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R1 0528 vs GPT-5.1-Codex-Mini

GPT-5.1-Codex-Mini leads R1 0528 on the Artificial Analysis Intelligence Index, 20.4 to 13.1, at about the same output price ($2.00 vs $2.18 per million). Updated October 22, 2026; 18 benchmarks have a result for both.

Replace R1 0528 Replace GPT-5.1-Codex-Mini
R1 0528DeepSeek
Coding
No data
Overall
46.8
Output $/M
$2.18
8
GPT-5.1-Codex-MiniOpenAI
Coding
No data
Overall
No data
Output $/M
$2.00
9
vs boards won of 18 shared, 1 tied

R1 0528 or GPT-5.1-Codex-Mini: which to pick

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

Pick R1 0528 for work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Model AR1 0528DeepSeekNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGPT-5.1-Codex-MiniOpenAINot benchmarked1 independent benchmarkNo cost per solved task
Shared results
18
R1 0528 only
42
GPT-5.1-Codex-Mini only
4
Like-for-like categories
8 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-5.1-Codex-Mini not benchmarked.
Widest category
Agentic work, 26.3 points apart on average over 1 shared benchmark.
Widest single gap
IFBench: R1 0528 39.6% against GPT-5.1-Codex-Mini 67.9%, 28.3 points apart on a 0 to 100 scale.
Output price
R1 0528 $2.18 against GPT-5.1-Codex-Mini $2.00 per million output tokens, 1.1x apart.
Context window
R1 0528 takes 164K tokens, GPT-5.1-Codex-Mini 400K.

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-5.1-Codex-MiniTies
Coding02
Intelligence01
Agentic work01
Reasoning011 tie
Math02
Knowledge10
Web design70
General02
All shared boards891 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for R1 0528 and GPT-5.1-Codex-Mini
BenchmarkR1 0528GPT-5.1-Codex-MiniLeader
Aider polyglot71.4%Not measuredOnly R1 0528 measured
LMArena WebDevNot measured1244Only GPT-5.1-Codex-Mini measured
LiveCodeBench (Artificial Analysis run)77.0%83.6%GPT-5.1-Codex-Mini
Terminal-Bench Hard (Artificial Analysis run)15.9%33.3%GPT-5.1-Codex-Mini
Terminal-BenchNot measured61.6%Only GPT-5.1-Codex-Mini measured
WeirdML41.6%Not measuredOnly R1 0528 measured
ALE-Bench804.1Not measuredOnly R1 0528 measured
LMArena Text: coding1427Not measuredOnly R1 0528 measured
LMArena Text: software and IT1435Not measuredOnly R1 0528 measured
LMArena WebDev: HTMLNot measured1253Only GPT-5.1-Codex-Mini measured
Neither model has a result on the other 29 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for R1 0528 and GPT-5.1-Codex-Mini
BenchmarkR1 0528GPT-5.1-Codex-MiniLeader
AA Intelligence Index13.120.4GPT-5.1-Codex-Mini
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for R1 0528 and GPT-5.1-Codex-Mini
BenchmarkR1 0528GPT-5.1-Codex-MiniLeader
τ²-Bench Telecom36.5%62.9%GPT-5.1-Codex-Mini
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 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
Reasoning benchmarks for R1 0528 and GPT-5.1-Codex-Mini
BenchmarkR1 0528GPT-5.1-Codex-MiniLeader
GPQA Diamond (Artificial Analysis run)81.3%81.3%Tie
Humanity's Last Exam (Artificial Analysis run)15.8%18.5%GPT-5.1-Codex-Mini
GPQA Diamond (Epoch AI run)76.3%Not measuredOnly R1 0528 measured
ARC-AGI21.2%Not measuredOnly R1 0528 measured
ARC-AGI-21.1%Not measuredOnly R1 0528 measured
SimpleBench40.8%Not measuredOnly R1 0528 measured
LMArena Text: hard prompts1415Not measuredOnly R1 0528 measured
LMArena Text: expert1394Not measuredOnly R1 0528 measured
LMArena Text: hard prompts in English1422Not measuredOnly R1 0528 measured
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for R1 0528 and GPT-5.1-Codex-Mini
BenchmarkR1 0528GPT-5.1-Codex-MiniLeader
AA Math Index76.091.7GPT-5.1-Codex-Mini
AIME 2025 (Artificial Analysis run)76.0%91.7%GPT-5.1-Codex-Mini
OTIS Mock AIME66.4%Not measuredOnly R1 0528 measured
MATH level 596.6%Not measuredOnly R1 0528 measured
LMArena Text: math1400Not measuredOnly R1 0528 measured
LMArena Text: mathematical work1415Not measuredOnly R1 0528 measured
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for R1 0528 and GPT-5.1-Codex-Mini
BenchmarkR1 0528GPT-5.1-Codex-MiniLeader
MMLU Pro (Artificial Analysis run)84.9%82.0%R1 0528
LMArena Text: science1430Not measuredOnly R1 0528 measured
LMArena Text: medicine and healthcare1445Not measuredOnly R1 0528 measured
LMArena Text: legal and government1419Not measuredOnly R1 0528 measured
LMArena Text: business and finance1402Not measuredOnly R1 0528 measured
Neither model has a result on the other 13 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index70
Web design benchmarks for R1 0528 and GPT-5.1-Codex-Mini
BenchmarkR1 0528GPT-5.1-Codex-MiniLeader
Design Arena: websites11491111R1 0528
Design Arena: UI components11001078R1 0528
Design Arena: game dev10971092R1 0528
Design Arena: data viz11821097R1 0528
Design Arena: 3D1110988R1 0528
Design Arena: all code categories11381093R1 0528
Design Arena: SVG1038978R1 0528
Design Arena: ASCII artNot measured1105Only GPT-5.1-Codex-Mini measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
General benchmarks for R1 0528 and GPT-5.1-Codex-Mini
BenchmarkR1 0528GPT-5.1-Codex-MiniLeader
IFBench39.6%67.9%GPT-5.1-Codex-Mini
Long context reasoning (AA-LCR)55.7%66.7%GPT-5.1-Codex-Mini
Fiction.LiveBench75.0%Not measuredOnly R1 0528 measured
Creative writing (Lech Mazur)81.9%Not measuredOnly R1 0528 measured
LMArena Text1428Not measuredOnly R1 0528 measured
LMArena Text: instruction following1382Not measuredOnly R1 0528 measured
LMArena Text: creative writing1405Not measuredOnly R1 0528 measured
LMArena Text: English1437Not measuredOnly R1 0528 measured
LMArena Text: non-English1412Not measuredOnly R1 0528 measured
LMArena Text: Chinese1442Not measuredOnly R1 0528 measured
LMArena Text: German1404Not measuredOnly R1 0528 measured
LMArena Text: Japanese1391Not measuredOnly R1 0528 measured
LMArena Text: Korean1360Not measuredOnly R1 0528 measured
LMArena Text: French1417Not measuredOnly R1 0528 measured
LMArena Text: Spanish1411Not measuredOnly R1 0528 measured
LMArena Text: Russian1423Not measuredOnly R1 0528 measured
LMArena Text: Polish1428Not measuredOnly R1 0528 measured
LMArena Text: multi-turn1405Not measuredOnly R1 0528 measured
LMArena Text: longer queries1391Not measuredOnly R1 0528 measured
LMArena Text: writing and language1402Not measuredOnly R1 0528 measured
LMArena Text: entertainment and media1400Not measuredOnly R1 0528 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
Image generation benchmarks for R1 0528 and GPT-5.1-Codex-Mini
BenchmarkR1 0528GPT-5.1-Codex-MiniLeader
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-5.1-Codex-Mini$0.0013Fits in one request

