Gemini 3.5 Flash
According to BenchLM.ai, Gemini 3.5 Flash ranks #11 out of 116 models on the provisional leaderboard with an overall score of 87/100. It also ranks #6 out of 24 on the verified leaderboard. This places it in the upper tier of AI models, with competitive scores across most benchmark categories.
Gemini 3.5 Flash is a proprietary model with a 1M 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.
BenchLM links it directly to Gemini 3 Flash as the earlier related model in that lineage. This profile currently has 27 of 196 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 Agentic (#3), while its weakest is Instruction Following (#37). This performance profile makes it particularly useful for coding agents, browser research, and computer-use workflows.
Ranking Distribution
Category rank across 6 benchmark categories — sorted by best rank
Category Performance
Scores across all benchmark categories (0-100 scale)
Category Breakdown
Agentic
#3Coding
#23Reasoning
#16Knowledge
Math
Multilingual
Multimodal
#17Inst. Following
#37Chatbot 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.
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See how Gemini 3.5 Flash stacks up against similar models
Frequently Asked Questions
How does Gemini 3.5 Flash perform overall in AI benchmarks?
Gemini 3.5 Flash currently ranks #11 out of 116 models on BenchLM's provisional leaderboard with an overall score of 87. It also ranks #6 out of 24 on the verified leaderboard. It is created by Google and features a 1M context window.
Is Gemini 3.5 Flash good for knowledge and understanding?
Gemini 3.5 Flash has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.
Is Gemini 3.5 Flash good for coding and programming?
Gemini 3.5 Flash ranks #23 out of 116 models in coding and programming benchmarks with an average score of 78.8. There are stronger options in this category.
Is Gemini 3.5 Flash good for reasoning and logic?
Gemini 3.5 Flash ranks #16 out of 116 models in reasoning and logic benchmarks with an average score of 79.9. There are stronger options in this category.
Is Gemini 3.5 Flash good for agentic tool use and computer tasks?
Gemini 3.5 Flash ranks #3 out of 116 models in agentic tool use and computer tasks benchmarks with an average score of 97.3. It is among the top performers in this category.
Is Gemini 3.5 Flash good for multimodal and grounded tasks?
Gemini 3.5 Flash ranks #17 out of 116 models in multimodal and grounded tasks benchmarks with an average score of 78.3. There are stronger options in this category.
Is Gemini 3.5 Flash good for instruction following?
Gemini 3.5 Flash ranks #37 out of 116 models in instruction following benchmarks with an average score of 79.2. There are stronger options in this category.
Does Gemini 3.5 Flash have full benchmark coverage on BenchLM?
Not yet. Gemini 3.5 Flash currently has 27 published benchmark scores out of the 196 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 Gemini 3.5 Flash?
Gemini 3.5 Flash has a context window of 1M, which determines how much text it can process in a single interaction.
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