Qwen3.6-27B
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
According to BenchLM.ai, Qwen3.6-27B ranks #28 out of 111 models on the provisional leaderboard with an overall score of 72/100. It also ranks #10 out of 15 on the verified leaderboard. This places it in the mid-tier of AI models, with strengths in specific benchmark categories.
Qwen3.6-27B is a open weight model with a 262K 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 37 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 Coding (#9), while its weakest is Multimodal & Grounded (#35). This performance profile makes it particularly well-suited for software development and code generation tasks.
Ranking Distribution
Category rank across 4 benchmark categories — sorted by best rank
Category Performance
Scores across all benchmark categories (0-100 scale)
Category Breakdown
Agentic
Coding
#9Reasoning
Knowledge
#33Math
Multilingual
Multimodal
#35Inst. Following
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.
Compare This Model
See how Qwen3.6-27B stacks up against similar models
Frequently Asked Questions
How does Qwen3.6-27B perform overall in AI benchmarks?
Qwen3.6-27B currently ranks #28 out of 111 models on BenchLM's provisional leaderboard with an overall score of 72. It also ranks #10 out of 15 on the verified leaderboard. It is created by Alibaba and features a 262K context window.
Is Qwen3.6-27B good for knowledge and understanding?
Qwen3.6-27B ranks #33 out of 111 models in knowledge and understanding benchmarks with an average score of 69.7. There are stronger options in this category.
Is Qwen3.6-27B good for coding and programming?
Qwen3.6-27B ranks #9 out of 111 models in coding and programming benchmarks with an average score of 86.9. It is among the top performers in this category.
Is Qwen3.6-27B good for mathematics?
Qwen3.6-27B has visible benchmark coverage in mathematics, but BenchLM does not currently assign it a global category rank there.
Is Qwen3.6-27B good for agentic tool use and computer tasks?
Qwen3.6-27B has visible benchmark coverage in agentic tool use and computer tasks, but BenchLM does not currently assign it a global category rank there.
Is Qwen3.6-27B good for multimodal and grounded tasks?
Qwen3.6-27B ranks #35 out of 111 models in multimodal and grounded tasks benchmarks with an average score of 68.6. There are stronger options in this category.
Is Qwen3.6-27B open source?
Yes, Qwen3.6-27B is an open weight model created by Alibaba, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Does Qwen3.6-27B have full benchmark coverage on BenchLM?
Not yet. Qwen3.6-27B currently has 37 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 Qwen3.6-27B?
Qwen3.6-27B has a context window of 262K, which determines how much text it can process in a single interaction.
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