Model profile
Gemini 1.5 Pro
Evidence coverage
6 of 321 tracked benchmarks are published. 0 are verified and 6 provisional. 3 of 8 categories are measured.
- Published / tracked
- 6 / 321
- Verified
- 0
- Provisional
- 6
- Categories with evidence
- 3 / 8
Evidence by category
- Agentic0 benchmarksNot measured
- Coding2 benchmarksReported
- Reasoning0 benchmarksNot measured
- Knowledge3 benchmarksReported
- Math0 benchmarksNot measured
- Multilingual0 benchmarksNot measured
- Multimodal1 benchmarkReported
- Inst. Following0 benchmarksNot measured
Gemini 1.5 Pro ranks #185 out of 200 models on the public leaderboard with an overall score of 35.71/100. It also ranks #84 out of 99 on the verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.
Gemini 1.5 Pro is a proprietary model with a 2M token context window. It processes queries without explicit chain-of-thought reasoning, offering faster response times and lower token usage.
This profile currently has 6 of 321 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 (#109). This performance profile makes it particularly well-suited for software development and code generation tasks.
Peer position
Exact provisional scores and ranks for the closest listed peers. A score can appear before a model clears the evidence threshold for a rank, so equal scores can have different rank states.
Range 34.47–38.32
- Granite-4.0-350MIBMCompare#18138.32Granite-4.0-350M is #181 with a score of 38.32.
- Granite-4.0-H-350MIBMCompare#18238.32Granite-4.0-H-350M is #182 with a score of 38.32.
- GPT-4o miniOpenAICompare#18337.87GPT-4o mini is #183 with a score of 37.87.
- Claude 4.1 Opus ThinkingAnthropicCompare#18436.55Claude 4.1 Opus Thinking is #184 with a score of 36.55.
- Gemini 1.5 ProCurrent modelGoogle#18535.71Gemini 1.5 Pro is #185 with a score of 35.71.
- Qwen2.5 Coder 32B InstructAlibabaCompare#18634.7Qwen2.5 Coder 32B Instruct is #186 with a score of 34.7.
- Ministral 3 14BMistralCompare#18734.47Ministral 3 14B is #187 with a score of 34.47.
Category percentile
More
Relative position among models eligible for each sourced category. A higher percentile means a stronger position within that category's ranked cohort; 100 is highest.
- Coding11%Eligible cohort rank #109 of 122Category score 36.6
Category evidence
Scores and ranks appear only where this model has published benchmark evidence. Categories without displayable source records remain not measured.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticWeight 22%0 benchmarksNot measured | Not measured | Not ranked | Not available | 22% | 0 benchmarks | Not measured |
| CodingRank #109 of 122Percentile 11thWeight 20%2 benchmarksReported | 36.6 | #109 of 122 | 11th | 20% | 2 benchmarks | Reported |
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | Not ranked | Not available | 17% | 0 benchmarks | Not measured |
| KnowledgeRank Not rankedWeight 12%3 benchmarksReported | 58.6 | Not ranked | Not available | 12% | 3 benchmarks | Reported |
| MathWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | Not ranked | Not available | 7% | 0 benchmarks | Not measured |
| MultimodalRank Not rankedWeight 12%1 benchmarkReported | 74.2 | Not ranked | Not available | 12% | 1 benchmark | Reported |
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
Chatbot Arena performance
Scroll horizontally to inspect confidence intervals and vote counts.
| View | Elo | Confidence interval | Votes |
|---|---|---|---|
| Text Overall | 1260 | Not available | Not available |
Benchmark Details
Rows below have a displayable published verification record. Each source link and provenance note remains in the page HTML while its category is closed. Source-unverified manual rows and generated rows stay hidden.
Coding2 benchmarks
Artificial Analysis Coding Index
Artificial Analysis SciCode
Knowledge3 benchmarks
Artificial Analysis GPQA Diamond
Artificial Analysis Humanity's Last Exam
Multimodal1 benchmark
Artificial Analysis MMMU-Pro
Frequently Asked Questions
How does Gemini 1.5 Pro perform overall in AI benchmarks?
Gemini 1.5 Pro has 6 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.
Is Gemini 1.5 Pro good for knowledge and understanding?
Gemini 1.5 Pro has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.
Is Gemini 1.5 Pro good for coding and programming?
Gemini 1.5 Pro ranks #109 out of 122 models in coding and programming benchmarks with an average score of 36.6. There are stronger options in this category.
Is Gemini 1.5 Pro good for multimodal and grounded tasks?
Gemini 1.5 Pro has visible benchmark coverage in multimodal and grounded tasks, but BenchLM does not currently assign it a global category rank there.
Does Gemini 1.5 Pro have full benchmark coverage on BenchLM?
Not yet. Gemini 1.5 Pro currently has 6 published benchmark scores out of the 321 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 1.5 Pro?
Gemini 1.5 Pro has a published context window of 2M, which determines how much text it can process in a single interaction.
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