPT-4o (2024-08-06) measured
MGSM (Vals AI)Not measured90.7%Only GPT-4o (2024-08-06) measured
AA Math Index76.0Not measuredOnly R1 0528 measured
AIME 2025 (Artificial Analysis run)76.0%Not measuredOnly R1 0528 measured
OTIS Mock AIME66.4%6.4%R1 0528
FrontierMath, tiers 1 to 3Not measured0.4%Only GPT-4o (2024-08-06) measured
MATH level 596.6%53.3%R1 0528
LMArena Text: math14001285R1 0528
LMArena Text: mathematical work14151283R1 0528
MathArena12.9%Not measuredOnly R1 0528 measured
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for R1 0528 and GPT-4o (2024-08-06)
BenchmarkR1 0528GPT-4o (2024-08-06)Leader
MMLU ProNot measured74.1%Only GPT-4o (2024-08-06) measured
LegalBench (Vals AI)Not measured80.1%Only GPT-4o (2024-08-06) measured
CorpFin (Vals AI)Not measured39.4%Only GPT-4o (2024-08-06) measured
TaxEval (Vals AI)Not measured71.1%Only GPT-4o (2024-08-06) measured
MortgageTax (Vals AI)Not measured61.0%Only GPT-4o (2024-08-06) measured
MedQA (Vals AI)Not measured88.2%Only GPT-4o (2024-08-06) measured
MMLU Pro (Artificial Analysis run)84.9%Not measuredOnly R1 0528 measured
SimpleQA VerifiedNot measured26.0%Only GPT-4o (2024-08-06) measured
MMLUNot measured84.3%Only GPT-4o (2024-08-06) measured
LMArena Text: science14301274R1 0528
LMArena Text: medicine and healthcare14451252R1 0528
LMArena Text: legal and government14191275R1 0528
LMArena Text: business and finance14021232R1 0528
PRBench Finance32.7%Not measuredOnly R1 0528 measured
PRBench Legal36.6%Not measuredOnly R1 0528 measured
Neither model has a result on the other 5 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for R1 0528 and GPT-4o (2024-08-06)
BenchmarkR1 0528GPT-4o (2024-08-06)Leader
Design Arena: websites1149Not measuredOnly R1 0528 measured
Design Arena: UI components1100Not measuredOnly R1 0528 measured
Design Arena: game dev1097Not measuredOnly R1 0528 measured
Design Arena: data viz1182Not measuredOnly R1 0528 measured
Design Arena: 3D1110Not measuredOnly R1 0528 measured
Design Arena: all code categories1138Not measuredOnly R1 0528 measured
Design Arena: SVG1038Not measuredOnly R1 0528 measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
General benchmarks for R1 0528 and GPT-4o (2024-08-06)
BenchmarkR1 0528GPT-4o (2024-08-06)Leader
IFBench39.6%36.0%R1 0528
Long context reasoning (AA-LCR)55.7%41.0%R1 0528
Fiction.LiveBench75.0%Not measuredOnly R1 0528 measured
Creative writing (Lech Mazur)81.9%Not measuredOnly R1 0528 measured
LMArena Text14281283R1 0528
LMArena Text: instruction following13821267R1 0528
LMArena Text: creative writing14051274R1 0528
LMArena VisionNot measured1065Only GPT-4o (2024-08-06) measured
LMArena Text: English14371297R1 0528
LMArena Text: non-English14121262R1 0528
LMArena Text: Chinese14421254R1 0528
LMArena Text: German14041257R1 0528
LMArena Text: Japanese13911234R1 0528
LMArena Text: Korean13601218R1 0528
LMArena Text: French14171263R1 0528
LMArena Text: Spanish14111269R1 0528
LMArena Text: Russian14231272R1 0528
LMArena Text: Polish1428Not measuredOnly R1 0528 measured
LMArena Text: multi-turn14051279R1 0528
LMArena Text: longer queries13911283R1 0528
LMArena Text: writing and language14021290R1 0528
LMArena Text: entertainment and media14001267R1 0528
LMArena Vision: EnglishNot measured1072Only GPT-4o (2024-08-06) measured
LMArena Vision: ChineseNot measured1009Only GPT-4o (2024-08-06) measured
Neither model has a result on the other 24 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for R1 0528 and GPT-4o (2024-08-06)
BenchmarkR1 0528GPT-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

R1 0528$0.0016Fits in one request
GPT-4o (2024-08-06)$0.0075Fits in one request

R1 0528 costs less

Repository review

50K input + 3K output tokens

R1 0528$0.032Fits in one request
GPT-4o (2024-08-06)$0.155Fits in one request

R1 0528 costs less

Agent loop

200K input + 10K output tokens

R1 0528$0.122Exceeds the context window
GPT-4o (2024-08-06)$0.600Exceeds the context window

R1 0528 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 R1 0528 and GPT-4o (2024-08-06)
SpecificationDeepSeek R1 0528OpenAI GPT-4o (2024-08-06)
MakerDeepSeekOpenAI
WeightsOpen weightsNo public weights listed
ReleasedMay 28, 2025August 6, 2024
Context window164K128K
Input $/Mtok$0.50$2.50
Output $/Mtok$2.18$10.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is R1 0528 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 R1 0528 for output tokens 4.6x cheaper ($2.18 vs $10.00 per million) and a larger context window (164K against 128K tokens).

Which is cheaper, R1 0528 or GPT-4o (2024-08-06)?

R1 0528 costs $0.50 per million input tokens and $2.18 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, R1 0528 or GPT-4o (2024-08-06)?

R1 0528, with 164K tokens against 128K.

How many benchmarks is the R1 0528 vs GPT-4o (2024-08-06) comparison based on?

40 benchmarks have a result for both models as of October 22, 2026. R1 0528'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.

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