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R1 0528 vs GPT-4.1 Nano

R1 0528 leads GPT-4.1 Nano on the Artificial Analysis Intelligence Index, 13.1 to 7.8, and GPT-4.1 Nano costs 5.5x less per output token ($0.40 vs $2.18 per million). Updated October 22, 2026; 49 benchmarks have a result for both.

Replace R1 0528 Replace GPT-4.1 Nano
R1 0528DeepSeek
Coding
No data
Overall
46.8
Output $/M
$2.18
49
GPT-4.1 NanoOpenAI
Coding
No data
Overall
24.7
Output $/M
$0.40
0
vs boards won of 49 shared

R1 0528 or GPT-4.1 Nano: which to pick

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

Compare them on price, context and the boards below.

Model AR1 0528DeepSeekNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGPT-4.1 NanoOpenAINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
49
R1 0528 only
14
GPT-4.1 Nano only
22
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-4.1 Nano not benchmarked.
Widest category
Math, 35.4 points apart on average over 6 shared benchmarks.
Widest single gap
Aider polyglot: R1 0528 71.4% against GPT-4.1 Nano 8.9%, 62.5 points apart on a 0 to 100 scale.
Output price
R1 0528 $2.18 against GPT-4.1 Nano $0.40 per million output tokens, 5.5x apart.
Context window
R1 0528 takes 164K tokens, GPT-4.1 Nano 1.05M.

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-4.1 NanoTies
Coding60
Intelligence10
Agentic work10
Reasoning80
Math60
Knowledge50
Web design60
General160
All shared boards490
CodingLike-for-likeSix of these boards feed the Vibe Coding Index60
Coding benchmarks for R1 0528 and GPT-4.1 Nano
BenchmarkR1 0528GPT-4.1 NanoLeader
Aider polyglot71.4%8.9%R1 0528
AA Coding IndexNot measured11.1Only GPT-4.1 Nano measured
LiveCodeBench (Vals AI)Not measured42.7%Only GPT-4.1 Nano measured
LiveCodeBench (Artificial Analysis run)77.0%32.6%R1 0528
Terminal-Bench Hard (Artificial Analysis run)15.9%3.8%R1 0528
WeirdML41.6%19.0%R1 0528
ALE-Bench804.1Not measuredOnly R1 0528 measured
LMArena Text: coding14271306R1 0528
LMArena Text: software and IT14351305R1 0528
Neither model has a result on the other 34 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for R1 0528 and GPT-4.1 Nano
BenchmarkR1 0528GPT-4.1 NanoLeader
AA Intelligence Index13.17.8R1 0528
Epoch Capabilities IndexNot measured129.5Only GPT-4.1 Nano measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for R1 0528 and GPT-4.1 Nano
BenchmarkR1 0528GPT-4.1 NanoLeader
τ²-Bench Telecom36.5%17.3%R1 0528
METR time horizons53.8%Not measuredOnly R1 0528 measured
DeepResearch Bench35.1%Not measuredOnly R1 0528 measured
Berkeley Function Calling Leaderboard (BFCL)Not measured33.1%Only GPT-4.1 Nano 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 index80
Reasoning benchmarks for R1 0528 and GPT-4.1 Nano
BenchmarkR1 0528GPT-4.1 NanoLeader
GPQA DiamondNot measured50.8%Only GPT-4.1 Nano measured
MMMU Pro (Vals AI)Not measured55.0%Only GPT-4.1 Nano measured
GPQA Diamond (Artificial Analysis run)81.3%51.2%R1 0528
Humanity's Last Exam (Artificial Analysis run)15.8%3.8%R1 0528
GPQA Diamond (Epoch AI run)76.3%48.9%R1 0528
ARC-AGI21.2%0.0%R1 0528
ARC-AGI-21.1%0.0%R1 0528
SimpleBench40.8%Not measuredOnly R1 0528 measured
Chess puzzlesNot measured0.0%Only GPT-4.1 Nano measured
LMArena Text: hard prompts14151286R1 0528
LMArena Text: expert13941271R1 0528
LMArena Text: hard prompts in English14221293R1 0528
Kagi LLM BenchmarkNot measured33.3%Only GPT-4.1 Nano measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index60
Math benchmarks for R1 0528 and GPT-4.1 Nano
BenchmarkR1 0528GPT-4.1 NanoLeader
AIMENot measured26.5%Only GPT-4.1 Nano measured
MATH 500 (Vals AI)Not measured80.2%Only GPT-4.1 Nano measured
MGSM (Vals AI)Not measured69.3%Only GPT-4.1 Nano measured
AA Math Index76.024.0R1 0528
AIME 2025 (Artificial Analysis run)76.0%24.0%R1 0528
OTIS Mock AIME66.4%28.9%R1 0528
MATH level 596.6%70.0%R1 0528
LMArena Text: math14001274R1 0528
LMArena Text: mathematical work14151274R1 0528
MathArena12.9%Not measuredOnly R1 0528 measured
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
Knowledge benchmarks for R1 0528 and GPT-4.1 Nano
BenchmarkR1 0528GPT-4.1 NanoLeader
MMLU ProNot measured63.5%Only GPT-4.1 Nano measured
LegalBench (Vals AI)Not measured61.1%Only GPT-4.1 Nano measured
CorpFin (Vals AI)Not measured42.1%Only GPT-4.1 Nano measured
TaxEval (Vals AI)Not measured60.8%Only GPT-4.1 Nano measured
MortgageTax (Vals AI)Not measured52.8%Only GPT-4.1 Nano measured
MedQA (Vals AI)Not measured68.2%Only GPT-4.1 Nano measured
MMLU Pro (Artificial Analysis run)84.9%65.7%R1 0528
SimpleQA VerifiedNot measured6.0%Only GPT-4.1 Nano measured
LMArena Text: science14301297R1 0528
LMArena Text: medicine and healthcare14451276R1 0528
LMArena Text: legal and government14191300R1 0528
LMArena Text: business and finance14021267R1 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 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index60
Web design benchmarks for R1 0528 and GPT-4.1 Nano
BenchmarkR1 0528GPT-4.1 NanoLeader
Design Arena: websites1149973R1 0528
Design Arena: UI components1100913R1 0528
Design Arena: game dev1097970R1 0528
Design Arena: data viz1182891R1 0528
Design Arena: 3D1110924R1 0528
Design Arena: all code categories1138962R1 0528
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 index160
General benchmarks for R1 0528 and GPT-4.1 Nano
BenchmarkR1 0528GPT-4.1 NanoLeader
IFBench39.6%32.0%R1 0528
Long context reasoning (AA-LCR)55.7%20.3%R1 0528
DTBenchNot measured52.5%Only GPT-4.1 Nano measured
LMCANot measured5.5%Only GPT-4.1 Nano measured
Fiction.LiveBench75.0%25.0%R1 0528
Creative writing (Lech Mazur)81.9%Not measuredOnly R1 0528 measured
LMArena Text14281285R1 0528
LMArena Text: instruction following13821266R1 0528
LMArena Text: creative writing14051260R1 0528
LMArena VisionNot measured1063Only GPT-4.1 Nano measured
LMArena Text: English14371303R1 0528
LMArena Text: non-English14121260R1 0528
LMArena Text: Chinese14421270R1 0528
LMArena Text: German14041288R1 0528
LMArena Text: Japanese13911198R1 0528
LMArena Text: Korean1360Not measuredOnly R1 0528 measured
LMArena Text: French1417Not measuredOnly R1 0528 measured
LMArena Text: Spanish1411Not measuredOnly R1 0528 measured
LMArena Text: Russian14231261R1 0528
LMArena Text: Polish1428Not measuredOnly R1 0528 measured
LMArena Text: multi-turn14051277R1 0528
LMArena Text: longer queries13911283R1 0528
LMArena Text: writing and language14021261R1 0528
LMArena Text: entertainment and media14001243R1 0528
LMArena Vision: EnglishNot measured1101Only GPT-4.1 Nano measured
Neither model has a result on the other 23 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-4.1 Nano
BenchmarkR1 0528GPT-4.1 NanoLeader
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-4.1 Nano$0.0003Fits in one request

