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MiMo-V2-Flash (Non-reasoning)

Xiaomi開源權重MIT · 商用許可

描述

MiMo-V2-Flash is a powerful, efficient, and ultra-fast foundation language model that excels in reasoning, coding, and agentic scenarios. It is a Mixture-of-Experts model with 309B total parameters and 15B active parameters, featuring a hybrid attention architecture with sliding-window and full attention (5:1 ratio, 128-token window). Delivers 150 tokens/sec inference with 256k context window.

發布日期
2025-12-16
參數規模
309.0B
上下文長度
262K
支援模態
text

能力雷達圖

37
general
44
coding
67
reasoning
40
science
60
agents
0
multimodal

排行榜排名

領域#排名分數來源
智慧體能力模型榜114
35.0
LS
程式碼能力榜210
51.0
AA
通用能力榜183
57.0
AA
科學能力324
41.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Agents

Tau-bench80.3%自報
BrowseCompOpenAI (2025)58.3%自報
Terminal-Bench 2.0Stanford × Laude Institute (2026)38.5%自報
Terminal-Bench30.5%自報

Biology

GPQANYU + Cohere + Anthropic (2023)83.7%自報

Code

SWE-Bench Verified73.4%自報
SWE-bench Multilingual71.7%自報

Creativity

Arena-Hard v286.2%自報

Finance

MMLU-Pro84.9%自報

General

LiveCodeBench v680.6%自報
LongBench v260.6%自報
MRCR45.7%自報

Math

AIME 202594.1%自報
HMMT 202584.4%自報
Humanity's Last Exam22.1%自報

AA 評測指數

(Artificial Analysis)
Math Index(Artificial Analysis)
67.7
Coding Index(Artificial Analysis)
49.8
Intelligence Index(Artificial Analysis)
25.1
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.8
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.7
Aime 25(MAA (Mathematical Association of America))
0.7
Gpqa(NYU + Cohere + Anthropic (2023))
0.7
Terminalbench V2 1
0.6
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.4
Ifbench(Google Research (2023))
0.4
Lcr(Artificial Analysis)
0.3
Scicode(UIUC + Argonne National Lab (2024))
0.3
Terminalbench Hard(Stanford × Laude Institute (2026))
0.3
Hle(Center for AI Safety + Scale AI (2025))
0.1

LLM Stats 分類評分

(LLM Stats (zeroeval))
Creativity
90
Writing
90
Legal
80
Physics
80
Language
80
Finance
80
Healthcare
80
Biology
80
Chemistry
80
Math
70
Reasoning
70
Frontend Development
70
General
70
Search
60
Structured Output
60
Tool Calling
60
Long Context
50
Agents
50
Code
50
Vision
20

定價

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混合價格(3:1)免費
快取讀取價格$0.0028 / 1M tokens

速度

Tokens/秒0.0
首Token延遲0.00s
首回答延遲0.00s

供應商價格排行

暫無提供商資料

外部連結

LLM StatsArtificial Analysis