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GPT-5.1-Codex-Mini vs Mistral Medium 3.1

GPT-5.1-Codex-Mini leads Mistral Medium 3.1 on the Artificial Analysis Intelligence Index, 20.4 to 9.2, at about the same output price ($2.00 vs $2.00 per million). Updated October 21, 2026; 19 benchmarks have a result for both.

Replace GPT-5.1-Codex-Mini Replace Mistral Medium 3.1
GPT-5.1-Codex-MiniOpenAI
Coding
No data
Overall
No data
Output $/M
$2.00
13
Mistral Medium 3.1Mistral AI
Coding
No data
Overall
No data
Output $/M
$2.00
6
vs boards won of 19 shared

GPT-5.1-Codex-Mini or Mistral Medium 3.1: which to pick

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

Pick GPT-5.1-Codex-Mini for a larger context window (400K against 131K tokens) and work measured by Design Arena: websites or Design Arena: UI components, where it leads.

Model AGPT-5.1-Codex-MiniOpenAINot benchmarked1 independent benchmarkNo cost per solved taskModel BMistral Medium 3.1Mistral AINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
19
GPT-5.1-Codex-Mini only
3
Mistral Medium 3.1 only
55
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
GPT-5.1-Codex-Mini not benchmarked, Mistral Medium 3.1 not benchmarked.
Widest category
Math, 53.4 points apart on average over 2 shared benchmarks.
Widest single gap
AA Math Index: GPT-5.1-Codex-Mini 91.7 against Mistral Medium 3.1 38.3, 53.4 points apart on a 0 to 100 scale.
Output price
Both cost $2.00 per million output tokens.
Context window
GPT-5.1-Codex-Mini takes 400K 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
CategoryGPT-5.1-Codex-MiniBarsMistral Medium 3.1Ties
Coding20
Intelligence10
Agentic work10
Reasoning20
Math20
Knowledge10
Web design26
General20
All shared boards136
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for GPT-5.1-Codex-Mini and Mistral Medium 3.1
BenchmarkGPT-5.1-Codex-MiniMistral Medium 3.1Leader
LMArena WebDev1244Not measuredOnly GPT-5.1-Codex-Mini 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)83.6%40.6%GPT-5.1-Codex-Mini
SciCodeNot measured32.4%Only Mistral Medium 3.1 measured
Terminal-Bench Hard (Artificial Analysis run)33.3%10.6%GPT-5.1-Codex-Mini
Terminal-Bench61.6%Not measuredOnly GPT-5.1-Codex-Mini measured
ALE-BenchNot measured210.2Only Mistral Medium 3.1 measured
LMArena Text: codingNot measured1433Only Mistral Medium 3.1 measured
LMArena Text: software and ITNot measured1436Only Mistral Medium 3.1 measured
LMArena WebDev: HTML1253Not measuredOnly GPT-5.1-Codex-Mini measured
Neither model has a result on the other 28 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GPT-5.1-Codex-Mini and Mistral Medium 3.1
BenchmarkGPT-5.1-Codex-MiniMistral Medium 3.1Leader
AA Intelligence Index20.49.2GPT-5.1-Codex-Mini
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GPT-5.1-Codex-Mini and Mistral Medium 3.1
BenchmarkGPT-5.1-Codex-MiniMistral Medium 3.1Leader
AA Agentic IndexNot measured1.9Only Mistral Medium 3.1 measured
τ²-Bench Telecom62.9%40.6%GPT-5.1-Codex-Mini
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
Reasoning benchmarks for GPT-5.1-Codex-Mini and Mistral Medium 3.1
BenchmarkGPT-5.1-Codex-MiniMistral 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%GPT-5.1-Codex-Mini
Humanity's Last Exam (Artificial Analysis run)18.5%4.7%GPT-5.1-Codex-Mini
LMArena Text: hard promptsNot measured1426Only Mistral Medium 3.1 measured
LMArena Text: expertNot measured1408Only Mistral Medium 3.1 measured
LMArena Text: hard prompts in EnglishNot measured1435Only Mistral Medium 3.1 measured
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 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for GPT-5.1-Codex-Mini and Mistral Medium 3.1
BenchmarkGPT-5.1-Codex-MiniMistral 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 Index91.738.3GPT-5.1-Codex-Mini
AIME 2025 (Artificial Analysis run)91.7%38.3%GPT-5.1-Codex-Mini
LMArena Text: mathNot measured1408Only Mistral Medium 3.1 measured
LMArena Text: mathematical workNot measured1412Only Mistral Medium 3.1 measured
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for GPT-5.1-Codex-Mini and Mistral Medium 3.1
BenchmarkGPT-5.1-Codex-MiniMistral 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)82.0%68.3%GPT-5.1-Codex-Mini
LMArena Text: scienceNot measured1444Only Mistral Medium 3.1 measured
LMArena Text: medicine and healthcareNot measured1449Only Mistral Medium 3.1 measured
LMArena Text: legal and governmentNot measured1439Only Mistral Medium 3.1 measured
LMArena Text: business and financeNot measured1418Only Mistral Medium 3.1 measured
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index26
Web design benchmarks for GPT-5.1-Codex-Mini and Mistral Medium 3.1
BenchmarkGPT-5.1-Codex-MiniMistral Medium 3.1Leader
Design Arena: websites11111133Mistral Medium 3.1
Design Arena: UI components10811100Mistral Medium 3.1
Design Arena: game dev10921074GPT-5.1-Codex-Mini
Design Arena: data viz10971144Mistral Medium 3.1
Design Arena: 3D9881081Mistral Medium 3.1
Design Arena: all code categories10941120Mistral Medium 3.1
Design Arena: SVG978993Mistral Medium 3.1
Design Arena: ASCII art1105997GPT-5.1-Codex-Mini
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
General benchmarks for GPT-5.1-Codex-Mini and Mistral Medium 3.1
BenchmarkGPT-5.1-Codex-MiniMistral Medium 3.1Leader
IFBench67.9%39.8%GPT-5.1-Codex-Mini
Long context reasoning (AA-LCR)66.7%42.7%GPT-5.1-Codex-Mini
DTBenchNot measured67.5%Only Mistral Medium 3.1 measured
LMCANot measured19.1%Only Mistral Medium 3.1 measured
LMArena TextNot measured1424Only Mistral Medium 3.1 measured
LMArena Text: instruction followingNot measured1398Only Mistral Medium 3.1 measured
LMArena Text: creative writingNot measured1391Only Mistral Medium 3.1 measured
LMArena VisionNot measured1172Only Mistral Medium 3.1 measured
LMArena Text: EnglishNot measured1438Only Mistral Medium 3.1 measured
LMArena Text: non-EnglishNot measured1408Only Mistral Medium 3.1 measured
LMArena Text: ChineseNot measured1447Only Mistral Medium 3.1 measured
LMArena Text: GermanNot measured1432Only Mistral Medium 3.1 measured
LMArena Text: JapaneseNot measured1379Only Mistral Medium 3.1 measured
LMArena Text: KoreanNot measured1380Only Mistral Medium 3.1 measured
LMArena Text: FrenchNot measured1460Only Mistral Medium 3.1 measured
LMArena Text: SpanishNot measured1433Only Mistral Medium 3.1 measured
LMArena Text: RussianNot measured1411Only Mistral Medium 3.1 measured
LMArena Text: PolishNot measured1430Only Mistral Medium 3.1 measured
LMArena Text: multi-turnNot measured1418Only Mistral Medium 3.1 measured
LMArena Text: longer queriesNot measured1406Only Mistral Medium 3.1 measured
LMArena Text: writing and languageNot measured1395Only Mistral Medium 3.1 measured
LMArena Text: entertainment and mediaNot measured1390Only Mistral Medium 3.1 measured
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 17 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-5.1-Codex-Mini and Mistral Medium 3.1
BenchmarkGPT-5.1-Codex-MiniMistral 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

