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R1 0528 vs Mistral Medium 3

R1 0528 leads Mistral Medium 3 on the Artificial Analysis Intelligence Index, 13.1 to 9.0, at about the same output price ($2.18 vs $2.00 per million). Updated October 21, 2026; 45 benchmarks have a result for both.

Replace R1 0528 Replace Mistral Medium 3
R1 0528DeepSeek
Coding
No data
Overall
46.8
Output $/M
$2.18
45
Mistral Medium 3Mistral AI
Coding
No data
Overall
No data
Output $/M
$2.00
0
vs boards won of 45 shared

R1 0528 or Mistral Medium 3: 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).

Model AR1 0528DeepSeekNot benchmarkedNo coding benchmarkNo cost per solved taskModel BMistral Medium 3Mistral AINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
45
R1 0528 only
15
Mistral Medium 3 only
12
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 not benchmarked.
Widest category
Math, 27.4 points apart on average over 4 shared benchmarks.
Widest single gap
AA Math Index: R1 0528 76.0 against Mistral Medium 3 30.3, 45.7 points apart on a 0 to 100 scale.
Output price
R1 0528 $2.18 against Mistral Medium 3 $2.00 per million output tokens, 1.1x apart.
Context window
R1 0528 takes 164K tokens, Mistral Medium 3 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 3Ties
Coding40
Intelligence10
Agentic work10
Reasoning50
Math40
Knowledge50
Web design60
General190
All shared boards450
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for R1 0528 and Mistral Medium 3
BenchmarkR1 0528Mistral Medium 3Leader
Aider polyglot71.4%Not measuredOnly R1 0528 measured
LiveCodeBench (Artificial Analysis run)77.0%40.0%R1 0528
Terminal-Bench Hard (Artificial Analysis run)15.9%3.8%R1 0528
WeirdML41.6%Not measuredOnly R1 0528 measured
ALE-Bench804.1Not measuredOnly R1 0528 measured
LMArena Text: coding14271385R1 0528
LMArena Text: software and IT14351385R1 0528
Neither model has a result on the other 32 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for R1 0528 and Mistral Medium 3
BenchmarkR1 0528Mistral Medium 3Leader
AA Intelligence Index13.19.0R1 0528
Epoch Capabilities IndexNot measured134.0Only Mistral Medium 3 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for R1 0528 and Mistral Medium 3
BenchmarkR1 0528Mistral Medium 3Leader
τ²-Bench Telecom36.5%24.3%R1 0528
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 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for R1 0528 and Mistral Medium 3
BenchmarkR1 0528Mistral Medium 3Leader
GPQA Diamond (Artificial Analysis run)81.3%57.8%R1 0528
Humanity's Last Exam (Artificial Analysis run)15.8%4.1%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 prompts14151364R1 0528
LMArena Text: expert13941342R1 0528
LMArena Text: hard prompts in English14221374R1 0528
LMArena Vision: diagramsNot measured1155Only Mistral Medium 3 measured
LMArena Vision: homeworkNot measured1165Only Mistral Medium 3 measured
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index40
Math benchmarks for R1 0528 and Mistral Medium 3
BenchmarkR1 0528Mistral Medium 3Leader
AA Math Index76.030.3R1 0528
AIME 2025 (Artificial Analysis run)76.0%30.3%R1 0528
OTIS Mock AIME66.4%Not measuredOnly R1 0528 measured
MATH level 596.6%Not measuredOnly R1 0528 measured
LMArena Text: math14001353R1 0528
LMArena Text: mathematical work14151354R1 0528
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
Knowledge benchmarks for R1 0528 and Mistral Medium 3
BenchmarkR1 0528Mistral Medium 3Leader
MMLU Pro (Artificial Analysis run)84.9%76.0%R1 0528
LMArena Text: science14301381R1 0528
LMArena Text: medicine and healthcare14451381R1 0528
LMArena Text: legal and government14191384R1 0528
LMArena Text: business and finance14021352R1 0528
Neither model has a result on the other 13 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index60
Web design benchmarks for R1 0528 and Mistral Medium 3
BenchmarkR1 0528Mistral Medium 3Leader
Design Arena: websites11491079R1 0528
Design Arena: UI components11031024R1 0528
Design Arena: game dev10971018R1 0528
Design Arena: data viz11821034R1 0528
Design Arena: 3D11111084R1 0528
Design Arena: all code categories11391069R1 0528
Design Arena: SVG1039Not 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 index190
General benchmarks for R1 0528 and Mistral Medium 3
BenchmarkR1 0528Mistral Medium 3Leader
IFBench39.6%39.3%R1 0528
Long context reasoning (AA-LCR)55.7%31.3%R1 0528
DTBenchNot measured62.3%Only Mistral Medium 3 measured
Fiction.LiveBench75.0%Not measuredOnly R1 0528 measured
Creative writing (Lech Mazur)81.9%Not measuredOnly R1 0528 measured
LMArena Text14281370R1 0528
LMArena Text: instruction following13821338R1 0528
LMArena Text: creative writing14051343R1 0528
LMArena VisionNot measured1157Only Mistral Medium 3 measured
LMArena Text: English14371385R1 0528
LMArena Text: non-English14121353R1 0528
LMArena Text: Chinese14421374R1 0528
LMArena Text: German14041377R1 0528
LMArena Text: Japanese13911316R1 0528
LMArena Text: Korean13601304R1 0528
LMArena Text: French14171368R1 0528
LMArena Text: Spanish14111364R1 0528
LMArena Text: Russian14231359R1 0528
LMArena Text: Polish14281371R1 0528
LMArena Text: multi-turn14051384R1 0528
LMArena Text: longer queries13911360R1 0528
LMArena Text: writing and language14021352R1 0528
LMArena Text: entertainment and media14001335R1 0528
LMArena Vision: EnglishNot measured1172Only Mistral Medium 3 measured
LMArena Vision: ChineseNot measured1161Only Mistral Medium 3 measured
LMArena Vision: reading textNot measured1154Only Mistral Medium 3 measured
LMArena Vision: humorNot measured1145Only Mistral Medium 3 measured
LMArena Vision: captioningNot measured1094Only Mistral Medium 3 measured
LMArena Vision: recognizing thingsNot measured1141Only Mistral Medium 3 measured
LMArena Vision: creative writingNot measured1146Only Mistral Medium 3 measured
Neither model has a result on the other 16 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
BenchmarkR1 0528Mistral Medium 3Leader
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$0.0014Fits in one request

Mistral Medium 3 costs less

Repository review

50K input + 3K output tokens

R1 0528$0.032Fits in one request
Mistral Medium 3$0.026Fits in one request

Mistral Medium 3 costs less

Agent loop

200K input + 10K output tokens

R1 0528$0.122Exceeds the context window
Mistral Medium 3$0.100Exceeds the context window

Mistral Medium 3 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
SpecificationDeepSeek R1 0528Mistral Medium 3
MakerDeepSeekMistral AI
WeightsOpen weightsNo public weights listed
ReleasedMay 28, 2025May 7, 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 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).

Which is cheaper, R1 0528 or Mistral Medium 3?

R1 0528 costs $0.50 per million input tokens and $2.18 per million output tokens; Mistral Medium 3 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?

R1 0528, with 164K tokens against 131K.

How many benchmarks is the R1 0528 vs Mistral Medium 3 comparison based on?

45 benchmarks have a result for both models as of October 21, 2026. R1 0528's coding index rests on 0 independent benchmarks and Mistral Medium 3's on 0. Where only one model has a result, the page says so instead of naming a winner.

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