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GPT-4o (2024-08-06) vs Mistral Large 3 2512

Mistral Large 3 2512 leads GPT-4o (2024-08-06) on the Artificial Analysis Intelligence Index, 9.3 to 7.7, and Mistral Large 3 2512 costs 6.7x less per output token ($1.50 vs $10.00 per million). Updated October 22, 2026; 10 benchmarks have a result for both.

Replace GPT-4o (2024-08-06) Replace Mistral Large 3 2512
GPT-4o (2024-08-06)OpenAI
Coding
No data
Overall
26.3
Output $/M
$10.00
4
Mistral Large 3 2512Mistral AI
Coding
No data
Overall
No data
Output $/M
$1.50
6
vs boards won of 10 shared

GPT-4o (2024-08-06) or Mistral Large 3 2512: which to pick

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

Pick GPT-4o (2024-08-06) for work measured by AA Intelligence Index or MMMU Pro (Vals AI), where it leads.

Model AGPT-4o (2024-08-06)OpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BMistral Large 3 2512Mistral AINot benchmarked1 independent benchmark$0.77 per solved task
Shared results
10
GPT-4o (2024-08-06) only
48
Mistral Large 3 2512 only
18
Like-for-like categories
4 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-4o (2024-08-06) not benchmarked, Mistral Large 3 2512 not benchmarked.
Widest category
Math, 17.1 points apart on average over 2 shared benchmarks.
Widest single gap
AIME: GPT-4o (2024-08-06) 14.0% against Mistral Large 3 2512 42.9%, 29.0 points apart on a 0 to 100 scale.
Output price
GPT-4o (2024-08-06) $10.00 against Mistral Large 3 2512 $1.50 per million output tokens, 6.7x apart.
Context window
GPT-4o (2024-08-06) takes 128K tokens, Mistral Large 3 2512 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-4o (2024-08-06)BarsMistral Large 3 2512Ties
Intelligence01
Reasoning01
Math11
Knowledge33
All shared boards46
CodingDirectional onlySix of these boards feed the Vibe Coding Index10 boards, none shared
Coding benchmarks for GPT-4o (2024-08-06) and Mistral Large 3 2512
BenchmarkGPT-4o (2024-08-06)Mistral Large 3 2512Leader
Aider polyglot23.1%Not measuredOnly GPT-4o (2024-08-06) measured
SWE-bench Lite21.7%Not measuredOnly GPT-4o (2024-08-06) measured
AA Coding IndexNot measured20.1Only Mistral Large 3 2512 measured
LiveCodeBench (Vals AI)Not measured55.3%Only Mistral Large 3 2512 measured
SWE-bench Verified (Vals AI)Not measured41.4%Only Mistral Large 3 2512 measured
LiveCodeBench (Artificial Analysis run)31.7%Not measuredOnly GPT-4o (2024-08-06) measured
Terminal-Bench Hard (Artificial Analysis run)8.3%Not measuredOnly GPT-4o (2024-08-06) measured
ALE-BenchNot measured264.7Only Mistral Large 3 2512 measured
LMArena Text: coding1283Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: software and IT1278Not measuredOnly GPT-4o (2024-08-06) measured
Neither model has a result on the other 33 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GPT-4o (2024-08-06) and Mistral Large 3 2512
BenchmarkGPT-4o (2024-08-06)Mistral Large 3 2512Leader
AA Intelligence Index7.79.3Mistral Large 3 2512
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for GPT-4o (2024-08-06) and Mistral Large 3 2512
BenchmarkGPT-4o (2024-08-06)Mistral Large 3 2512Leader
AA Agentic IndexNot measured1.0Only Mistral Large 3 2512 measured
τ²-Bench Telecom28.9%Not measuredOnly GPT-4o (2024-08-06) measured
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
Reasoning benchmarks for GPT-4o (2024-08-06) and Mistral Large 3 2512
BenchmarkGPT-4o (2024-08-06)Mistral Large 3 2512Leader
GPQA DiamondNot measured68.4%Only Mistral Large 3 2512 measured
MMMU Pro (Vals AI)64.0%66.2%Mistral Large 3 2512
GPQA Diamond (Artificial Analysis run)52.1%Not measuredOnly GPT-4o (2024-08-06) measured
Humanity's Last Exam (Artificial Analysis run)2.3%Not measuredOnly GPT-4o (2024-08-06) measured
GPQA Diamond (Epoch AI run)49.2%Not measuredOnly GPT-4o (2024-08-06) measured
SimpleBench17.8%Not measuredOnly GPT-4o (2024-08-06) measured
Chess puzzles6.0%Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: hard prompts1264Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: expert1241Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: hard prompts in English1277Not measuredOnly GPT-4o (2024-08-06) measured
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index11
Math benchmarks for GPT-4o (2024-08-06) and Mistral Large 3 2512
BenchmarkGPT-4o (2024-08-06)Mistral Large 3 2512Leader
AIME14.0%42.9%Mistral Large 3 2512
MATH 500 (Vals AI)75.2%Not measuredOnly GPT-4o (2024-08-06) measured
MGSM (Vals AI)90.7%85.4%GPT-4o (2024-08-06)
OTIS Mock AIME6.4%Not measuredOnly GPT-4o (2024-08-06) measured
FrontierMath, tiers 1 to 30.4%Not measuredOnly GPT-4o (2024-08-06) measured
MATH level 553.3%Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: math1285Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: mathematical work1283Not measuredOnly GPT-4o (2024-08-06) measured
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index33
Knowledge benchmarks for GPT-4o (2024-08-06) and Mistral Large 3 2512
BenchmarkGPT-4o (2024-08-06)Mistral Large 3 2512Leader
MMLU Pro74.1%79.8%Mistral Large 3 2512
LegalBench (Vals AI)80.1%79.1%GPT-4o (2024-08-06)
CaseLaw (Vals AI)Not measured61.4%Only Mistral Large 3 2512 measured
CorpFin (Vals AI)39.4%61.0%Mistral Large 3 2512
TaxEval (Vals AI)71.1%73.1%Mistral Large 3 2512
MortgageTax (Vals AI)61.0%52.1%GPT-4o (2024-08-06)
MedQA (Vals AI)88.2%82.2%GPT-4o (2024-08-06)
SimpleQA Verified26.0%Not measuredOnly GPT-4o (2024-08-06) measured
MMLU84.3%Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: science1274Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: medicine and healthcare1252Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: legal and government1275Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: business and finance1232Not measuredOnly GPT-4o (2024-08-06) measured
Neither model has a result on the other 7 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for GPT-4o (2024-08-06) and Mistral Large 3 2512
BenchmarkGPT-4o (2024-08-06)Mistral Large 3 2512Leader
Design Arena: websitesNot measured1162Only Mistral Large 3 2512 measured
Design Arena: UI componentsNot measured1099Only Mistral Large 3 2512 measured
Design Arena: game devNot measured1079Only Mistral Large 3 2512 measured
Design Arena: data vizNot measured1137Only Mistral Large 3 2512 measured
Design Arena: 3DNot measured1099Only Mistral Large 3 2512 measured
Design Arena: all code categoriesNot measured1141Only Mistral Large 3 2512 measured
Design Arena: SVGNot measured992Only Mistral Large 3 2512 measured
Design Arena: ASCII artNot measured1069Only Mistral Large 3 2512 measured
Neither model has a result on the other 1 board here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index24 boards, none shared
General benchmarks for GPT-4o (2024-08-06) and Mistral Large 3 2512
BenchmarkGPT-4o (2024-08-06)Mistral Large 3 2512Leader
SAGE (Vals AI)Not measured24.6%Only Mistral Large 3 2512 measured
IFBench36.0%Not measuredOnly GPT-4o (2024-08-06) measured
Long context reasoning (AA-LCR)41.0%Not measuredOnly GPT-4o (2024-08-06) measured
DTBenchNot measured65.1%Only Mistral Large 3 2512 measured
LMCANot measured16.7%Only Mistral Large 3 2512 measured
LMArena Text1283Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: instruction following1267Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: creative writing1274Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Vision1065Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: English1297Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: non-English1262Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: Chinese1254Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: German1257Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: Japanese1234Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: Korean1218Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: French1263Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: Spanish1269Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: Russian1272Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: multi-turn1279Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: longer queries1283Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: writing and language1290Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: entertainment and media1267Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Vision: English1072Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Vision: Chinese1009Not measuredOnly GPT-4o (2024-08-06) measured
Neither model has a result on the other 24 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4o (2024-08-06) and Mistral Large 3 2512
BenchmarkGPT-4o (2024-08-06)Mistral Large 3 2512Leader
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-4o (2024-08-06)$0.0075Fits in one request
Mistral Large 3 2512$0.0013Fits in one request

