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Model profile

Gemini 1.5 Pro

GoogleEstablishedReleased Feb 15, 2024
Data verified
Overall Score
35.71Public #185 of 200Verified #84 of 99
Arena Elo
1260
Eligible category ranks
1of 8
Price (1M tokens)
$1.25 in / $5 out
API pricing
Speed
Not listed
Context
2M

Evidence coverage

6 of 321 tracked benchmarks are published. 0 are verified and 6 provisional. 3 of 8 categories are measured.

Updated July 20, 2026Methodology
Published / tracked
6 / 321
Verified
0
Provisional
6
Categories with evidence
3 / 8

Evidence by category

  • Agentic0 benchmarks
    Not measured
  • Coding2 benchmarks
    Reported
  • Reasoning0 benchmarks
    Not measured
  • Knowledge3 benchmarks
    Reported
  • Math0 benchmarks
    Not measured
  • Multilingual0 benchmarks
    Not measured
  • Multimodal1 benchmark
    Reported
  • Inst. Following0 benchmarks
    Not measured
ProprietaryNon-Reasoning
Confidence:
Low
base

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 34.4738.32

  1. Granite-4.0-350M
    IBM
    #18138.32
    Granite-4.0-350M is #181 with a score of 38.32.
    Compare
  2. Granite-4.0-H-350M
    IBM
    #18238.32
    Granite-4.0-H-350M is #182 with a score of 38.32.
    Compare
  3. GPT-4o mini
    OpenAI
    #18337.87
    GPT-4o mini is #183 with a score of 37.87.
    Compare
  4. Claude 4.1 Opus Thinking
    Anthropic
    #18436.55
    Claude 4.1 Opus Thinking is #184 with a score of 36.55.
    Compare
  5. Gemini 1.5 ProCurrent model
    Google
    #18535.71
    Gemini 1.5 Pro is #185 with a score of 35.71.
  6. Qwen2.5 Coder 32B Instruct
    Alibaba
    #18634.7
    Qwen2.5 Coder 32B Instruct is #186 with a score of 34.7.
    Compare
  7. Ministral 3 14B
    Mistral
    #18734.47
    Ministral 3 14B is #187 with a score of 34.47.
    Compare

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.

  1. 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 scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticWeight 22%0 benchmarksNot measuredNot measured
CodingRank #109 of 122Percentile 11thWeight 20%2 benchmarksReported36.6
ReasoningWeight 17%0 benchmarksNot measuredNot measured
KnowledgeRank Not rankedWeight 12%3 benchmarksReported58.6
MathWeight 5%0 benchmarksNot measuredNot measured
MultilingualWeight 7%0 benchmarksNot measuredNot measured
MultimodalRank Not rankedWeight 12%1 benchmarkReported74.2
Inst. FollowingWeight 5%0 benchmarksNot measuredNot measured

Chatbot Arena performance

Scroll horizontally to inspect confidence intervals and vote counts.

Chatbot Arena Elo, confidence interval, and vote count by evaluation view
ViewEloConfidence intervalVotes
Text Overall1260Not availableNot 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
AA Coding IndexReported

Artificial Analysis Coding Index

23.6%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-SciCodeReported

Artificial Analysis SciCode

29.5%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Knowledge3 benchmarks
Artificial Analysis Intelligence IndexReported
10.0%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-GPQA DiamondReported

Artificial Analysis GPQA Diamond

58.9%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-HLEReported

Artificial Analysis Humanity's Last Exam

4.9%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Multimodal1 benchmark
AA-MMMU-ProReported

Artificial Analysis MMMU-Pro

55.0%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.

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.

Last updated: July 20, 2026 · Runtime metrics stay blank until BenchLM has a sourced snapshot.

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