GPT-5.1-Codex-Mini costs less

Repository review

50K input + 3K output tokens

R1 0528$0.032Fits in one request
GPT-5.1-Codex-Mini$0.018Fits in one request

GPT-5.1-Codex-Mini costs less

Agent loop

200K input + 10K output tokens

R1 0528$0.122Exceeds the context window
GPT-5.1-Codex-Mini$0.070Fits in one request

GPT-5.1-Codex-Mini 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-5.1-Codex-Mini
SpecificationDeepSeek R1 0528OpenAI GPT-5.1-Codex-Mini
MakerDeepSeekOpenAI
WeightsOpen weightsNo public weights listed
ReleasedMay 28, 2025November 13, 2025
Context window164K400K
Input $/Mtok$0.50$0.25
Output $/Mtok$2.18$2.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is R1 0528 better than GPT-5.1-Codex-Mini for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick R1 0528 for work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Which is cheaper, R1 0528 or GPT-5.1-Codex-Mini?

R1 0528 costs $0.50 per million input tokens and $2.18 per million output tokens; GPT-5.1-Codex-Mini costs $0.25 and $2.00. Cost per solved task is known for neither of them.

Which has the bigger context window, R1 0528 or GPT-5.1-Codex-Mini?

GPT-5.1-Codex-Mini, with 400K tokens against 164K.

How many benchmarks is the R1 0528 vs GPT-5.1-Codex-Mini comparison based on?

18 benchmarks have a result for both models as of October 22, 2026. R1 0528's coding index rests on 0 independent benchmarks and GPT-5.1-Codex-Mini's on 1. Where only one model has a result, the page says so instead of naming a winner.

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