Qwen3.5-35B-A3B
According to BenchLM.ai, Qwen3.5-35B-A3B ranks #56 out of 115 models on the provisional leaderboard with an overall score of 56/100. It also ranks #18 out of 23 on the verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.
Qwen3.5-35B-A3B 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 15 of 193 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 Knowledge (#26), while its weakest is Agentic (#48). This performance profile makes it particularly effective for knowledge-intensive tasks like research, analysis, and factual Q&A.
Ranking Distribution
Category rank across 7 benchmark categories — sorted by best rank
Category Performance
Scores across all benchmark categories (0-100 scale)
Category Breakdown
Agentic
#48Coding
#43Reasoning
Knowledge
#26Math
Multilingual
#32Multimodal
#46Inst. Following
#30Chatbot Arena Performance
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 Qwen3.5-35B-A3B stacks up against similar models
Frequently Asked Questions
How does Qwen3.5-35B-A3B perform overall in AI benchmarks?
Qwen3.5-35B-A3B currently ranks #56 out of 115 models on BenchLM's provisional leaderboard with an overall score of 56. It also ranks #18 out of 23 on the verified leaderboard. It is created by Alibaba and features a 262K context window.
Is Qwen3.5-35B-A3B good for knowledge and understanding?
Qwen3.5-35B-A3B ranks #26 out of 115 models in knowledge and understanding benchmarks with an average score of 76.2. There are stronger options in this category.
Is Qwen3.5-35B-A3B good for coding and programming?
Qwen3.5-35B-A3B ranks #43 out of 115 models in coding and programming benchmarks with an average score of 60.9. There are stronger options in this category.
Is Qwen3.5-35B-A3B good for reasoning and logic?
Qwen3.5-35B-A3B has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.
Is Qwen3.5-35B-A3B good for agentic tool use and computer tasks?
Qwen3.5-35B-A3B ranks #48 out of 115 models in agentic tool use and computer tasks benchmarks with an average score of 47.6. There are stronger options in this category.
Is Qwen3.5-35B-A3B good for multimodal and grounded tasks?
Qwen3.5-35B-A3B ranks #46 out of 115 models in multimodal and grounded tasks benchmarks with an average score of 59. There are stronger options in this category.
Is Qwen3.5-35B-A3B good for instruction following?
Qwen3.5-35B-A3B ranks #30 out of 115 models in instruction following benchmarks with an average score of 82.1. There are stronger options in this category.
Is Qwen3.5-35B-A3B good for multilingual tasks?
Qwen3.5-35B-A3B ranks #32 out of 115 models in multilingual tasks benchmarks with an average score of 70.6. There are stronger options in this category.
Is Qwen3.5-35B-A3B open source?
Yes, Qwen3.5-35B-A3B is an open weight model created by Alibaba, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Does Qwen3.5-35B-A3B have full benchmark coverage on BenchLM?
Not yet. Qwen3.5-35B-A3B currently has 15 published benchmark scores out of the 193 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 Qwen3.5-35B-A3B?
Qwen3.5-35B-A3B has a context window of 262K, which determines how much text it can process in a single interaction.
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