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R1 0528 vs MiniMax M2.7

Updated October 21, 2026. 44 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace R1 0528 Replace MiniMax M2.7
R1 0528DeepSeek
Coding
71.4
Overall
13.1
Output $/M
$2.15
18
MiniMax M2.7MiniMax
Coding
28.4
Overall
22.8
Output $/M
$1.20
26
vs boards won of 44 shared

Decision reading

Pick R1 0528 for coding: it scores 71.4 on the Vibe Coding Index against 28.4 for MiniMax M2.7.

Pick MiniMax M2.7 when output tokens cost 1.8x less, or when the context window is larger, 205K against 164K tokens.

Model AR1 0528DeepSeek71.4/1001 independent benchmarkNo cost per solved taskModel BMiniMax M2.7MiniMax28.4/1001 independent benchmark$0.64 per solved task
Shared results
44
R1 0528 only
15
MiniMax M2.7 only
30
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
R1 0528 71.4 from 1 benchmark, MiniMax M2.7 28.4 from 1 benchmark.
Widest category
Agentic work, 48.2 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: R1 0528 36.5% against MiniMax M2.7 84.8%, 48.2 points apart on a 0 to 100 scale.
Output price
R1 0528 $2.15 against MiniMax M2.7 $1.20 per million output tokens, 1.8x apart.
Context window
R1 0528 takes 164K tokens, MiniMax M2.7 205K.

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 0528BarsMiniMax M2.7Ties
Coding23
Intelligence01
Agentic work01
Reasoning05
Math02
Knowledge31
Web design07
General136
All shared boards1826
CodingLike-for-likeFour of these boards feed the Vibe Coding Index23
Coding benchmarks for R1 0528 and MiniMax M2.7
BenchmarkR1 0528MiniMax M2.7Leader
Aider polyglot71.4%Not measuredOnly R1 0528 measured
LMArena WebDevNot measured1399Only MiniMax M2.7 measured
AA Coding IndexNot measured52.6Only MiniMax M2.7 measured
LiveCodeBench (Vals AI)Not measured79.9%Only MiniMax M2.7 measured
SWE-bench Verified (Vals AI)Not measured73.8%Only MiniMax M2.7 measured
Vibe Code Bench (Vals AI)Not measured11.9%Only MiniMax M2.7 measured
Code migration (Vals AI)Not measured8.7%Only MiniMax M2.7 measured
ProgramBench (Vals AI)Not measured0.0%Only MiniMax M2.7 measured
Terminal-Bench 2.1 (Vals AI)Not measured48.7%Only MiniMax M2.7 measured
LiveCodeBench (Artificial Analysis run)77.0%Not measuredOnly R1 0528 measured
SciCodeNot measured50.1%Only MiniMax M2.7 measured
Terminal-Bench Hard (Artificial Analysis run)15.9%39.4%MiniMax M2.7
Terminal-BenchNot measured45.1%Only MiniMax M2.7 measured
WeirdML41.6%37.0%R1 0528
ALE-Bench804.1599.3R1 0528
LMArena Text: coding14271454MiniMax M2.7
LMArena Text: software and IT14351446MiniMax M2.7
LMArena WebDev: ReactNot measured1388Only MiniMax M2.7 measured
LMArena WebDev: HTMLNot measured1401Only MiniMax M2.7 measured
Neither model has a result on the other 19 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for R1 0528 and MiniMax M2.7
BenchmarkR1 0528MiniMax M2.7Leader
AA Intelligence Index13.122.8MiniMax M2.7
Epoch Capabilities IndexNot measured145.8Only MiniMax M2.7 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for R1 0528 and MiniMax M2.7
BenchmarkR1 0528MiniMax M2.7Leader
AA Agentic IndexNot measured15.3Only MiniMax M2.7 measured
Finance Agent (Vals AI)Not measured27.9%Only MiniMax M2.7 measured
Tax Agent Bench (Vals AI)Not measured6.9%Only MiniMax M2.7 measured
Legal Research Bench (Vals AI)Not measured10.6%Only MiniMax M2.7 measured
Excel Modeling Benchmark (Vals AI)Not measured28.4%Only MiniMax M2.7 measured
τ²-Bench Telecom36.5%84.8%MiniMax M2.7
METR time horizons53.8%Not measuredOnly R1 0528 measured
DeepResearch Bench35.1%Not measuredOnly R1 0528 measured
Neither model has a result on the other 31 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for R1 0528 and MiniMax M2.7
BenchmarkR1 0528MiniMax M2.7Leader
GPQA DiamondNot measured86.6%Only MiniMax M2.7 measured
GPQA Diamond (Artificial Analysis run)81.3%87.4%MiniMax M2.7
Humanity's Last Exam (Artificial Analysis run)15.8%29.6%MiniMax M2.7
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 prompts14151422MiniMax M2.7
LMArena Text: expert13941443MiniMax M2.7
LMArena Text: hard prompts in English14221441MiniMax M2.7
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for R1 0528 and MiniMax M2.7
BenchmarkR1 0528MiniMax M2.7Leader
AIMENot measured91.0%Only MiniMax M2.7 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%Not measuredOnly R1 0528 measured
ProofBenchNot measured3.0%Only MiniMax M2.7 measured
MATH level 596.6%Not measuredOnly R1 0528 measured
LMArena Text: math14001421MiniMax M2.7
LMArena Text: mathematical work14151437MiniMax M2.7
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index31
Knowledge benchmarks for R1 0528 and MiniMax M2.7
BenchmarkR1 0528MiniMax M2.7Leader
MMLU ProNot measured80.4%Only MiniMax M2.7 measured
LegalBench (Vals AI)Not measured84.0%Only MiniMax M2.7 measured
CaseLaw (Vals AI)Not measured60.9%Only MiniMax M2.7 measured
CorpFin (Vals AI)Not measured61.2%Only MiniMax M2.7 measured
TaxEval (Vals AI)Not measured66.6%Only MiniMax M2.7 measured
MedCode (Vals AI)Not measured34.4%Only MiniMax M2.7 measured
MMLU Pro (Artificial Analysis run)84.9%Not measuredOnly R1 0528 measured
LMArena Text: science14301416R1 0528
LMArena Text: medicine and healthcare14451409R1 0528
LMArena Text: legal and government14191403R1 0528
LMArena Text: business and finance14021407MiniMax M2.7
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for R1 0528 and MiniMax M2.7
BenchmarkR1 0528MiniMax M2.7Leader
Design Arena: websites11491243MiniMax M2.7
Design Arena: UI components11021210MiniMax M2.7
Design Arena: game dev10981210MiniMax M2.7
Design Arena: data viz11821233MiniMax M2.7
Design Arena: 3D11111195MiniMax M2.7
Design Arena: all code categories11391233MiniMax M2.7
Design Arena: SVG10381136MiniMax M2.7
Design Arena: ASCII artNot measured1136Only MiniMax M2.7 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index136
General benchmarks for R1 0528 and MiniMax M2.7
BenchmarkR1 0528MiniMax M2.7Leader
MedScribe (Vals AI)Not measured79.9%Only MiniMax M2.7 measured
IFBench39.6%75.7%MiniMax M2.7
Long context reasoning (AA-LCR)55.7%78.3%MiniMax M2.7
Fiction.LiveBench75.0%Not measuredOnly R1 0528 measured
Creative writing (Lech Mazur)81.9%Not measuredOnly R1 0528 measured
ExploitBenchNot measured13.3%Only MiniMax M2.7 measured
LMArena Text14281405R1 0528
LMArena Text: instruction following13821405MiniMax M2.7
LMArena Text: creative writing14051354R1 0528
LMArena Text: English14371426R1 0528
LMArena Text: non-English14121382R1 0528
LMArena Text: Chinese14421442R1 0528
LMArena Text: German14041398R1 0528
LMArena Text: Japanese13911260R1 0528
LMArena Text: Korean13601314R1 0528
LMArena Text: French14171424MiniMax M2.7
LMArena Text: Spanish14111402R1 0528
LMArena Text: Russian14231383R1 0528
LMArena Text: Polish14281387R1 0528
LMArena Text: multi-turn14051412MiniMax M2.7
LMArena Text: longer queries13911418MiniMax M2.7
LMArena Text: writing and language14021376R1 0528
LMArena Text: entertainment and media14001360R1 0528
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 MiniMax M2.7
BenchmarkR1 0528MiniMax M2.7Leader
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
MiniMax M2.7$0.0009Fits in one request

