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R1 0528 vs Mercury 2

R1 0528 leads Mercury 2 on the Artificial Analysis Intelligence Index, 13.1 to 10.8, and Mercury 2 costs 2.9x less per output token ($0.75 vs $2.18 per million). Updated October 22, 2026; 35 benchmarks have a result for both.

R1 0528DeepSeek
Coding
No data
Overall
46.8
Output $/M
$2.18
30
Mercury 2Inception
Coding
No data
Overall
No data
Output $/M
$0.75
5
vs boards won of 35 shared

R1 0528 or Mercury 2: which to pick

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

Pick R1 0528 for a larger context window (164K against 128K tokens) and work measured by Terminal-Bench Hard (Artificial Analysis run) or WeirdML, where it leads.

Shared results
35
R1 0528 only
25
Mercury 2 only
7
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, Mercury 2 not benchmarked.
Widest category
Agentic work, 34.2 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: R1 0528 36.5% against Mercury 2 70.8%, 34.2 points apart on a 0 to 100 scale.
Output price
R1 0528 $2.18 against Mercury 2 $0.75 per million output tokens, 2.9x apart.
Context window
R1 0528 takes 164K tokens, Mercury 2 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 0528BarsMercury 2Ties
Coding32
Intelligence10
Agentic work01
Reasoning41
Knowledge30
Web design70
General121
All shared boards305
CodingLike-for-likeSix of these boards feed the Vibe Coding Index32
Coding benchmarks for R1 0528 and Mercury 2
BenchmarkR1 0528Mercury 2Leader
Aider polyglot71.4%Not measuredOnly R1 0528 measured
LMArena WebDevNot measured1171Only Mercury 2 measured
AA Coding IndexNot measured31.1Only Mercury 2 measured
LiveCodeBench (Artificial Analysis run)77.0%Not measuredOnly R1 0528 measured
SciCodeNot measured37.7%Only Mercury 2 measured
Terminal-Bench Hard (Artificial Analysis run)15.9%26.5%Mercury 2
WeirdML41.6%43.2%Mercury 2
ALE-Bench804.1785.6R1 0528
LMArena Text: coding14271390R1 0528
LMArena Text: software and IT14351385R1 0528
LMArena WebDev: ReactNot measured1160Only Mercury 2 measured
LMArena WebDev: HTMLNot measured1199Only Mercury 2 measured
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for R1 0528 and Mercury 2
BenchmarkR1 0528Mercury 2Leader
AA Intelligence Index13.110.8R1 0528
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 Mercury 2
BenchmarkR1 0528Mercury 2Leader
AA Agentic IndexNot measured1.6Only Mercury 2 measured
τ²-Bench Telecom36.5%70.8%Mercury 2
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 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index41
Reasoning benchmarks for R1 0528 and Mercury 2
BenchmarkR1 0528Mercury 2Leader
GPQA Diamond (Artificial Analysis run)81.3%77.0%R1 0528
Humanity's Last Exam (Artificial Analysis run)15.8%17.1%Mercury 2
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 prompts14151362R1 0528
LMArena Text: expert13941358R1 0528
LMArena Text: hard prompts in English14221374R1 0528
Neither model has a result on the other 13 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Math benchmarks for R1 0528 and Mercury 2
BenchmarkR1 0528Mercury 2Leader
AA Math Index76.0Not measuredOnly R1 0528 measured
AIME 2025 (Artificial Analysis run)76.0%Not measuredOnly R1 0528 measured
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 index30
Knowledge benchmarks for R1 0528 and Mercury 2
BenchmarkR1 0528Mercury 2Leader
MMLU Pro (Artificial Analysis run)84.9%Not measuredOnly R1 0528 measured
LMArena Text: science14301343R1 0528
LMArena Text: medicine and healthcare14451363R1 0528
LMArena Text: legal and government1419Not measuredOnly R1 0528 measured
LMArena Text: business and finance14021349R1 0528
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 Mercury 2
BenchmarkR1 0528Mercury 2Leader
Design Arena: websites11491036R1 0528
Design Arena: UI components1100996R1 0528
Design Arena: game dev1097984R1 0528
Design Arena: data viz11821009R1 0528
Design Arena: 3D1110982R1 0528
Design Arena: all code categories11381021R1 0528
Design Arena: SVG1038998R1 0528
Design Arena: ASCII artNot measured988Only Mercury 2 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index121
General benchmarks for R1 0528 and Mercury 2
BenchmarkR1 0528Mercury 2Leader
IFBench39.6%69.8%Mercury 2
Long context reasoning (AA-LCR)55.7%43.7%R1 0528
Fiction.LiveBench75.0%Not measuredOnly R1 0528 measured
Creative writing (Lech Mazur)81.9%Not measuredOnly R1 0528 measured
LMArena Text14281354R1 0528
LMArena Text: instruction following13821328R1 0528
LMArena Text: creative writing14051286R1 0528
LMArena Text: English14371378R1 0528
LMArena Text: non-English14121330R1 0528
LMArena Text: Chinese14421414R1 0528
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: Russian14231304R1 0528
LMArena Text: Polish1428Not measuredOnly R1 0528 measured
LMArena Text: multi-turn14051357R1 0528
LMArena Text: longer queries13911329R1 0528
LMArena Text: writing and language14021300R1 0528
LMArena Text: entertainment and media14001314R1 0528
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 Mercury 2
BenchmarkR1 0528Mercury 2Leader
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
Mercury 2$0.0006Fits in one request

Mercury 2 costs less

Repository review

50K input + 3K output tokens

R1 0528$0.032Fits in one request
Mercury 2$0.015Fits in one request

Mercury 2 costs less

Agent loop

200K input + 10K output tokens

R1 0528$0.122Exceeds the context window
Mercury 2$0.058Exceeds the context window

Mercury 2 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 Mercury 2
SpecificationDeepSeek R1 0528Inception Mercury 2
MakerDeepSeekInception
WeightsOpen weightsNo public weights listed
ReleasedMay 28, 2025March 4, 2026
Context window164K128K
Input $/Mtok$0.50$0.25
Output $/Mtok$2.18$0.75
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is R1 0528 better than Mercury 2 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick R1 0528 for a larger context window (164K against 128K tokens) and work measured by Terminal-Bench Hard (Artificial Analysis run) or WeirdML, where it leads.

Which is cheaper, R1 0528 or Mercury 2?

R1 0528 costs $0.50 per million input tokens and $2.18 per million output tokens; Mercury 2 costs $0.25 and $0.75. Cost per solved task is known for neither of them.

Which has the bigger context window, R1 0528 or Mercury 2?

R1 0528, with 164K tokens against 128K.

How many benchmarks is the R1 0528 vs Mercury 2 comparison based on?

35 benchmarks have a result for both models as of October 22, 2026. R1 0528's coding index rests on 0 independent benchmarks and Mercury 2's on 1. Where only one model has a result, the page says so instead of naming a winner.

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