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R1 0528 vs Mistral Medium 3.5

Updated October 21, 2026. 42 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 Mistral Medium 3.5
R1 0528DeepSeek
Coding
71.4
Overall
13.1
Output $/M
$2.15
20
Mistral Medium 3.5Mistral AI
Coding
9.2
Overall
14.2
Output $/M
$7.50
22
vs boards won of 42 shared

Decision reading

Pick R1 0528 for coding: it scores 71.4 on the Vibe Coding Index against 9.2 for Mistral Medium 3.5.

Pick Mistral Medium 3.5 when the context window is larger, 262K against 164K tokens, or when what matters is Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.

Model AR1 0528DeepSeek71.4/1001 independent benchmarkNo cost per solved taskModel BMistral Medium 3.5Mistral AI9.2/1001 independent benchmark$6.02 per solved task
Shared results
42
R1 0528 only
17
Mistral Medium 3.5 only
38
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, Mistral Medium 3.5 9.2 from 1 benchmark.
Widest category
Agentic work, 57.6 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: R1 0528 36.5% against Mistral Medium 3.5 94.2%, 57.6 points apart on a 0 to 100 scale.
Output price
R1 0528 $2.15 against Mistral Medium 3.5 $7.50 per million output tokens, 3.5x apart.
Context window
R1 0528 takes 164K tokens, Mistral Medium 3.5 262K.

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 3.5Ties
Coding13
Intelligence01
Agentic work01
Reasoning23
Math02
Knowledge22
Web design70
General810
All shared boards2022
CodingLike-for-likeFour of these boards feed the Vibe Coding Index13
Coding benchmarks for R1 0528 and Mistral Medium 3.5
BenchmarkR1 0528Mistral Medium 3.5Leader
Aider polyglot71.4%Not measuredOnly R1 0528 measured
LMArena WebDevNot measured1264Only Mistral Medium 3.5 measured
AA Coding IndexNot measured46.9Only Mistral Medium 3.5 measured
SWE-bench Verified (Vals AI)Not measured66.4%Only Mistral Medium 3.5 measured
Vibe Code Bench (Vals AI)Not measured2.9%Only Mistral Medium 3.5 measured
Code migration (Vals AI)Not measured5.1%Only Mistral Medium 3.5 measured
Terminal-Bench 2.1 (Vals AI)Not measured39.0%Only Mistral Medium 3.5 measured
LiveCodeBench (Artificial Analysis run)77.0%Not measuredOnly R1 0528 measured
SciCodeNot measured40.2%Only Mistral Medium 3.5 measured
Terminal-Bench Hard (Artificial Analysis run)15.9%33.3%Mistral Medium 3.5
WeirdML41.6%Not measuredOnly R1 0528 measured
ALE-Bench804.1764.0R1 0528
LMArena Text: coding14271460Mistral Medium 3.5
LMArena Text: software and IT14351458Mistral Medium 3.5
LMArena WebDev: ReactNot measured1254Only Mistral Medium 3.5 measured
LMArena WebDev: HTMLNot measured1308Only Mistral Medium 3.5 measured
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for R1 0528 and Mistral Medium 3.5
BenchmarkR1 0528Mistral Medium 3.5Leader
AA Intelligence Index13.114.2Mistral Medium 3.5
Epoch Capabilities IndexNot measured141.4Only Mistral Medium 3.5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for R1 0528 and Mistral Medium 3.5
BenchmarkR1 0528Mistral Medium 3.5Leader
AA Agentic IndexNot measured7.0Only Mistral Medium 3.5 measured
Finance Agent (Vals AI)Not measured32.1%Only Mistral Medium 3.5 measured
Tax Agent Bench (Vals AI)Not measured4.5%Only Mistral Medium 3.5 measured
Legal Research Bench (Vals AI)Not measured9.1%Only Mistral Medium 3.5 measured
Excel Modeling Benchmark (Vals AI)Not measured11.2%Only Mistral Medium 3.5 measured
τ²-Bench Telecom36.5%94.2%Mistral Medium 3.5
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 index23
Reasoning benchmarks for R1 0528 and Mistral Medium 3.5
BenchmarkR1 0528Mistral Medium 3.5Leader
GPQA DiamondNot measured34.9%Only Mistral Medium 3.5 measured
GPQA Diamond (Artificial Analysis run)81.3%74.8%R1 0528
Humanity's Last Exam (Artificial Analysis run)15.8%13.8%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 prompts14151436Mistral Medium 3.5
LMArena Text: expert13941432Mistral Medium 3.5
LMArena Text: hard prompts in English14221445Mistral Medium 3.5
LMArena Vision: diagramsNot measured1254Only Mistral Medium 3.5 measured
LMArena Vision: homeworkNot measured1230Only Mistral Medium 3.5 measured
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for R1 0528 and Mistral Medium 3.5
BenchmarkR1 0528Mistral Medium 3.5Leader
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 measured9.0%Only Mistral Medium 3.5 measured
MATH level 596.6%Not measuredOnly R1 0528 measured
LMArena Text: math14001431Mistral Medium 3.5
LMArena Text: mathematical work14151440Mistral Medium 3.5
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22
Knowledge benchmarks for R1 0528 and Mistral Medium 3.5
BenchmarkR1 0528Mistral Medium 3.5Leader
MMLU ProNot measured75.3%Only Mistral Medium 3.5 measured
CaseLaw (Vals AI)Not measured44.2%Only Mistral Medium 3.5 measured
CorpFin (Vals AI)Not measured58.8%Only Mistral Medium 3.5 measured
TaxEval (Vals AI)Not measured68.0%Only Mistral Medium 3.5 measured
MortgageTax (Vals AI)Not measured28.9%Only Mistral Medium 3.5 measured
MedCode (Vals AI)Not measured33.8%Only Mistral Medium 3.5 measured
MMLU Pro (Artificial Analysis run)84.9%Not measuredOnly R1 0528 measured
LMArena Text: science14301428R1 0528
LMArena Text: medicine and healthcare14451409R1 0528
LMArena Text: legal and government14191437Mistral Medium 3.5
LMArena Text: business and finance14021426Mistral Medium 3.5
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index70
Web design benchmarks for R1 0528 and Mistral Medium 3.5
BenchmarkR1 0528Mistral Medium 3.5Leader
Design Arena: websites11491142R1 0528
Design Arena: UI components11021079R1 0528
Design Arena: game dev10981079R1 0528
Design Arena: data viz11821120R1 0528
Design Arena: 3D11111061R1 0528
Design Arena: all code categories11391122R1 0528
Design Arena: SVG1038949R1 0528
Design Arena: ASCII artNot measured1062Only Mistral Medium 3.5 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index810
General benchmarks for R1 0528 and Mistral Medium 3.5
BenchmarkR1 0528Mistral Medium 3.5Leader
SAGE (Vals AI)Not measured37.6%Only Mistral Medium 3.5 measured
MedScribe (Vals AI)Not measured67.7%Only Mistral Medium 3.5 measured
Vals Multimodal IndexNot measured34.8%Only Mistral Medium 3.5 measured
IFBench39.6%68.8%Mistral Medium 3.5
Long context reasoning (AA-LCR)55.7%69.3%Mistral Medium 3.5
DTBenchNot measured75.5%Only Mistral Medium 3.5 measured
LMCANot measured26.1%Only Mistral Medium 3.5 measured
Fiction.LiveBench75.0%Not measuredOnly R1 0528 measured
Creative writing (Lech Mazur)81.9%Not measuredOnly R1 0528 measured
Surface Evolver BenchNot measured26.9%Only Mistral Medium 3.5 measured
LMArena Text14281421R1 0528
LMArena Text: instruction following13821415Mistral Medium 3.5
LMArena Text: creative writing14051374R1 0528
LMArena VisionNot measured1222Only Mistral Medium 3.5 measured
LMArena Text: English14371433R1 0528
LMArena Text: non-English14121404R1 0528
LMArena Text: Chinese14421444Mistral Medium 3.5
LMArena Text: German14041453Mistral Medium 3.5
LMArena Text: Japanese1391Not measuredOnly R1 0528 measured
LMArena Text: Korean13601384Mistral Medium 3.5
LMArena Text: French14171448Mistral Medium 3.5
LMArena Text: Spanish14111411R1 0528
LMArena Text: Russian14231395R1 0528
LMArena Text: Polish14281430Mistral Medium 3.5
LMArena Text: multi-turn14051423Mistral Medium 3.5
LMArena Text: longer queries13911415Mistral Medium 3.5
LMArena Text: writing and language14021384R1 0528
LMArena Text: entertainment and media14001382R1 0528
LMArena Vision: EnglishNot measured1240Only Mistral Medium 3.5 measured
LMArena Vision: ChineseNot measured1244Only Mistral Medium 3.5 measured
LMArena Vision: reading textNot measured1233Only Mistral Medium 3.5 measured
LMArena Vision: humorNot measured1216Only Mistral Medium 3.5 measured
LMArena Vision: creative writingNot measured1198Only Mistral Medium 3.5 measured
Neither model has a result on the other 13 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 3.5
BenchmarkR1 0528Mistral Medium 3.5Leader
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 3.5$0.0053Fits in one request

