Enter opens the highlighted result. Esc closes.

GPT-5.1-Codex vs Mistral Medium 3.1

Updated October 21, 2026. 18 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GPT-5.1-Codex Replace Mistral Medium 3.1
GPT-5.1-CodexOpenAI
Coding
15.3
Overall
23.7
Output $/M
$10.00
18
Mistral Medium 3.1Mistral AI
Coding
No data
Overall
9.2
Output $/M
$2.00
0
vs boards won of 18 shared

Decision reading

Only GPT-5.1-Codex has a coding score, 15.3 on the Vibe Coding Index; Mistral Medium 3.1 has none, so the two cannot be ranked on coding.

Mistral Medium 3.1 has the edge where output tokens cost 5.0x less.

Model AGPT-5.1-CodexOpenAI15.3/1002 independent benchmarks$0.892 per solved taskModel BMistral Medium 3.1Mistral AINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
18
GPT-5.1-Codex only
8
Mistral Medium 3.1 only
56
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
GPT-5.1-Codex 15.3 from 2 benchmarks, Mistral Medium 3.1 not benchmarked.
Widest category
Math, 57.4 points apart on average over 2 shared benchmarks.
Widest single gap
AA Math Index: GPT-5.1-Codex 95.7 against Mistral Medium 3.1 38.3, 57.4 points apart on a 0 to 100 scale.
Output price
GPT-5.1-Codex $10.00 against Mistral Medium 3.1 $2.00 per million output tokens, 5.0x apart.
Context window
GPT-5.1-Codex 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-CodexBarsMistral Medium 3.1Ties
Coding40
Intelligence10
Agentic work10
Reasoning20
Math20
Knowledge10
Web design50
General20
All shared boards180
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for GPT-5.1-Codex and Mistral Medium 3.1
BenchmarkGPT-5.1-CodexMistral Medium 3.1Leader
SWE-bench Verified66.0%Not measuredOnly GPT-5.1-Codex measured
LMArena WebDev1337Not measuredOnly GPT-5.1-Codex measured
AA Coding IndexNot measured20.5Only Mistral Medium 3.1 measured
LiveCodeBench (Vals AI)85.5%44.8%GPT-5.1-Codex
Vibe Code Bench (Vals AI)13.1%Not measuredOnly GPT-5.1-Codex measured
LiveCodeBench (Artificial Analysis run)84.9%40.6%GPT-5.1-Codex
SciCodeNot measured32.4%Only Mistral Medium 3.1 measured
Terminal-Bench Hard (Artificial Analysis run)34.8%10.6%GPT-5.1-Codex
Terminal-Bench57.8%Not measuredOnly GPT-5.1-Codex measured
ALE-Bench1244.9210.2GPT-5.1-Codex
LMArena Text: codingNot measured1433Only Mistral Medium 3.1 measured
LMArena Text: software and ITNot measured1436Only Mistral Medium 3.1 measured
LMArena WebDev: HTML1346Not measuredOnly GPT-5.1-Codex measured
Neither model has a result on the other 25 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GPT-5.1-Codex and Mistral Medium 3.1
BenchmarkGPT-5.1-CodexMistral Medium 3.1Leader
AA Intelligence Index23.79.2GPT-5.1-Codex
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 and Mistral Medium 3.1
BenchmarkGPT-5.1-CodexMistral Medium 3.1Leader
AA Agentic IndexNot measured1.9Only Mistral Medium 3.1 measured
Design Arena: agents building web apps1018Not measuredOnly GPT-5.1-Codex measured
Design Arena: agents building full-stack apps1086Not measuredOnly GPT-5.1-Codex measured
Design Arena: agents building mobile apps1191Not measuredOnly GPT-5.1-Codex measured
τ²-Bench Telecom83.0%40.6%GPT-5.1-Codex
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
Reasoning benchmarks for GPT-5.1-Codex and Mistral Medium 3.1
BenchmarkGPT-5.1-CodexMistral Medium 3.1Leader
MMMU Pro (Vals AI)Not measured63.0%Only Mistral Medium 3.1 measured
GPQA Diamond (Artificial Analysis run)86.0%58.8%GPT-5.1-Codex
Humanity's Last Exam (Artificial Analysis run)25.7%4.7%GPT-5.1-Codex
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 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for GPT-5.1-Codex and Mistral Medium 3.1
BenchmarkGPT-5.1-CodexMistral 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 Index95.738.3GPT-5.1-Codex
AIME 2025 (Artificial Analysis run)95.7%38.3%GPT-5.1-Codex
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 and Mistral Medium 3.1
BenchmarkGPT-5.1-CodexMistral 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)86.0%68.3%GPT-5.1-Codex
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 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index50
Web design benchmarks for GPT-5.1-Codex and Mistral Medium 3.1
BenchmarkGPT-5.1-CodexMistral Medium 3.1Leader
Design Arena: websites11621133GPT-5.1-Codex
Design Arena: UI components12371099GPT-5.1-Codex
Design Arena: game dev11381074GPT-5.1-Codex
Design Arena: data viz12131144GPT-5.1-Codex
Design Arena: 3DNot measured1081Only Mistral Medium 3.1 measured
Design Arena: all code categories11521120GPT-5.1-Codex
Design Arena: SVGNot measured993Only Mistral Medium 3.1 measured
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 index20
General benchmarks for GPT-5.1-Codex and Mistral Medium 3.1
BenchmarkGPT-5.1-CodexMistral Medium 3.1Leader
IFBench70.0%39.8%GPT-5.1-Codex
Long context reasoning (AA-LCR)69.3%42.7%GPT-5.1-Codex
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 and Mistral Medium 3.1
BenchmarkGPT-5.1-CodexMistral 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$0.0063Fits 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

GPT-5.1-Codex$0.092Fits 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

GPT-5.1-Codex$0.350Fits in one request
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 GPT-5.1-Codex and Mistral Medium 3.1
SpecificationOpenAI GPT-5.1-CodexMistral Medium 3.1
MakerOpenAIMistral AI
WeightsNo public weights listedNo public weights listed
ReleasedNovember 13, 2025August 13, 2025
Context window400K131K
Input $/Mtok$1.25$0.40
Output $/Mtok$10.00$2.00
Coding index15.3Not benchmarked
Independent measurements behind it20
Cost per solved task$0.892Not computable
SourceOpenRouter listingOpenRouter listing

Questions

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

Only GPT-5.1-Codex has a coding score, 15.3 on the Vibe Coding Index; Mistral Medium 3.1 has none, so the two cannot be ranked on coding. Mistral Medium 3.1 has the edge where output tokens cost 5.0x less.

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

GPT-5.1-Codex costs $1.25 per million input tokens and $10.00 per million output tokens; Mistral Medium 3.1 costs $0.40 and $2.00. Cost per solved task is known for GPT-5.1-Codex only.

Which has the bigger context window, GPT-5.1-Codex or Mistral Medium 3.1?

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

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

18 benchmarks have a result for both models as of October 21, 2026. GPT-5.1-Codex's coding index rests on 2 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.

Compare next