Mistral Large 3 2512 costs less

Repository review

50K input + 3K output tokens

GPT-4o (2024-08-06)$0.155Fits in one request
Mistral Large 3 2512$0.029Fits in one request

Mistral Large 3 2512 costs less

Agent loop

200K input + 10K output tokens

GPT-4o (2024-08-06)$0.600Exceeds the context window
Mistral Large 3 2512$0.115Fits in one request

Mistral Large 3 2512 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-4o (2024-08-06) and Mistral Large 3 2512
SpecificationOpenAI GPT-4o (2024-08-06)Mistral Large 3 2512
MakerOpenAIMistral AI
WeightsNo public weights listedNo public weights listed
ReleasedAugust 6, 2024December 1, 2025
Context window128K262K
Input $/Mtok$2.50$0.50
Output $/Mtok$10.00$1.50
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computable$0.77
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4o (2024-08-06) better than Mistral Large 3 2512 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4o (2024-08-06) for work measured by AA Intelligence Index or MMMU Pro (Vals AI), where it leads.

Which is cheaper, GPT-4o (2024-08-06) or Mistral Large 3 2512?

GPT-4o (2024-08-06) costs $2.50 per million input tokens and $10.00 per million output tokens; Mistral Large 3 2512 costs $0.50 and $1.50. Cost per solved task is known for Mistral Large 3 2512 only.

Which has the bigger context window, GPT-4o (2024-08-06) or Mistral Large 3 2512?

Mistral Large 3 2512, with 262K tokens against 128K.

How many benchmarks is the GPT-4o (2024-08-06) vs Mistral Large 3 2512 comparison based on?

10 benchmarks have a result for both models as of October 22, 2026. GPT-4o (2024-08-06)'s coding index rests on 0 independent benchmarks and Mistral Large 3 2512's on 1. Where only one model has a result, the page says so instead of naming a winner.

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