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GPT-4.1 vs Mistral Medium 3

Updated October 21, 2026. 57 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GPT-4.1 Replace Mistral Medium 3
GPT-4.1OpenAI
Coding
No data
Overall
12.7
Output $/M
$8.00
52
Mistral Medium 3Mistral AI
Coding
No data
Overall
9.0
Output $/M
$2.00
5
vs boards won of 57 shared

Decision reading

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

GPT-4.1 has the edge where the context window is larger, 1.05M against 131K tokens, and where what matters is LMArena Text: medicine and healthcare or Design Arena: websites, where it leads.

Model AGPT-4.1OpenAINot benchmarkedNo coding benchmark$0.37 per solved taskModel BMistral Medium 3Mistral AINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
57
GPT-4.1 only
30
Mistral Medium 3 only
0
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-4.1 not benchmarked, Mistral Medium 3 not benchmarked.
Widest category
Agentic work, 22.8 points apart on average over 1 shared benchmark.
Widest single gap
Long context reasoning (AA-LCR): GPT-4.1 68.3% against Mistral Medium 3 31.3%, 37.0 points apart on a 0 to 100 scale.
Output price
GPT-4.1 $8.00 against Mistral Medium 3 $2.00 per million output tokens, 4.0x apart.
Context window
GPT-4.1 takes 1.05M tokens, Mistral Medium 3 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-4.1BarsMistral Medium 3Ties
Coding40
Intelligence20
Agentic work10
Reasoning70
Math40
Knowledge41
Web design24
General280
All shared boards525
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for GPT-4.1 and Mistral Medium 3
BenchmarkGPT-4.1Mistral Medium 3Leader
Aider polyglot52.4%Not measuredOnly GPT-4.1 measured
SWE-bench Verified39.6%Not measuredOnly GPT-4.1 measured
SWE-bench Multimodal31.1%Not measuredOnly GPT-4.1 measured
LiveCodeBench (Vals AI)54.7%Not measuredOnly GPT-4.1 measured
LiveCodeBench (Artificial Analysis run)45.7%40.0%GPT-4.1
Terminal-Bench Hard (Artificial Analysis run)13.6%3.8%GPT-4.1
WeirdML39.0%Not measuredOnly GPT-4.1 measured
ALE-Bench558.1Not measuredOnly GPT-4.1 measured
LMArena Text: coding13901385GPT-4.1
LMArena Text: software and IT13911385GPT-4.1
Neither model has a result on the other 28 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for GPT-4.1 and Mistral Medium 3
BenchmarkGPT-4.1Mistral Medium 3Leader
AA Intelligence Index12.79.0GPT-4.1
Epoch Capabilities Index136.7134.0GPT-4.1
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GPT-4.1 and Mistral Medium 3
BenchmarkGPT-4.1Mistral Medium 3Leader
τ²-Bench Telecom47.1%24.3%GPT-4.1
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index70
Reasoning benchmarks for GPT-4.1 and Mistral Medium 3
BenchmarkGPT-4.1Mistral Medium 3Leader
GPQA Diamond65.4%Not measuredOnly GPT-4.1 measured
MMMU Pro (Vals AI)72.4%Not measuredOnly GPT-4.1 measured
GPQA Diamond (Artificial Analysis run)66.6%57.8%GPT-4.1
Humanity's Last Exam (Artificial Analysis run)4.2%4.1%GPT-4.1
GPQA Diamond (Epoch AI run)66.9%Not measuredOnly GPT-4.1 measured
ARC-AGI5.5%Not measuredOnly GPT-4.1 measured
ARC-AGI-20.4%Not measuredOnly GPT-4.1 measured
SimpleBench27.0%Not measuredOnly GPT-4.1 measured
Chess puzzles3.0%Not measuredOnly GPT-4.1 measured
LMArena Text: hard prompts13841364GPT-4.1
LMArena Text: expert13641342GPT-4.1
LMArena Text: hard prompts in English13931374GPT-4.1
LMArena Vision: diagrams12151155GPT-4.1
LMArena Vision: homework12481165GPT-4.1
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index40
Math benchmarks for GPT-4.1 and Mistral Medium 3
BenchmarkGPT-4.1Mistral Medium 3Leader
AIME39.6%Not measuredOnly GPT-4.1 measured
MATH 500 (Vals AI)87.2%Not measuredOnly GPT-4.1 measured
MGSM (Vals AI)87.7%Not measuredOnly GPT-4.1 measured
AA Math Index34.730.3GPT-4.1
AIME 2025 (Artificial Analysis run)34.7%30.3%GPT-4.1
OTIS Mock AIME38.3%Not measuredOnly GPT-4.1 measured
FrontierMath, tiers 1 to 36.0%Not measuredOnly GPT-4.1 measured
MATH level 583.0%Not measuredOnly GPT-4.1 measured
LMArena Text: math13691353GPT-4.1
LMArena Text: mathematical work13601354GPT-4.1
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
Knowledge benchmarks for GPT-4.1 and Mistral Medium 3
BenchmarkGPT-4.1Mistral Medium 3Leader
MMLU Pro80.5%Not measuredOnly GPT-4.1 measured
LegalBench (Vals AI)83.1%Not measuredOnly GPT-4.1 measured
CaseLaw (Vals AI)69.9%Not measuredOnly GPT-4.1 measured
CorpFin (Vals AI)63.0%Not measuredOnly GPT-4.1 measured
TaxEval (Vals AI)75.1%Not measuredOnly GPT-4.1 measured
MortgageTax (Vals AI)65.9%Not measuredOnly GPT-4.1 measured
MedQA (Vals AI)91.2%Not measuredOnly GPT-4.1 measured
MMLU Pro (Artificial Analysis run)80.6%76.0%GPT-4.1
SimpleQA Verified31.1%Not measuredOnly GPT-4.1 measured
GeoBench72.0%Not measuredOnly GPT-4.1 measured
LMArena Text: science13821381GPT-4.1
LMArena Text: medicine and healthcare13791381Mistral Medium 3
LMArena Text: legal and government13991384GPT-4.1
LMArena Text: business and finance13691352GPT-4.1
Neither model has a result on the other 3 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index24
Web design benchmarks for GPT-4.1 and Mistral Medium 3
BenchmarkGPT-4.1Mistral Medium 3Leader
Design Arena: websites10391079Mistral Medium 3
Design Arena: UI components10001024Mistral Medium 3
Design Arena: game dev10791018GPT-4.1
Design Arena: data viz11041034GPT-4.1
Design Arena: 3D8501083Mistral Medium 3
Design Arena: all code categories10261069Mistral Medium 3
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index280
General benchmarks for GPT-4.1 and Mistral Medium 3
BenchmarkGPT-4.1Mistral Medium 3Leader
IFBench43.0%39.3%GPT-4.1
Long context reasoning (AA-LCR)68.3%31.3%GPT-4.1
DTBench68.3%62.3%GPT-4.1
LMCA25.6%Not measuredOnly GPT-4.1 measured
Fiction.LiveBench63.9%Not measuredOnly GPT-4.1 measured
LMArena Text13831370GPT-4.1
LMArena Text: instruction following13671338GPT-4.1
LMArena Text: creative writing13631343GPT-4.1
LMArena Vision12101157GPT-4.1
LMArena Text: English13921385GPT-4.1
LMArena Text: non-English13701353GPT-4.1
LMArena Text: Chinese13821374GPT-4.1
LMArena Text: German13811377GPT-4.1
LMArena Text: Japanese13191316GPT-4.1
LMArena Text: Korean13381304GPT-4.1
LMArena Text: French13821368GPT-4.1
LMArena Text: Spanish13761364GPT-4.1
LMArena Text: Russian13771359GPT-4.1
LMArena Text: Polish13891371GPT-4.1
LMArena Text: multi-turn13971384GPT-4.1
LMArena Text: longer queries13851360GPT-4.1
LMArena Text: writing and language13711352GPT-4.1
LMArena Text: entertainment and media13651335GPT-4.1
LMArena Vision: English12091172GPT-4.1
LMArena Vision: Chinese12261161GPT-4.1
LMArena Vision: reading text12181154GPT-4.1
LMArena Vision: humor11961145GPT-4.1
LMArena Vision: captioning12071094GPT-4.1
LMArena Vision: recognizing things12081141GPT-4.1
LMArena Vision: creative writing12101146GPT-4.1
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-4.1 and Mistral Medium 3
BenchmarkGPT-4.1Mistral Medium 3Leader
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-4.1$0.0060Fits in one request
Mistral Medium 3$0.0014Fits in one request

