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Claude Sonnet 4.5 vs R1 0528

Updated October 21, 2026. 45 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Claude Sonnet 4.5Anthropic
Coding
59.1
Overall
20.7
Output $/M
$15.00
41
R1 0528DeepSeek
Coding
71.4
Overall
13.1
Output $/M
$2.15
4
vs boards won of 45 shared

Decision reading

Pick R1 0528 for coding: it scores 71.4 on the Vibe Coding Index against 59.1 for Claude Sonnet 4.5, though on 1 benchmark against 2.

Pick Claude Sonnet 4.5 when the context window is larger, 1M against 164K tokens, or when what matters is WeirdML or LMArena Text: coding, where it leads.

Shared results
45
Claude Sonnet 4.5 only
47
R1 0528 only
14
Like-for-like categories
8 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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
Claude Sonnet 4.5 59.1 from 2 benchmarks, R1 0528 71.4 from 1 benchmark.
Widest category
Agentic work, 15.6 points apart on average over 2 shared benchmarks.
Widest single gap
ARC-AGI: Claude Sonnet 4.5 63.7% against R1 0528 21.2%, 42.5 points apart on a 0 to 100 scale.
Output price
Claude Sonnet 4.5 $15.00 against R1 0528 $2.15 per million output tokens, 7.0x apart.
Context window
Claude Sonnet 4.5 takes 1M tokens, R1 0528 164K.

