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Mistral Large 3

MistralMistralOpen WeightApache 2.0 · Uso Comercial

Descripción

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.

Fecha de lanzamiento
2025-12-02
Parámetros
675.0B
Longitud del contexto
262K
Modalidades
image, text

Radar de capacidades

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

Rankings

Dominio#PosiciónPuntuaciónFuente
Ranking de codificación323
34.0
AA
Ranking general324
39.0
AA
Ciencia298
45.0
AA

Puntuaciones 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.

Índices de evaluación 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

Puntuaciones por categoría LLM Stats

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

Precios

Precio de entrada$0.5 / 1M tokens
Precio de salida$1.5 / 1M tokens
Precio mixto (3:1)$0.75 / 1M tokens

Velocidad

Tokens/seg55.8
Retraso del primer token0.71s
Tiempo hasta la respuesta0.71s

Ranking de Precios por Proveedor

Ranking de Precios por Proveedor

7 proveedores

Más barato: MistralMás caro: 302.AI
ProveedorEntradaSalida
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

Comparar precios entre diferentes proveedores de API para este modelo.

Fuentes externas