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GPT-4 vs Mistral Medium 3.1

Updated October 21, 2026. 35 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GPT-4 Replace Mistral Medium 3.1
GPT-4OpenAI
Coding
No data
Overall
6.7
Output $/M
$60.00
0
Mistral Medium 3.1Mistral AI
Coding
No data
Overall
9.2
Output $/M
$2.00
35
vs boards won of 35 shared

Decision reading

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

GPT-4 has the edge where what matters is AA Coding Index or LMArena Text: coding, where it leads.

Model AGPT-4OpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BMistral Medium 3.1Mistral AINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
35
GPT-4 only
10
Mistral Medium 3.1 only
39
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-4 not benchmarked, Mistral Medium 3.1 not benchmarked.
Widest category
Knowledge, 38.8 points apart on average over 5 shared benchmarks.
Widest single gap
LMArena Text: medicine and healthcare: GPT-4 1145 against Mistral Medium 3.1 1449, 50.7 points apart on a 0 to 100 scale.
Output price
GPT-4 $60.00 against Mistral Medium 3.1 $2.00 per million output tokens, 30.0x apart.
Context window
GPT-4 takes 8K 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-4BarsMistral Medium 3.1Ties
Coding03
Intelligence01
Reasoning04
Math02
Knowledge05
General020
All shared boards035
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-4 and Mistral Medium 3.1
BenchmarkGPT-4Mistral Medium 3.1Leader
SWE-bench Verified22.4%Not measuredOnly GPT-4 measured
SWE-bench Lite39.7%Not measuredOnly GPT-4 measured
SWE-bench (full test set)12.5%Not measuredOnly GPT-4 measured
AA Coding Index13.120.5Mistral Medium 3.1
LiveCodeBench (Vals AI)Not measured44.8%Only Mistral Medium 3.1 measured
LiveCodeBench (Artificial Analysis run)Not measured40.6%Only Mistral Medium 3.1 measured
SciCodeNot measured32.4%Only Mistral Medium 3.1 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured10.6%Only Mistral Medium 3.1 measured
ALE-BenchNot measured210.2Only Mistral Medium 3.1 measured
LMArena Text: coding12091433Mistral Medium 3.1
LMArena Text: software and IT11951436Mistral Medium 3.1
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GPT-4 and Mistral Medium 3.1
BenchmarkGPT-4Mistral Medium 3.1Leader
AA Intelligence Index6.79.2Mistral Medium 3.1
Epoch Capabilities Index125.7Not measuredOnly GPT-4 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for GPT-4 and Mistral Medium 3.1
BenchmarkGPT-4Mistral Medium 3.1Leader
AA Agentic IndexNot measured1.9Only Mistral Medium 3.1 measured
τ²-Bench TelecomNot measured40.6%Only Mistral Medium 3.1 measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for GPT-4 and Mistral Medium 3.1
BenchmarkGPT-4Mistral Medium 3.1Leader
MMMU Pro (Vals AI)Not measured63.0%Only Mistral Medium 3.1 measured
GPQA Diamond (Artificial Analysis run)34.9%58.8%Mistral Medium 3.1
Humanity's Last Exam (Artificial Analysis run)Not measured4.7%Only Mistral Medium 3.1 measured
BIG-Bench Hard75.1%Not measuredOnly GPT-4 measured
LMArena Text: hard prompts12001426Mistral Medium 3.1
LMArena Text: expert11491408Mistral Medium 3.1
LMArena Text: hard prompts in English12091435Mistral Medium 3.1
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 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for GPT-4 and Mistral Medium 3.1
BenchmarkGPT-4Mistral 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 IndexNot measured38.3Only Mistral Medium 3.1 measured
AIME 2025 (Artificial Analysis run)Not measured38.3%Only Mistral Medium 3.1 measured
GSM8K92.0%Not measuredOnly GPT-4 measured
LMArena Text: math12301408Mistral Medium 3.1
LMArena Text: mathematical work12281412Mistral Medium 3.1
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for GPT-4 and Mistral Medium 3.1
BenchmarkGPT-4Mistral 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)56.2%68.3%Mistral Medium 3.1
