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Mistral Large 3

MistralMistral오픈 웨이트Apache 2.0 · 상업적 사용 가능

설명

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.

출시일
2025-12-02
파라미터
675.0B
컨텍스트 길이
262K
모달리티
image, text

능력 레이더

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

랭킹

도메인#순위점수소스
코딩 랭킹323
34.0
AA
종합 랭킹324
39.0
AA
과학298
45.0
AA

벤치마크 점수 (LLM Stats)

(LLM Stats (zeroeval))

Biology

GPQANYU + Cohere + Anthropic (2023)43.9%자체 보고

Code

LiveCodeBench34.4%자체 보고

Communication

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

Creativity

Arena Hard55.1%자체 보고

Factuality

SimpleQA23.8%자체 보고

General

MMMLU85.5%자체 보고
MMLU-Redux82.0%자체 보고
TriviaQA74.9%자체 보고

Math

MATH90.4%자체 보고
MATH (CoT)67.6%자체 보고
AMC_2022_2352.0%자체 보고

AA 평가 지수

(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

LLM Stats 카테고리 점수

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

가격

입력 가격$0.5 / 1M 토큰
출력 가격$1.5 / 1M 토큰
혼합 가격 (3:1)$0.75 / 1M 토큰

속도

토큰/초55.8
첫 토큰 지연0.71s
첫 응답 지연0.71s

공급자 가격 순위

공급자 가격 순위

7개 공급자

최저가: Mistral최고가: 302.AI
공급자입력출력
1Mistral주요
$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

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