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Mistral Large 3

MistralMistralOpen WeightApache 2.0 · Usage Commercial

Description

Mistral Large 3 (675B Instruct 2512 Eagle) is a state-of-the-art general-purpose Multimodal granular Mixture-of-Experts model with 41B active parameters and 675B total parameters trained from scratch with 3000 H200s. This model is the base pre-trained version, not fine-tuned for instruction or reasoning tasks, making it ideal for custom post-training processes. Designed for reliability and long-context comprehension - It is engineered for production-grade assistants, retrieval-augmented systems, scientific workloads, and complex enterprise workflows. This model is the Eagle speculator for Mistral Large 3 Instruct. Depending on the task, you can expect noticeable speed-ups on your generations.

Date de sortie
2025-12-02
Paramètres
675.0B
Longueur du contexte
262K
Modalités
image, text

Radar de capacités

34
general
31
coding
43
reasoning
44
science
39
agents
85
multimodal

Classements

Domaine#RangScoreSource
Classement codage323
34.0
AA
Classement général324
39.0
AA
Science298
45.0
AA

Scores de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

Biology

GPQANYU + Cohere + Anthropic (2023)43.9%Aut.

Code

LiveCodeBench34.4%Aut.

Communication

MM-MT-Bench84.90 / 100Aut.
Wild Bench68.5%Aut.

Creativity

Arena Hard55.1%Aut.

Factuality

SimpleQA23.8%Aut.

General

MMMLU85.5%Aut.
MMLU-Redux82.0%Aut.
TriviaQA74.9%Aut.

Math

MATH90.4%Aut.
MATH (CoT)67.6%Aut.
AMC_2022_2352.0%Aut.

Indices d'évaluation AA

(Artificial Analysis)
Math Index(Artificial Analysis)
38.0
Coding Index(Artificial Analysis)
20.1
Intelligence Index(Artificial Analysis)
15.9
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.8
Gpqa(NYU + Cohere + Anthropic (2023))
0.7
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.5
Aime 25(MAA (Mathematical Association of America))
0.4
Scicode(UIUC + Argonne National Lab (2024))
0.4
Ifbench(Google Research (2023))
0.4
Lcr(Artificial Analysis)
0.3
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.2
Terminalbench Hard(Stanford × Laude Institute (2026))
0.2
Terminalbench V2 1
0.1
Tau Banking
0.1
Hle(Center for AI Safety + Scale AI (2025))
0.0

Scores par catégorie LLM Stats

(LLM Stats (zeroeval))
Language
90
Math
70
Reasoning
50
General
50
Physics
40
Biology
40
Chemistry
40
Code
30
Factuality
20

Tarification

Prix d'entrée$0.5 / 1M tokens
Prix de sortie$1.5 / 1M tokens
Prix mixte (3:1)$0.75 / 1M tokens

Vitesse

Tokens/sec55.8
Délai du premier token0.71s
Temps de réponse0.71s

Classement des Prix par Fournisseur

Classement des Prix par Fournisseur

7 fournisseurs

Moins cher: MistralPlus cher: 302.AI
FournisseurEntréeSortie
1MistralPRINCIPAL
$0.5
$1.5
2OpenRouter
$0.5
$1.5
3Kilo Gateway
$0.5
$1.5
4LLM Gateway
$0.5
$1.5
5Pioneer
$0.5
$1.5
6Cortecs
$0.557
$1.671
7302.AI
$1.1
$3.3

Comparer les prix entre différents fournisseurs API pour ce modèle.

Sources externes