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GPT-5.1-Codex vs Mistral Medium 3.5

Updated October 21, 2026. 16 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 3.5
GPT-5.1-CodexOpenAI
Coding
50.5
Overall
23.7
Output $/M
$10.00
14
Mistral Medium 3.5Mistral AI
Coding
9.2
Overall
14.2
Output $/M
$7.50
1
vs boards won of 16 shared, 1 tied

Decision reading

Pick GPT-5.1-Codex for coding: it scores 50.5 on the Vibe Coding Index against 9.2 for Mistral Medium 3.5.

Pick Mistral Medium 3.5 when output tokens cost 1.3x less, or when the benchmark that matters is τ²-Bench Telecom, where it leads.

Model AGPT-5.1-CodexOpenAI50.5/1002 independent benchmarks$0.892 per solved taskModel BMistral Medium 3.5Mistral AI9.2/1001 independent benchmark$6.02 per solved task
Shared results
16
GPT-5.1-Codex only
10
Mistral Medium 3.5 only
64
Like-for-like categories
6 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 50.5 from 2 benchmarks, Mistral Medium 3.5 9.2 from 1 benchmark.
Widest category
Reasoning, 11.6 points apart on average over 2 shared benchmarks.
Widest single gap
Design Arena: UI components: GPT-5.1-Codex 1237 against Mistral Medium 3.5 1079, 19.8 points apart on a 0 to 100 scale.
Output price
GPT-5.1-Codex $10.00 against Mistral Medium 3.5 $7.50 per million output tokens, 1.3x apart.
Context window
GPT-5.1-Codex takes 400K 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
CategoryGPT-5.1-CodexBarsMistral Medium 3.5Ties
Coding50
Intelligence10
Agentic work01
Reasoning20
Web design50
General101 tie
All shared boards1411 tie
CodingLike-for-likeFour of these boards feed the Vibe Coding Index50
Coding benchmarks for GPT-5.1-Codex and Mistral Medium 3.5
BenchmarkGPT-5.1-CodexMistral Medium 3.5Leader
SWE-bench Verified66.0%Not measuredOnly GPT-5.1-Codex measured
LMArena WebDev13371264GPT-5.1-Codex
AA Coding IndexNot measured46.9Only Mistral Medium 3.5 measured
LiveCodeBench (Vals AI)85.5%Not measuredOnly GPT-5.1-Codex measured
SWE-bench Verified (Vals AI)Not measured66.4%Only Mistral Medium 3.5 measured
Vibe Code Bench (Vals AI)13.1%2.9%GPT-5.1-Codex
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)84.9%Not measuredOnly GPT-5.1-Codex measured
SciCodeNot measured40.2%Only Mistral Medium 3.5 measured
Terminal-Bench Hard (Artificial Analysis run)34.8%33.3%GPT-5.1-Codex
Terminal-Bench57.8%Not measuredOnly GPT-5.1-Codex measured
ALE-Bench1244.9764.0GPT-5.1-Codex
LMArena Text: codingNot measured1460Only Mistral Medium 3.5 measured
LMArena Text: software and ITNot measured1458Only Mistral Medium 3.5 measured
LMArena WebDev: ReactNot measured1254Only Mistral Medium 3.5 measured
LMArena WebDev: HTML13461308GPT-5.1-Codex
Neither model has a result on the other 21 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GPT-5.1-Codex and Mistral Medium 3.5
BenchmarkGPT-5.1-CodexMistral Medium 3.5Leader
AA Intelligence Index23.714.2GPT-5.1-Codex
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 GPT-5.1-Codex and Mistral Medium 3.5
BenchmarkGPT-5.1-CodexMistral Medium 3.5Leader
AA Agentic IndexNot measured7.0Only Mistral Medium 3.5 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
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 Telecom83.0%94.2%Mistral Medium 3.5
Neither model has a result on the other 30 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
Reasoning benchmarks for GPT-5.1-Codex and Mistral Medium 3.5
BenchmarkGPT-5.1-CodexMistral Medium 3.5Leader
GPQA DiamondNot measured34.9%Only Mistral Medium 3.5 measured
GPQA Diamond (Artificial Analysis run)86.0%74.8%GPT-5.1-Codex
Humanity's Last Exam (Artificial Analysis run)25.7%13.8%GPT-5.1-Codex
LMArena Text: hard promptsNot measured1436Only Mistral Medium 3.5 measured
LMArena Text: expertNot measured1432Only Mistral Medium 3.5 measured
LMArena Text: hard prompts in EnglishNot measured1445Only Mistral Medium 3.5 measured
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 13 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Math benchmarks for GPT-5.1-Codex and Mistral Medium 3.5
BenchmarkGPT-5.1-CodexMistral Medium 3.5Leader
AA Math Index95.7Not measuredOnly GPT-5.1-Codex measured
AIME 2025 (Artificial Analysis run)95.7%Not measuredOnly GPT-5.1-Codex measured
ProofBenchNot measured9.0%Only Mistral Medium 3.5 measured
LMArena Text: mathNot measured1431Only Mistral Medium 3.5 measured
LMArena Text: mathematical workNot measured1440Only Mistral Medium 3.5 measured
Neither model has a result on the other 8 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
Knowledge benchmarks for GPT-5.1-Codex and Mistral Medium 3.5
BenchmarkGPT-5.1-CodexMistral 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)86.0%Not measuredOnly GPT-5.1-Codex measured
LMArena Text: scienceNot measured1428Only Mistral Medium 3.5 measured
LMArena Text: medicine and healthcareNot measured1409Only Mistral Medium 3.5 measured
LMArena Text: legal and governmentNot measured1437Only Mistral Medium 3.5 measured
LMArena Text: business and financeNot measured1426Only Mistral Medium 3.5 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 3.5
BenchmarkGPT-5.1-CodexMistral Medium 3.5Leader
Design Arena: websites11621142GPT-5.1-Codex
Design Arena: UI components12371079GPT-5.1-Codex
Design Arena: game dev11381079GPT-5.1-Codex
Design Arena: data viz12131120GPT-5.1-Codex
Design Arena: 3DNot measured1061Only Mistral Medium 3.5 measured
Design Arena: all code categories11531122GPT-5.1-Codex
Design Arena: SVGNot measured949Only Mistral Medium 3.5 measured
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 index10
General benchmarks for GPT-5.1-Codex and Mistral Medium 3.5
BenchmarkGPT-5.1-CodexMistral 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
IFBench70.0%68.8%GPT-5.1-Codex
Long context reasoning (AA-LCR)69.3%69.3%Tie
DTBenchNot measured75.5%Only Mistral Medium 3.5 measured
LMCANot measured26.1%Only Mistral Medium 3.5 measured
Surface Evolver BenchNot measured26.9%Only Mistral Medium 3.5 measured
LMArena TextNot measured1421Only Mistral Medium 3.5 measured
LMArena Text: instruction followingNot measured1415Only Mistral Medium 3.5 measured
LMArena Text: creative writingNot measured1374Only Mistral Medium 3.5 measured
LMArena VisionNot measured1222Only Mistral Medium 3.5 measured
LMArena Text: EnglishNot measured1433Only Mistral Medium 3.5 measured
LMArena Text: non-EnglishNot measured1404Only Mistral Medium 3.5 measured
LMArena Text: ChineseNot measured1444Only Mistral Medium 3.5 measured
LMArena Text: GermanNot measured1453Only Mistral Medium 3.5 measured
LMArena Text: KoreanNot measured1384Only Mistral Medium 3.5 measured
LMArena Text: FrenchNot measured1448Only Mistral Medium 3.5 measured
LMArena Text: SpanishNot measured1411Only Mistral Medium 3.5 measured
LMArena Text: RussianNot measured1395Only Mistral Medium 3.5 measured
LMArena Text: PolishNot measured1430Only Mistral Medium 3.5 measured
LMArena Text: multi-turnNot measured1423Only Mistral Medium 3.5 measured
LMArena Text: longer queriesNot measured1415Only Mistral Medium 3.5 measured
LMArena Text: writing and languageNot measured1384Only Mistral Medium 3.5 measured
LMArena Text: entertainment and mediaNot measured1382Only Mistral Medium 3.5 measured
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 16 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 3.5
BenchmarkGPT-5.1-CodexMistral 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

