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R1 0528 vs Mistral Medium 3.1

R1 0528 leads Mistral Medium 3.1 on the Artificial Analysis Intelligence Index, 13.1 to 9.2, at about the same output price ($2.18 vs $2.00 per million). Updated October 22, 2026; 47 benchmarks have a result for both.

Replace R1 0528 Replace Mistral Medium 3.1
R1 0528DeepSeek
Coding
No data
Overall
46.8
Output $/M
$2.18
25
Mistral Medium 3.1Mistral AI
Coding
No data
Overall
No data
Output $/M
$2.00
22
vs boards won of 47 shared

R1 0528 or Mistral Medium 3.1: 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 131K tokens) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Model AR1 0528DeepSeekNot benchmarkedNo coding benchmarkNo cost per solved taskModel BMistral Medium 3.1Mistral AINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
47
R1 0528 only
13
Mistral Medium 3.1 only
27
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, Mistral Medium 3.1 not benchmarked.
Widest category
Math, 19.3 points apart on average over 4 shared benchmarks.
Widest single gap
AA Math Index: R1 0528 76.0 against Mistral Medium 3.1 38.3, 37.7 points apart on a 0 to 100 scale.
Output price
R1 0528 $2.18 against Mistral Medium 3.1 $2.00 per million output tokens, 1.1x apart.
Context window
R1 0528 takes 164K tokens, Mistral Medium 3.1 131K.

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 0528BarsMistral Medium 3.1Ties
Coding32
Intelligence10
Agentic work01
Reasoning23
Math31
Knowledge14
Web design70
General811
All shared boards2522
CodingLike-for-likeSix of these boards feed the Vibe Coding Index32
Coding benchmarks for R1 0528 and Mistral Medium 3.1
BenchmarkR1 0528Mistral Medium 3.1Leader
Aider polyglot71.4%Not measuredOnly R1 0528 measured
AA Coding IndexNot measured20.5Only Mistral Medium 3.1 measured
LiveCodeBench (Vals AI)Not measured44.8%Only Mistral Medium 3.1 measured
LiveCodeBench (Artificial Analysis run)77.0%40.6%R1 0528
SciCodeNot measured32.4%Only Mistral Medium 3.1 measured
Terminal-Bench Hard (Artificial Analysis run)15.9%10.6%R1 0528
WeirdML41.6%Not measuredOnly R1 0528 measured
ALE-Bench804.1210.2R1 0528
LMArena Text: coding14271433Mistral Medium 3.1
LMArena Text: software and IT14351436Mistral Medium 3.1
Neither model has a result on the other 29 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for R1 0528 and Mistral Medium 3.1
BenchmarkR1 0528Mistral Medium 3.1Leader
AA Intelligence Index13.19.2R1 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 Mistral Medium 3.1
BenchmarkR1 0528Mistral Medium 3.1Leader
AA Agentic IndexNot measured1.9Only Mistral Medium 3.1 measured
τ²-Bench Telecom36.5%40.6%Mistral Medium 3.1
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 index23
Reasoning benchmarks for R1 0528 and Mistral Medium 3.1
BenchmarkR1 0528Mistral Medium 3.1Leader
MMMU Pro (Vals AI)Not measured63.0%Only Mistral Medium 3.1 measured
GPQA Diamond (Artificial Analysis run)81.3%58.8%R1 0528
Humanity's Last Exam (Artificial Analysis run)15.8%4.7%R1 0528
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 prompts14151426Mistral Medium 3.1
LMArena Text: expert13941408Mistral Medium 3.1
LMArena Text: hard prompts in English14221435Mistral Medium 3.1
LMArena Vision: diagramsNot measured1175Only Mistral Medium 3.1 measured
LMArena Vision: homeworkNot measured1165Only Mistral Medium 3.1 measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index31
Math benchmarks for R1 0528 and Mistral Medium 3.1
BenchmarkR1 0528Mistral Medium 3.1Leader
AIMENot measured42.3%Only Mistral Medium 3.1 measured
MATH 500 (Vals AI)Not measured87.0%Only Mistral Medium 3.1 measured
MGSM (Vals AI)Not measured90.9%Only Mistral Medium 3.1 measured
AA Math Index76.038.3R1 0528
AIME 2025 (Artificial Analysis run)76.0%38.3%R1 0528
OTIS Mock AIME66.4%Not measuredOnly R1 0528 measured
MATH level 596.6%Not measuredOnly R1 0528 measured
LMArena Text: math14001408Mistral Medium 3.1
LMArena Text: mathematical work14151412R1 0528
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index14
Knowledge benchmarks for R1 0528 and Mistral Medium 3.1
BenchmarkR1 0528Mistral Medium 3.1Leader
MMLU ProNot measured75.3%Only Mistral Medium 3.1 measured
LegalBench (Vals AI)Not measured62.0%Only Mistral Medium 3.1 measured
CorpFin (Vals AI)Not measured50.7%Only Mistral Medium 3.1 measured
TaxEval (Vals AI)Not measured70.3%Only Mistral Medium 3.1 measured
MortgageTax (Vals AI)Not measured36.5%Only Mistral Medium 3.1 measured
MedQA (Vals AI)Not measured78.2%Only Mistral Medium 3.1 measured
MMLU Pro (Artificial Analysis run)84.9%68.3%R1 0528
LMArena Text: science14301444Mistral Medium 3.1
LMArena Text: medicine and healthcare14451449Mistral Medium 3.1
LMArena Text: legal and government14191439Mistral Medium 3.1
LMArena Text: business and finance14021418Mistral Medium 3.1
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index70
Web design benchmarks for R1 0528 and Mistral Medium 3.1
BenchmarkR1 0528Mistral Medium 3.1Leader
Design Arena: websites11491132R1 0528
Design Arena: UI components11001097R1 0528
Design Arena: game dev10971073R1 0528
Design Arena: data viz11821144R1 0528
Design Arena: 3D11101081R1 0528
Design Arena: all code categories11381120R1 0528
Design Arena: SVG1038992R1 0528
Design Arena: ASCII artNot measured997Only Mistral Medium 3.1 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index811
General benchmarks for R1 0528 and Mistral Medium 3.1
BenchmarkR1 0528Mistral Medium 3.1Leader
IFBench39.6%39.8%Mistral Medium 3.1
Long context reasoning (AA-LCR)55.7%42.7%R1 0528
DTBenchNot measured67.5%Only Mistral Medium 3.1 measured
LMCANot measured19.1%Only Mistral Medium 3.1 measured
Fiction.LiveBench75.0%Not measuredOnly R1 0528 measured
Creative writing (Lech Mazur)81.9%Not measuredOnly R1 0528 measured
LMArena Text14281424R1 0528
LMArena Text: instruction following13821398Mistral Medium 3.1
LMArena Text: creative writing14051391R1 0528
LMArena VisionNot measured1172Only Mistral Medium 3.1 measured
LMArena Text: English14371438Mistral Medium 3.1
LMArena Text: non-English14121408R1 0528
LMArena Text: Chinese14421447Mistral Medium 3.1
LMArena Text: German14041432Mistral Medium 3.1
LMArena Text: Japanese13911379R1 0528
LMArena Text: Korean13601380Mistral Medium 3.1
LMArena Text: French14171460Mistral Medium 3.1
LMArena Text: Spanish14111433Mistral Medium 3.1
LMArena Text: Russian14231411R1 0528
LMArena Text: Polish14281430Mistral Medium 3.1
LMArena Text: multi-turn14051418Mistral Medium 3.1
LMArena Text: longer queries13911406Mistral Medium 3.1
LMArena Text: writing and language14021395R1 0528
LMArena Text: entertainment and media14001390R1 0528
LMArena Vision: EnglishNot measured1179Only Mistral Medium 3.1 measured
LMArena Vision: ChineseNot measured1190Only Mistral Medium 3.1 measured
LMArena Vision: reading textNot measured1175Only Mistral Medium 3.1 measured
LMArena Vision: humorNot measured1168Only Mistral Medium 3.1 measured
LMArena Vision: captioningNot measured1145Only Mistral Medium 3.1 measured
LMArena Vision: recognizing thingsNot measured1147Only Mistral Medium 3.1 measured
LMArena Vision: creative writingNot measured1200Only Mistral Medium 3.1 measured
Neither model has a result on the other 15 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for R1 0528 and Mistral Medium 3.1
BenchmarkR1 0528Mistral Medium 3.1Leader
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
Mistral Medium 3.1$0.0014Fits in one request