MiniMax M2.7 costs less

Repository review

50K input + 3K output tokens

R1 0528$0.031Fits in one request
MiniMax M2.7$0.019Fits in one request

MiniMax M2.7 costs less

Agent loop

200K input + 10K output tokens

R1 0528$0.121Exceeds the context window
MiniMax M2.7$0.072Exceeds the context window

MiniMax M2.7 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 MiniMax M2.7
SpecificationDeepSeek R1 0528MiniMax M2.7
MakerDeepSeekMiniMax
WeightsOpen weightsOpen weights
ReleasedMay 28, 2025March 18, 2026
Context window164K205K
Input $/Mtok$0.50$0.30
Output $/Mtok$2.15$1.20
Coding index71.428.4
Independent measurements behind it11
Cost per solved taskNot computable$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is R1 0528 better than MiniMax M2.7 for coding?

Pick R1 0528 for coding: it scores 71.4 on the Vibe Coding Index against 28.4 for MiniMax M2.7. Pick MiniMax M2.7 when output tokens cost 1.8x less, or when the context window is larger, 205K against 164K tokens.

Which is cheaper, R1 0528 or MiniMax M2.7?

R1 0528 costs $0.50 per million input tokens and $2.15 per million output tokens; MiniMax M2.7 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M2.7 only.

Which has the bigger context window, R1 0528 or MiniMax M2.7?

MiniMax M2.7, with 205K tokens against 164K.

How many benchmarks is the R1 0528 vs MiniMax M2.7 comparison based on?

44 benchmarks have a result for both models as of October 21, 2026. R1 0528's coding index rests on 1 independent benchmark and MiniMax M2.7's on 1. Where only one model has a result, the page says so instead of naming a winner.

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