GPT-4.1 Nano costs less

Repository review

50K input + 3K output tokens

R1 0528$0.032Fits in one request
GPT-4.1 Nano$0.0062Fits in one request

GPT-4.1 Nano costs less

Agent loop

200K input + 10K output tokens

R1 0528$0.122Exceeds the context window
GPT-4.1 Nano$0.024Fits in one request

GPT-4.1 Nano 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-4.1 Nano
SpecificationDeepSeek R1 0528OpenAI GPT-4.1 Nano
MakerDeepSeekOpenAI
WeightsOpen weightsNo public weights listed
ReleasedMay 28, 2025April 14, 2025
Context window164K1.05M
Input $/Mtok$0.50$0.10
Output $/Mtok$2.18$0.40
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is R1 0528 better than GPT-4.1 Nano for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, R1 0528 or GPT-4.1 Nano?

R1 0528 costs $0.50 per million input tokens and $2.18 per million output tokens; GPT-4.1 Nano costs $0.10 and $0.40. Cost per solved task is known for neither of them.

Which has the bigger context window, R1 0528 or GPT-4.1 Nano?

GPT-4.1 Nano, with 1.05M tokens against 164K.

How many benchmarks is the R1 0528 vs GPT-4.1 Nano comparison based on?

49 benchmarks have a result for both models as of October 22, 2026. R1 0528's coding index rests on 0 independent benchmarks and GPT-4.1 Nano's on 0. Where only one model has a result, the page says so instead of naming a winner.

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