Mistral Medium 3.1 costs less

Repository review

50K input + 3K output tokens

R1 0528$0.032Fits in one request
Mistral Medium 3.1$0.026Fits in one request

Mistral Medium 3.1 costs less

Agent loop

200K input + 10K output tokens

R1 0528$0.122Exceeds the context window
Mistral Medium 3.1$0.100Exceeds the context window

Mistral Medium 3.1 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 Mistral Medium 3.1
SpecificationDeepSeek R1 0528Mistral Medium 3.1
MakerDeepSeekMistral AI
WeightsOpen weightsNo public weights listed
ReleasedMay 28, 2025August 13, 2025
Context window164K131K
Input $/Mtok$0.50$0.40
Output $/Mtok$2.18$2.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is R1 0528 better than Mistral Medium 3.1 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 131K tokens) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, R1 0528 or Mistral Medium 3.1?

R1 0528 costs $0.50 per million input tokens and $2.18 per million output tokens; Mistral Medium 3.1 costs $0.40 and $2.00. Cost per solved task is known for neither of them.

Which has the bigger context window, R1 0528 or Mistral Medium 3.1?

R1 0528, with 164K tokens against 131K.

How many benchmarks is the R1 0528 vs Mistral Medium 3.1 comparison based on?

47 benchmarks have a result for both models as of October 22, 2026. R1 0528's coding index rests on 0 independent benchmarks and Mistral Medium 3.1's on 0. Where only one model has a result, the page says so instead of naming a winner.

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