MAI-Thinking-1
According to BenchLM.ai, MAI-Thinking-1 ranks #43 out of 122 models on the provisional leaderboard with an overall score of 65/100. It also ranks #23 out of 31 on the verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.
MAI-Thinking-1 is a proprietary 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 14 of 236 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 Instruction Following (#1), while its weakest is Knowledge (#47). This performance profile makes it a well-rounded choice across a range of tasks.
Ranking Distribution
Category rank across 5 benchmark categories — sorted by best rank
Category Performance
Scores across all benchmark categories (0-100 scale)
Category Breakdown
Agentic
Coding
#15Reasoning
Knowledge
#47Math
Multilingual
Multimodal
Inst. Following
#1Benchmark 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.
Compare This Model
See how MAI-Thinking-1 stacks up against similar models
Frequently Asked Questions
How does MAI-Thinking-1 perform overall in AI benchmarks?
MAI-Thinking-1 currently ranks #43 out of 122 models on BenchLM's provisional leaderboard with an overall score of 65. It also ranks #23 out of 31 on the verified leaderboard. It is created by Microsoft and features a 256K context window.
Is MAI-Thinking-1 good for knowledge and understanding?
MAI-Thinking-1 ranks #47 out of 122 models in knowledge and understanding benchmarks with an average score of 64.6. There are stronger options in this category.
Is MAI-Thinking-1 good for coding and programming?
MAI-Thinking-1 ranks #15 out of 122 models in coding and programming benchmarks with an average score of 84.5. There are stronger options in this category.
Is MAI-Thinking-1 good for mathematics?
MAI-Thinking-1 has visible benchmark coverage in mathematics, but BenchLM does not currently assign it a global category rank there.
Is MAI-Thinking-1 good for reasoning and logic?
MAI-Thinking-1 has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.
Is MAI-Thinking-1 good for agentic tool use and computer tasks?
MAI-Thinking-1 has visible benchmark coverage in agentic tool use and computer tasks, but BenchLM does not currently assign it a global category rank there.
Is MAI-Thinking-1 good for instruction following?
MAI-Thinking-1 ranks #1 out of 122 models in instruction following benchmarks with an average score of 100. It is among the top performers in this category.
Does MAI-Thinking-1 have full benchmark coverage on BenchLM?
Not yet. MAI-Thinking-1 currently has 14 published benchmark scores out of the 236 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 MAI-Thinking-1?
MAI-Thinking-1 has a context window of 256K, which determines how much text it can process in a single interaction.
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