MiniCPM5-1B
According to BenchLM.ai, MiniCPM5-1B ranks #89 out of 119 models on the provisional leaderboard with an overall score of 34/100. It also ranks #28 out of 28 on the verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.
MiniCPM5-1B is a open weight model with a 131K 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 14 of 225 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 (#64), while its weakest is Instruction Following (#104). This performance profile makes it particularly strong for mathematical reasoning, scientific computing, and quantitative analysis.
Ranking Distribution
Category rank across 3 benchmark categories — sorted by best rank
Category Performance
Scores across all benchmark categories (0-100 scale)
Category Breakdown
Agentic
Coding
Reasoning
Knowledge
Math
#64Multilingual
Multimodal
Inst. Following
#104Benchmark 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.
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Frequently Asked Questions
How does MiniCPM5-1B perform overall in AI benchmarks?
MiniCPM5-1B currently ranks #89 out of 119 models on BenchLM's provisional leaderboard with an overall score of 34 (estimated). It also ranks #28 out of 28 on the verified leaderboard. It is created by OpenBMB and features a 131K context window.
Is MiniCPM5-1B good for knowledge and understanding?
MiniCPM5-1B has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.
Is MiniCPM5-1B good for coding and programming?
MiniCPM5-1B has visible benchmark coverage in coding and programming, but BenchLM does not currently assign it a global category rank there.
Is MiniCPM5-1B good for mathematics?
MiniCPM5-1B ranks #64 out of 119 models in mathematics benchmarks with an average score of 37. There are stronger options in this category.
Is MiniCPM5-1B good for reasoning and logic?
MiniCPM5-1B has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.
Is MiniCPM5-1B good for agentic tool use and computer tasks?
MiniCPM5-1B has visible benchmark coverage in agentic tool use and computer tasks, but BenchLM does not currently assign it a global category rank there.
Is MiniCPM5-1B good for instruction following?
MiniCPM5-1B ranks #104 out of 119 models in instruction following benchmarks with an average score of 31.9. There are stronger options in this category.
Is MiniCPM5-1B open source?
Yes, MiniCPM5-1B is an open weight model created by OpenBMB, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Does MiniCPM5-1B have full benchmark coverage on BenchLM?
Not yet. MiniCPM5-1B currently has 14 published benchmark scores out of the 225 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 MiniCPM5-1B?
MiniCPM5-1B has a context window of 131K, which determines how much text it can process in a single interaction.
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