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
CategoryClaude Sonnet 4.5BarsR1 0528Ties
Coding30
Intelligence10
Agentic work20
Reasoning70
Math40
Knowledge31
Web design61
General152
All shared boards414
CodingLike-for-likeFour of these boards feed the Vibe Coding Index30
Coding benchmarks for Claude Sonnet 4.5 and R1 0528
BenchmarkClaude Sonnet 4.5R1 0528Leader
Aider polyglotNot measured71.4%Only R1 0528 measured
SWE-bench Verified74.8%Not measuredOnly Claude Sonnet 4.5 measured
SWE-bench Multilingual67.0%Not measuredOnly Claude Sonnet 4.5 measured
LMArena WebDev1394Not measuredOnly Claude Sonnet 4.5 measured
AA Coding Index52.1Not measuredOnly Claude Sonnet 4.5 measured
LiveCodeBench (Vals AI)73.0%Not measuredOnly Claude Sonnet 4.5 measured
SWE-bench Verified (Vals AI)70.0%Not measuredOnly Claude Sonnet 4.5 measured
Vibe Code Bench (Vals AI)22.6%Not measuredOnly Claude Sonnet 4.5 measured
LiveCodeBench (Artificial Analysis run)Not measured77.0%Only R1 0528 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured15.9%Only R1 0528 measured
Terminal-Bench46.5%Not measuredOnly Claude Sonnet 4.5 measured
GSO-Bench14.7%Not measuredOnly Claude Sonnet 4.5 measured
WeirdML47.7%41.6%Claude Sonnet 4.5
Cybench60.0%Not measuredOnly Claude Sonnet 4.5 measured
ALE-BenchNot measured804.1Only R1 0528 measured
LMArena Text: coding14881427Claude Sonnet 4.5
LMArena Text: software and IT14731435Claude Sonnet 4.5
LMArena WebDev: React1386Not measuredOnly Claude Sonnet 4.5 measured
LMArena WebDev: HTML1399Not measuredOnly Claude Sonnet 4.5 measured
Neither model has a result on the other 19 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Claude Sonnet 4.5 and R1 0528
BenchmarkClaude Sonnet 4.5R1 0528Leader
AA Intelligence Index20.713.1Claude Sonnet 4.5
Epoch Capabilities Index146.7Not measuredOnly Claude Sonnet 4.5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
Agentic work benchmarks for Claude Sonnet 4.5 and R1 0528
BenchmarkClaude Sonnet 4.5R1 0528Leader
AA Agentic Index15.8Not measuredOnly Claude Sonnet 4.5 measured
Design Arena: agents building web apps1060Not measuredOnly Claude Sonnet 4.5 measured
Design Arena: agents building full-stack apps1050Not measuredOnly Claude Sonnet 4.5 measured
Design Arena: agents building mobile apps1137Not measuredOnly Claude Sonnet 4.5 measured
τ²-Bench TelecomNot measured36.5%Only R1 0528 measured
METR time horizons67.4%53.8%Claude Sonnet 4.5
Remote Labor Index2.1%Not measuredOnly Claude Sonnet 4.5 measured
GDPval42.5%Not measuredOnly Claude Sonnet 4.5 measured
DeepResearch Bench52.6%35.1%Claude Sonnet 4.5
OSWorld62.9%Not measuredOnly Claude Sonnet 4.5 measured
Vending-Bench 2$3,839Not measuredOnly Claude Sonnet 4.5 measured
Neither model has a result on the other 28 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index70
Reasoning benchmarks for Claude Sonnet 4.5 and R1 0528
BenchmarkClaude Sonnet 4.5R1 0528Leader
GPQA Diamond81.6%Not measuredOnly Claude Sonnet 4.5 measured
MMMU Pro (Vals AI)79.3%Not measuredOnly Claude Sonnet 4.5 measured
GPQA Diamond (Artificial Analysis run)Not measured81.3%Only R1 0528 measured
Humanity's Last Exam (Artificial Analysis run)Not measured15.8%Only R1 0528 measured
GPQA Diamond (Epoch AI run)82.3%76.3%Claude Sonnet 4.5
ARC-AGI63.7%21.2%Claude Sonnet 4.5
ARC-AGI-213.6%1.1%Claude Sonnet 4.5
SimpleBench54.3%40.8%Claude Sonnet 4.5
Chess puzzles10.0%Not measuredOnly Claude Sonnet 4.5 measured
Mystery game puzzles17.0%Not measuredOnly Claude Sonnet 4.5 measured
EBR-bench2.4%Not measuredOnly Claude Sonnet 4.5 measured
VPCT39.8%Not measuredOnly Claude Sonnet 4.5 measured
LMArena Text: hard prompts14621415Claude Sonnet 4.5
LMArena Text: expert14831394Claude Sonnet 4.5
LMArena Text: hard prompts in English14711422Claude Sonnet 4.5
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index40
Math benchmarks for Claude Sonnet 4.5 and R1 0528
BenchmarkClaude Sonnet 4.5R1 0528Leader
AIME88.2%Not measuredOnly Claude Sonnet 4.5 measured
MGSM (Vals AI)94.3%Not measuredOnly Claude Sonnet 4.5 measured
AA Math IndexNot measured76.0Only R1 0528 measured
AIME 2025 (Artificial Analysis run)Not measured76.0%Only R1 0528 measured
OTIS Mock AIME77.8%66.4%Claude Sonnet 4.5
FrontierMath, tiers 1 to 323.9%Not measuredOnly Claude Sonnet 4.5 measured
FrontierMath, tier 42.4%Not measuredOnly Claude Sonnet 4.5 measured
ProofBench19.0%Not measuredOnly Claude Sonnet 4.5 measured
MATH level 597.7%96.6%Claude Sonnet 4.5
LMArena Text: math14491400Claude Sonnet 4.5
LMArena Text: mathematical work14621415Claude Sonnet 4.5
Neither model has a result on the other 2 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index31
Knowledge benchmarks for Claude Sonnet 4.5 and R1 0528
BenchmarkClaude Sonnet 4.5R1 0528Leader
MMLU Pro87.4%Not measuredOnly Claude Sonnet 4.5 measured
LegalBench (Vals AI)84.1%Not measuredOnly Claude Sonnet 4.5 measured
CaseLaw (Vals AI)62.2%Not measuredOnly Claude Sonnet 4.5 measured
CorpFin (Vals AI)62.0%Not measuredOnly Claude Sonnet 4.5 measured
TaxEval (Vals AI)73.3%Not measuredOnly Claude Sonnet 4.5 measured
MortgageTax (Vals AI)64.0%Not measuredOnly Claude Sonnet 4.5 measured
MedQA (Vals AI)94.7%Not measuredOnly Claude Sonnet 4.5 measured
MedCode (Vals AI)44.1%Not measuredOnly Claude Sonnet 4.5 measured
MMLU Pro (Artificial Analysis run)Not measured84.9%Only R1 0528 measured
SimpleQA Verified30.7%Not measuredOnly Claude Sonnet 4.5 measured
LMArena Text: science14481430Claude Sonnet 4.5
LMArena Text: medicine and healthcare14441445R1 0528
LMArena Text: legal and government14511419Claude Sonnet 4.5
LMArena Text: business and finance14401402Claude Sonnet 4.5
Neither model has a result on the other 3 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index61
Web design benchmarks for Claude Sonnet 4.5 and R1 0528
BenchmarkClaude Sonnet 4.5R1 0528Leader
Design Arena: websites11901149Claude Sonnet 4.5
Design Arena: UI components11731102Claude Sonnet 4.5
Design Arena: game dev11661098Claude Sonnet 4.5
Design Arena: data viz11671182R1 0528
Design Arena: 3D11581111Claude Sonnet 4.5
Design Arena: all code categories11831139Claude Sonnet 4.5
Design Arena: SVG11141038Claude Sonnet 4.5
Design Arena: ASCII art1204Not measuredOnly Claude Sonnet 4.5 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index152
General benchmarks for Claude Sonnet 4.5 and R1 0528
BenchmarkClaude Sonnet 4.5R1 0528Leader
SAGE (Vals AI)36.1%Not measuredOnly Claude Sonnet 4.5 measured
MedScribe (Vals AI)84.5%Not measuredOnly Claude Sonnet 4.5 measured
IFBenchNot measured39.6%Only R1 0528 measured
Long context reasoning (AA-LCR)Not measured55.7%Only R1 0528 measured
DTBench83.2%Not measuredOnly Claude Sonnet 4.5 measured
LMCA38.8%Not measuredOnly Claude Sonnet 4.5 measured
Fiction.LiveBenchNot measured75.0%Only R1 0528 measured
Creative writing (Lech Mazur)Not measured81.9%Only R1 0528 measured
LMArena Text14381428Claude Sonnet 4.5
LMArena Text: instruction following14591382Claude Sonnet 4.5
LMArena Text: creative writing14421405Claude Sonnet 4.5
LMArena Text: English14501437Claude Sonnet 4.5
LMArena Text: non-English14251412Claude Sonnet 4.5
LMArena Text: Chinese14601442Claude Sonnet 4.5
LMArena Text: German14271404Claude Sonnet 4.5
LMArena Text: Japanese13901391R1 0528
LMArena Text: Korean14021360Claude Sonnet 4.5
LMArena Text: French14591417Claude Sonnet 4.5
LMArena Text: Spanish14581411Claude Sonnet 4.5
LMArena Text: Russian14371423Claude Sonnet 4.5
LMArena Text: Polish14231428R1 0528
LMArena Text: multi-turn14651405Claude Sonnet 4.5
LMArena Text: longer queries14751391Claude Sonnet 4.5
LMArena Text: writing and language14421402Claude Sonnet 4.5
LMArena Text: entertainment and media14281400Claude Sonnet 4.5
LMArena Document1450Not measuredOnly Claude Sonnet 4.5 measured
Neither model has a result on the other 20 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Sonnet 4.5 and R1 0528
BenchmarkClaude Sonnet 4.5R1 0528Leader
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

