Mellum2-12B-A2.5B-Thinking
BenchLM is tracking Mellum2-12B-A2.5B-Thinking, but this profile is currently excluded from the public leaderboard because it still lacks enough non-generated benchmark coverage to rank safely. Only non-generated public benchmark rows appear below.
Mellum2-12B-A2.5B-Thinking is a open weight model with a 128K 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.
Mellum2-12B-A2.5B-Thinking sits inside the Mellum2 12B-A2.5B family alongside Mellum2-12B-A2.5B-Instruct. This profile currently has 6 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 (#106). This performance profile makes it a well-rounded choice across a range of tasks.
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
Multilingual
Multimodal
Inst. Following
#106Benchmark 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 Mellum2-12B-A2.5B-Thinking stacks up against similar models
Frequently Asked Questions
How does Mellum2-12B-A2.5B-Thinking perform overall in AI benchmarks?
Mellum2-12B-A2.5B-Thinking has 6 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.
Is Mellum2-12B-A2.5B-Thinking good for knowledge and understanding?
Mellum2-12B-A2.5B-Thinking has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.
Is Mellum2-12B-A2.5B-Thinking good for coding and programming?
Mellum2-12B-A2.5B-Thinking has visible benchmark coverage in coding and programming, but BenchLM does not currently assign it a global category rank there.
Is Mellum2-12B-A2.5B-Thinking good for agentic tool use and computer tasks?
Mellum2-12B-A2.5B-Thinking has visible benchmark coverage in agentic tool use and computer tasks, but BenchLM does not currently assign it a global category rank there.
Is Mellum2-12B-A2.5B-Thinking good for instruction following?
Mellum2-12B-A2.5B-Thinking ranks #106 out of 122 models in instruction following benchmarks with an average score of 34.8. There are stronger options in this category.
Is Mellum2-12B-A2.5B-Thinking open source?
Yes, Mellum2-12B-A2.5B-Thinking is an open weight model created by JetBrains, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Which sibling models are related to Mellum2-12B-A2.5B-Thinking?
Mellum2-12B-A2.5B-Thinking belongs to the Mellum2 12B-A2.5B family. Related variants on BenchLM include Mellum2-12B-A2.5B-Instruct.
Does Mellum2-12B-A2.5B-Thinking have full benchmark coverage on BenchLM?
Not yet. Mellum2-12B-A2.5B-Thinking currently has 6 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 Mellum2-12B-A2.5B-Thinking?
Mellum2-12B-A2.5B-Thinking has a context window of 128K, which determines how much text it can process in a single interaction.
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