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MiMo-V2-Flash

XiaomiCurrentReleased Mar 15, 2026
Overall Score
Est. 62Prov. #43 of 110
Arena Elo
1392
Categories Ranked
8of 8
Price (1M tokens)
$0 in / $0 out
Speed
129tok/s
Context
256K
Open WeightReasoning
Confidence
base

According to BenchLM.ai, MiMo-V2-Flash ranks #43 out of 110 models on the provisional leaderboard with an overall score of 62/100. It does not yet have enough sourced coverage for BenchLM's verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.

MiMo-V2-Flash is a open weight model with a 256K token context window. It uses explicit chain-of-thought reasoning, which typically improves performance on math and complex reasoning tasks at the cost of higher latency and token usage.

This profile currently has 4 of 152 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.

Its strongest category is Mathematics (#22), while its weakest is Instruction Following (#54). This performance profile makes it particularly strong for mathematical reasoning, scientific computing, and quantitative analysis.

Ranking Distribution

Category rank across 8 benchmark categories — sorted by best rank

Category Performance

Scores across all benchmark categories (0-100 scale)

Category Breakdown

Agentic

#29
62.6/ 100
Weight: 22%0 benchmarks
Terminal-Bench 2.0BrowseCompOSWorld-VerifiedGAIATAU-benchWebArena

Coding

#28
72.4/ 100
Weight: 20%1 benchmark
SWE-bench VerifiedLiveCodeBenchSWE-bench ProSWE-RebenchSciCode

Reasoning

#44
56.4/ 100
Weight: 17%0 benchmarks
MuSRLongBench v2MRCRv2ARC-AGI-2

Knowledge

#40
64.6/ 100
Weight: 12%2 benchmarks
GPQASuperGPQAMMLU-ProHLEFrontierScienceSimpleQA

Math

#22
82.1/ 100
Weight: 5%1 benchmark
AIME 2025BRUMO 2025MATH-500FrontierMath

Multilingual

#50
60.6/ 100
Weight: 7%0 benchmarks
MGSMMMLU-ProX

Multimodal

#39
67.3/ 100
Weight: 12%0 benchmarks
MMMU-ProOfficeQA Pro

Inst. Following

#54
63.0/ 100
Weight: 5%0 benchmarks
IFEvalIFBench

Chatbot Arena Performance

Text Overall1392

Benchmark Details

Only benchmark rows with an attached exact-source record are shown here. Source-unverified manual rows and generated rows are hidden from model pages.

Frequently Asked Questions

How does MiMo-V2-Flash perform overall in AI benchmarks?

MiMo-V2-Flash currently ranks #43 out of 110 models on BenchLM's provisional leaderboard with an overall score of 62 (estimated). It is created by Xiaomi and features a 256K context window.

Is MiMo-V2-Flash good for knowledge and understanding?

MiMo-V2-Flash ranks #40 out of 110 models in knowledge and understanding benchmarks with an average score of 64.6. There are stronger options in this category.

Is MiMo-V2-Flash good for coding and programming?

MiMo-V2-Flash ranks #28 out of 110 models in coding and programming benchmarks with an average score of 72.4. There are stronger options in this category.

Is MiMo-V2-Flash good for mathematics?

MiMo-V2-Flash ranks #22 out of 110 models in mathematics benchmarks with an average score of 82.1. There are stronger options in this category.

Is MiMo-V2-Flash open source?

Yes, MiMo-V2-Flash is an open weight model created by Xiaomi, meaning it can be downloaded and run locally or fine-tuned for specific use cases.

Does MiMo-V2-Flash have full benchmark coverage on BenchLM?

Not yet. MiMo-V2-Flash currently has 4 published benchmark scores out of the 152 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.

What is the context window size of MiMo-V2-Flash?

MiMo-V2-Flash has a context window of 256K, which determines how much text it can process in a single interaction.

Last updated: April 20, 2026 · Runtime metrics stay blank until BenchLM has a sourced snapshot.

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