Claude Sonnet 4.5$0.011Fits in one request
R1 0528$0.0016Fits in one request

R1 0528 costs less

Repository review

50K input + 3K output tokens

Claude Sonnet 4.5$0.195Fits in one request
R1 0528$0.031Fits in one request

R1 0528 costs less

Agent loop

200K input + 10K output tokens

Claude Sonnet 4.5$0.750Fits in one request
R1 0528$0.121Exceeds 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 Claude Sonnet 4.5 and R1 0528
SpecificationAnthropic Claude Sonnet 4.5DeepSeek R1 0528
MakerAnthropicDeepSeek
WeightsNo public weights listedOpen weights
ReleasedSeptember 29, 2025May 28, 2025
Context window1M164K
Input $/Mtok$3.00$0.50
Output $/Mtok$15.00$2.15
Coding index59.171.4
Independent measurements behind it21
Cost per solved task$1.16Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Sonnet 4.5 better than R1 0528 for coding?

Pick R1 0528 for coding: it scores 71.4 on the Vibe Coding Index against 59.1 for Claude Sonnet 4.5, though on 1 benchmark against 2. Pick Claude Sonnet 4.5 when the context window is larger, 1M against 164K tokens, or when what matters is WeirdML or LMArena Text: coding, where it leads.

Which is cheaper, Claude Sonnet 4.5 or R1 0528?

Claude Sonnet 4.5 costs $3.00 per million input tokens and $15.00 per million output tokens; R1 0528 costs $0.50 and $2.15. Cost per solved task is known for Claude Sonnet 4.5 only.

Which has the bigger context window, Claude Sonnet 4.5 or R1 0528?

Claude Sonnet 4.5, with 1M tokens against 164K.

How many benchmarks is the Claude Sonnet 4.5 vs R1 0528 comparison based on?

45 benchmarks have a result for both models as of October 21, 2026. Claude Sonnet 4.5's coding index rests on 2 independent benchmarks and R1 0528's on 1. Where only one model has a result, the page says so instead of naming a winner.

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