MMLU86.4%Not measuredOnly GPT-4 measured
AI2 Reasoning Challenge96.3%Not measuredOnly GPT-4 measured
LMArena Text: science11771444Mistral Medium 3.1
LMArena Text: medicine and healthcare11451449Mistral Medium 3.1
LMArena Text: legal and government11911439Mistral Medium 3.1
LMArena Text: business and finance11451418Mistral Medium 3.1
Neither model has a result on the other 4 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for GPT-4 and Mistral Medium 3.1
BenchmarkGPT-4Mistral Medium 3.1Leader
Design Arena: websitesNot measured1133Only Mistral Medium 3.1 measured
Design Arena: UI componentsNot measured1099Only Mistral Medium 3.1 measured
Design Arena: game devNot measured1074Only Mistral Medium 3.1 measured
Design Arena: data vizNot measured1144Only Mistral Medium 3.1 measured
Design Arena: 3DNot measured1081Only Mistral Medium 3.1 measured
Design Arena: all code categoriesNot measured1120Only Mistral Medium 3.1 measured
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 index020
General benchmarks for GPT-4 and Mistral Medium 3.1
BenchmarkGPT-4Mistral Medium 3.1Leader
IFBench33.2%39.8%Mistral Medium 3.1
Long context reasoning (AA-LCR)Not measured42.7%Only Mistral Medium 3.1 measured
DTBench62.7%67.5%Mistral Medium 3.1
LMCA17.1%19.1%Mistral Medium 3.1
HellaSwag95.3%Not measuredOnly GPT-4 measured
WinoGrande87.5%Not measuredOnly GPT-4 measured
LMArena Text12061424Mistral Medium 3.1
LMArena Text: instruction following12011398Mistral Medium 3.1
LMArena Text: creative writing11911391Mistral Medium 3.1
LMArena VisionNot measured1172Only Mistral Medium 3.1 measured
LMArena Text: English12201438Mistral Medium 3.1
LMArena Text: non-English11941408Mistral Medium 3.1
LMArena Text: Chinese11841447Mistral Medium 3.1
LMArena Text: German11981432Mistral Medium 3.1
LMArena Text: Japanese11371379Mistral Medium 3.1
LMArena Text: Korean10871380Mistral Medium 3.1
LMArena Text: French12201460Mistral Medium 3.1
LMArena Text: Spanish11971433Mistral Medium 3.1
LMArena Text: Russian11951411Mistral Medium 3.1
LMArena Text: Polish12651430Mistral Medium 3.1
LMArena Text: multi-turn12061418Mistral Medium 3.1
LMArena Text: longer queries11901406Mistral Medium 3.1
LMArena Text: writing and language12191395Mistral Medium 3.1
LMArena Text: entertainment and media11841390Mistral Medium 3.1
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 15 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4 and Mistral Medium 3.1
BenchmarkGPT-4Mistral 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-4$0.060Fits 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-4$1.68Exceeds the context window
Mistral Medium 3.1$0.026Fits in one request

Mistral Medium 3.1 costs less

Agent loop

200K input + 10K output tokens

GPT-4$6.60Exceeds the context window
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-4 and Mistral Medium 3.1
SpecificationOpenAI GPT-4Mistral Medium 3.1
MakerOpenAIMistral AI
WeightsNo public weights listedNo public weights listed
ReleasedMay 28, 2023August 13, 2025
Context window8K131K
Input $/Mtok$30.00$0.40
Output $/Mtok$60.00$2.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4 better than Mistral Medium 3.1 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. GPT-4 has the edge where what matters is AA Coding Index or LMArena Text: coding, where it leads.

Which is cheaper, GPT-4 or Mistral Medium 3.1?

GPT-4 costs $30.00 per million input tokens and $60.00 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-4 or Mistral Medium 3.1?

Mistral Medium 3.1, with 131K tokens against 8K.

How many benchmarks is the GPT-4 vs Mistral Medium 3.1 comparison based on?

35 benchmarks have a result for both models as of October 21, 2026. GPT-4's coding index rests on 0 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.

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