Mistral Medium 3 costs less

Repository review

50K input + 3K output tokens

GPT-4.1$0.124Fits in one request
Mistral Medium 3$0.026Fits in one request

Mistral Medium 3 costs less

Agent loop

200K input + 10K output tokens

GPT-4.1$0.480Fits in one request
Mistral Medium 3$0.100Exceeds the context window

Mistral Medium 3 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-4.1 and Mistral Medium 3
SpecificationOpenAI GPT-4.1Mistral Medium 3
MakerOpenAIMistral AI
WeightsNo public weights listedNo public weights listed
ReleasedApril 14, 2025May 7, 2025
Context window1.05M131K
Input $/Mtok$2.00$0.40
Output $/Mtok$8.00$2.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved task$0.37Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4.1 better than Mistral Medium 3 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. GPT-4.1 has the edge where the context window is larger, 1.05M against 131K tokens, and where what matters is LMArena Text: medicine and healthcare or Design Arena: websites, where it leads.

Which is cheaper, GPT-4.1 or Mistral Medium 3?

GPT-4.1 costs $2.00 per million input tokens and $8.00 per million output tokens; Mistral Medium 3 costs $0.40 and $2.00. Cost per solved task is known for GPT-4.1 only.

Which has the bigger context window, GPT-4.1 or Mistral Medium 3?

GPT-4.1, with 1.05M tokens against 131K.

How many benchmarks is the GPT-4.1 vs Mistral Medium 3 comparison based on?

57 benchmarks have a result for both models as of October 21, 2026. GPT-4.1's coding index rests on 0 independent benchmarks and Mistral Medium 3's on 0. Where only one model has a result, the page says so instead of naming a winner.

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