GPT-5.1-Codex$0.0063Fits in one request
Mistral Medium 3.5$0.0053Fits in one request

Mistral Medium 3.5 costs less

Repository review

50K input + 3K output tokens

GPT-5.1-Codex$0.092Fits in one request
Mistral Medium 3.5$0.098Fits in one request

GPT-5.1-Codex costs less

Agent loop

200K input + 10K output tokens

GPT-5.1-Codex$0.350Fits in one request
Mistral Medium 3.5$0.375Fits in one request

GPT-5.1-Codex 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 3.5
SpecificationOpenAI GPT-5.1-CodexMistral Medium 3.5
MakerOpenAIMistral AI
WeightsNo public weights listedNo public weights listed
ReleasedNovember 13, 2025April 30, 2026
Context window400K262K
Input $/Mtok$1.25$1.50
Output $/Mtok$10.00$7.50
Coding index50.59.2
Independent measurements behind it21
Cost per solved task$0.892$6.02
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5.1-Codex better than Mistral Medium 3.5 for coding?

Pick GPT-5.1-Codex for coding: it scores 50.5 on the Vibe Coding Index against 9.2 for Mistral Medium 3.5. Pick Mistral Medium 3.5 when output tokens cost 1.3x less, or when the benchmark that matters is τ²-Bench Telecom, where it leads.

Which is cheaper, GPT-5.1-Codex or Mistral Medium 3.5?

GPT-5.1-Codex costs $1.25 per million input tokens and $10.00 per million output tokens; Mistral Medium 3.5 costs $1.50 and $7.50. Per solved SWE-bench Verified task, GPT-5.1-Codex costs $0.892 and Mistral Medium 3.5 $6.02.

Which has the bigger context window, GPT-5.1-Codex or Mistral Medium 3.5?

GPT-5.1-Codex, with 400K tokens against 262K.

How many benchmarks is the GPT-5.1-Codex vs Mistral Medium 3.5 comparison based on?

16 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 3.5's on 1. Where only one model has a result, the page says so instead of naming a winner.

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