Model profile
MiMo-V2-Flash
Evidence coverage
19 of 321 tracked benchmarks are published. 1 is verified and 18 provisional. 6 of 8 categories are measured.
- Published / tracked
- 19 / 321
- Verified
- 1
- Provisional
- 18
- Categories with evidence
- 6 / 8
Evidence by category
- Agentic4 benchmarksReported
- Coding3 benchmarksMixed evidence
- Reasoning2 benchmarksReported
- Knowledge8 benchmarksReported
- Math1 benchmarkReported
- Multilingual0 benchmarksNot measured
- Multimodal0 benchmarksNot measured
- Inst. Following1 benchmarkReported
MiMo-V2-Flash ranks #91 out of 200 models on the public leaderboard with an overall score of 54.06/100. It also ranks #52 out of 99 on the 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 19 of 321 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 Coding (#39), while its weakest is Agentic (#63). This performance profile makes it particularly well-suited for software development and code generation tasks.
Peer position
Exact provisional scores and ranks for the closest listed peers. A score can appear before a model clears the evidence threshold for a rank, so equal scores can have different rank states.
Range 53.61–54.48
- GPT-5.1-Codex-MaxOpenAICompare#9054.48GPT-5.1-Codex-Max is #90 with a score of 54.48.
- MiMo-V2-FlashCurrent modelXiaomi#9154.06MiMo-V2-Flash is #91 with a score of 54.06.
- DeepSeek V4 Flash (High)DeepSeekCompare#9253.95DeepSeek V4 Flash (High) is #92 with a score of 53.95.
- Qwen3.6-27BAlibabaCompare#9353.82Qwen3.6-27B is #93 with a score of 53.82.
- GPT-5.1OpenAICompare#9453.65GPT-5.1 is #94 with a score of 53.65.
- DeepSeek V3.1DeepSeekCompare#9553.64DeepSeek V3.1 is #95 with a score of 53.64.
- Claude Sonnet 4.5AnthropicCompare#9653.61Claude Sonnet 4.5 is #96 with a score of 53.61.
Category percentile
More
Relative position among models eligible for each sourced category. A higher percentile means a stronger position within that category's ranked cohort; 100 is highest.
- Coding69%Eligible cohort rank #39 of 122Category score 54.0
- Agentic47%Eligible cohort rank #63 of 119Category score 47.2
Category evidence
Scores and ranks appear only where this model has published benchmark evidence. Categories without displayable source records remain not measured.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #63 of 119Percentile 47thWeight 22%4 benchmarksReported | 47.2 | #63 of 119 | 47th | 22% | 4 benchmarks | Reported |
| CodingRank #39 of 122Percentile 69thWeight 20%3 benchmarksMixed sources | 54.0 | #39 of 122 | 69th | 20% | 3 benchmarks | Mixed sources |
| ReasoningRank Not rankedWeight 17%2 benchmarksReported | 66.2 | Not ranked | Not available | 17% | 2 benchmarks | Reported |
| KnowledgeRank Not rankedWeight 12%8 benchmarksReported | 51.3 | Not ranked | Not available | 12% | 8 benchmarks | Reported |
| MathWeight 5%1 benchmarkReported | Score pending | Not ranked | Not available | 5% | 1 benchmark | Reported |
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | Not ranked | Not available | 7% | 0 benchmarks | Not measured |
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | Not ranked | Not available | 12% | 0 benchmarks | Not measured |
| Inst. FollowingRank Not rankedWeight 5%1 benchmarkReported | 84.0 | Not ranked | Not available | 5% | 1 benchmark | Reported |
Chatbot Arena performance
Scroll horizontally to inspect confidence intervals and vote counts.
| View | Elo | Confidence interval | Votes |
|---|---|---|---|
| Text Overall | 1392 | Not available | Not available |
Benchmark Details
Rows below have a displayable published verification record. Each source link and provenance note remains in the page HTML while its category is closed. Source-unverified manual rows and generated rows stay hidden.
Agentic4 benchmarks
Artificial Analysis Agentic Index
τ²-Bench Tool-Agent-User Evaluation
GDPval-AA normalized
Coding3 benchmarks
Software Engineering Benchmark Verified
Artificial Analysis Coding Index
Artificial Analysis SciCode
Reasoning2 benchmarks
Artificial Analysis Long Context Reasoning
Critical Physics Tasks
Knowledge8 benchmarks
Massive Multitask Language Understanding Professional
Graduate-Level Google-Proof Q&A
Artificial Analysis GPQA Diamond
Artificial Analysis Humanity's Last Exam
Artificial Analysis Omniscience Index
Artificial Analysis Omniscience Accuracy
Artificial Analysis Omniscience Hallucination Rate
Math1 benchmark
American Invitational Mathematics Examination 2025
Inst. Following1 benchmark
Artificial Analysis IFBench
Frequently Asked Questions
How does MiMo-V2-Flash perform overall in AI benchmarks?
MiMo-V2-Flash has 19 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.
Is MiMo-V2-Flash good for knowledge and understanding?
MiMo-V2-Flash has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.
Is MiMo-V2-Flash good for coding and programming?
MiMo-V2-Flash ranks #39 out of 122 models in coding and programming benchmarks with an average score of 54. There are stronger options in this category.
Is MiMo-V2-Flash good for mathematics?
MiMo-V2-Flash has visible benchmark coverage in mathematics, but BenchLM does not currently assign it a global category rank there.
Is MiMo-V2-Flash good for reasoning and logic?
MiMo-V2-Flash has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.
Is MiMo-V2-Flash good for agentic tool use and computer tasks?
MiMo-V2-Flash ranks #63 out of 119 models in agentic tool use and computer tasks benchmarks with an average score of 47.2. There are stronger options in this category.
Is MiMo-V2-Flash good for instruction following?
MiMo-V2-Flash has visible benchmark coverage in instruction following, but BenchLM does not currently assign it a global category rank there.
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 19 published benchmark scores out of the 321 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 published context window of 256K, which determines how much text it can process in a single interaction.
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