R1 0528 costs less

Repository review

50K input + 3K output tokens

R1 0528$0.031Fits in one request
Mistral Medium 3.5$0.098Fits in one request

R1 0528 costs less

Agent loop

200K input + 10K output tokens

R1 0528$0.121Exceeds the context window
Mistral Medium 3.5$0.375Fits in one request

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 R1 0528 and Mistral Medium 3.5
SpecificationDeepSeek R1 0528Mistral Medium 3.5
MakerDeepSeekMistral AI
WeightsOpen weightsNo public weights listed
ReleasedMay 28, 2025April 30, 2026
Context window164K262K
Input $/Mtok$0.50$1.50
Output $/Mtok$2.15$7.50
Coding index71.49.2
Independent measurements behind it11
Cost per solved taskNot computable$6.02
SourceOpenRouter listingOpenRouter listing

Questions

Is R1 0528 better than Mistral Medium 3.5 for coding?

Pick R1 0528 for coding: it scores 71.4 on the Vibe Coding Index against 9.2 for Mistral Medium 3.5. Pick Mistral Medium 3.5 when the context window is larger, 262K against 164K tokens, or when what matters is Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.

Which is cheaper, R1 0528 or Mistral Medium 3.5?

R1 0528 costs $0.50 per million input tokens and $2.15 per million output tokens; Mistral Medium 3.5 costs $1.50 and $7.50. Cost per solved task is known for Mistral Medium 3.5 only.

Which has the bigger context window, R1 0528 or Mistral Medium 3.5?

Mistral Medium 3.5, with 262K tokens against 164K.

How many benchmarks is the R1 0528 vs Mistral Medium 3.5 comparison based on?

42 benchmarks have a result for both models as of October 21, 2026. R1 0528's coding index rests on 1 independent benchmark and Mistral Medium 3.5's on 1. Where only one model has a result, the page says so instead of naming a winner.

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