GPT-5.1-Codex-Mini$0.0013Fits in one request
Mistral Medium 3.1$0.0014Fits in one request

GPT-5.1-Codex-Mini costs less

Repository review

50K input + 3K output tokens

GPT-5.1-Codex-Mini$0.018Fits in one request
Mistral Medium 3.1$0.026Fits in one request

GPT-5.1-Codex-Mini costs less

Agent loop

200K input + 10K output tokens

GPT-5.1-Codex-Mini$0.070Fits in one request
Mistral Medium 3.1$0.100Exceeds the context window

GPT-5.1-Codex-Mini 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 GPT-5.1-Codex-Mini and Mistral Medium 3.1
SpecificationOpenAI GPT-5.1-Codex-MiniMistral Medium 3.1
MakerOpenAIMistral AI
WeightsNo public weights listedNo public weights listed
ReleasedNovember 13, 2025August 13, 2025
Context window400K131K
Input $/Mtok$0.25$0.40
Output $/Mtok$2.00$2.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5.1-Codex-Mini better than Mistral Medium 3.1 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5.1-Codex-Mini for a larger context window (400K against 131K tokens) and work measured by Design Arena: websites or Design Arena: UI components, where it leads.

Which is cheaper, GPT-5.1-Codex-Mini or Mistral Medium 3.1?

GPT-5.1-Codex-Mini costs $0.25 per million input tokens and $2.00 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, GPT-5.1-Codex-Mini or Mistral Medium 3.1?

GPT-5.1-Codex-Mini, with 400K tokens against 131K.

How many benchmarks is the GPT-5.1-Codex-Mini vs Mistral Medium 3.1 comparison based on?

19 benchmarks have a result for both models as of October 21, 2026. GPT-5.1-Codex-Mini's coding index rests on 1 independent benchmark 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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