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Model profile

Gemini 1.0 Pro

GoogleTracked
Data verified
Overall Score
21.78Public #193 of 200Verified #92 of 99
Arena Elo
1120
Eligible category ranks
0of 8
Price (1M tokens)
Not listedAPI pricing
Speed
Not listed
Context
32K

Evidence coverage

4 of 321 tracked benchmarks are published. 0 are verified and 4 provisional. 2 of 8 categories are measured.

Updated July 20, 2026Methodology
Published / tracked
4 / 321
Verified
0
Provisional
4
Categories with evidence
2 / 8

Evidence by category

  • Agentic0 benchmarks
    Not measured
  • Coding1 benchmark
    Reported
  • Reasoning0 benchmarks
    Not measured
  • Knowledge3 benchmarks
    Reported
  • Math0 benchmarks
    Not measured
  • Multilingual0 benchmarks
    Not measured
  • Multimodal0 benchmarks
    Not measured
  • Inst. Following0 benchmarks
    Not measured
ProprietaryNon-Reasoning
Confidence:
Low
base

Gemini 1.0 Pro ranks #193 out of 200 models on the public leaderboard with an overall score of 21.78/100. It also ranks #92 out of 99 on the verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.

Gemini 1.0 Pro is a proprietary model with a 32K token context window. It processes queries without explicit chain-of-thought reasoning, offering faster response times and lower token usage.

This profile currently has 4 of 321 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.

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 18.8723.49

  1. Llama 4 Maverick
    Meta
    #19123.49
    Llama 4 Maverick is #191 with a score of 23.49.
    Compare
  2. Phi-4
    Microsoft
    #19222.69
    Phi-4 is #192 with a score of 22.69.
    Compare
  3. Gemini 1.0 ProCurrent model
    Google
    #19321.78
    Gemini 1.0 Pro is #193 with a score of 21.78.
  4. Claude 3 Haiku
    Anthropic
    #19421.39
    Claude 3 Haiku is #194 with a score of 21.39.
    Compare
  5. Ministral 3 8B
    Mistral
    #19520.96
    Ministral 3 8B is #195 with a score of 20.96.
    Compare
  6. Nova Pro
    Amazon
    #19620.32
    Nova Pro is #196 with a score of 20.32.
    Compare
  7. LFM2-24B-A2B
    LiquidAI
    #19718.87
    LFM2-24B-A2B is #197 with a score of 18.87.
    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.

No eligible category percentile is available from the published evidence yet.

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 Not rankedWeight 20%1 benchmarkReported7.7
ReasoningWeight 17%0 benchmarksNot measuredNot measured
KnowledgeRank Not rankedWeight 12%3 benchmarksReported31.8
MathWeight 5%0 benchmarksNot measuredNot measured
MultilingualWeight 7%0 benchmarksNot measuredNot measured
MultimodalWeight 12%0 benchmarksNot measuredNot measured
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 Overall1120Not 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.

Coding1 benchmark
AA-SciCodeReported

Artificial Analysis SciCode

11.7%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
3.1%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

27.7%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

4.6%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.

Frequently Asked Questions

How does Gemini 1.0 Pro perform overall in AI benchmarks?

Gemini 1.0 Pro has 4 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.

Is Gemini 1.0 Pro good for knowledge and understanding?

Gemini 1.0 Pro has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.

Is Gemini 1.0 Pro good for coding and programming?

Gemini 1.0 Pro has visible benchmark coverage in coding and programming, but BenchLM does not currently assign it a global category rank there.

Does Gemini 1.0 Pro have full benchmark coverage on BenchLM?

Not yet. Gemini 1.0 Pro currently has 4 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 1.0 Pro?

Gemini 1.0 Pro has a published context window of 32K, 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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