Decision support

Gemini 3.7 Flash vs Pareto 26.10

Compare canonical objects directly. The useful dimensions change with the object type, so model and hardware comparisons stay separate.

Gemini 3.7 Flash

Google DeepMind

Sources:models.devOpenRouter

Pareto 26.10

Unbiased

Sources:OpenRouter

Benchmark results

  • DeepSWE 1.1

    Best pass@1 · Higher is better

    • Gemini 3.7 Flash
      65.5%
      #12 of 28
    • Pareto 26.10
      Not reported
    Runs and sources
    Gemini 3.7 Flash
    • low53.8%mini-swe-agent · pass@4 77.9% · $1.83 / attempt
    • medium65.5%mini-swe-agent · pass@4 83.2% · $2.03 / attempt
    • high65.3%mini-swe-agent · pass@4 82.3% · $2.18 / attempt
    Pareto 26.10

    Not reported

  • Arena Text

    Arena rating · Higher is better

    • Gemini 3.7 Flash
      1489
      Arena #16CI 1485 to 1494
    • Pareto 26.10
      Not reported
    Runs and sources
    Gemini 3.7 Flash
    • high148995% CI 1485 to 1494 · 33,300 votes
    Pareto 26.10

    Not reported

  • Arena WebDev

    Arena rating · Higher is better

    • Gemini 3.7 Flash
      1588
      Arena #40CI 1582 to 1595
    • Pareto 26.10
      Not reported
    Runs and sources
    Gemini 3.7 Flash
    • high158895% CI 1582 to 1595 · 14,591 votes
    Pareto 26.10

    Not reported

  • Arena Vision

    Arena rating · Higher is better

    • Gemini 3.7 Flash
      1294
      Arena #8CI 1285 to 1302
    • Pareto 26.10
      Not reported
    Runs and sources
    Gemini 3.7 Flash
    • high129495% CI 1285 to 1302 · 6,840 votes
    Pareto 26.10

    Not reported

  • Arena Document

    Arena rating · Higher is better

    • Gemini 3.7 Flash
      1468
      Arena #21CI 1460 to 1476
    • Pareto 26.10
      Not reported
    Runs and sources
    Gemini 3.7 Flash
    • high146895% CI 1460 to 1476 · 7,680 votes
    Pareto 26.10

    Not reported

  • Agent Arena

    IPS score · Higher is better

    • Gemini 3.7 Flash
      -0.022
      Arena #37CI -0.031 to -0.013
    • Pareto 26.10
      Not reported
    Runs and sources
    Gemini 3.7 Flash
    • high-0.02295% CI -0.031 to -0.013 · 6,212,677 observations
    Pareto 26.10

    Not reported

  • ARC-AGI-2

    Best published score · Higher is better

    • Gemini 3.7 Flash
      84.6%
      #14 of 85
    • Pareto 26.10
      Not reported
    Runs and sources
    Gemini 3.7 Flash
    • low52.9%
    • medium63.8%
    • high84.6%
    Pareto 26.10

    Not reported

    Source:External evaluation via Epoch AIOriginal-source terms apply
  • FrontierMath-Tier-4-v2-Private

    Best published score · Higher is better

    • Gemini 3.7 Flash
      36.6%
      #29 of 72
    • Pareto 26.10
      Not reported
    Runs and sources
    Gemini 3.7 Flash
    • high36.6%
    Pareto 26.10

    Not reported

  • FrontierMath-Tiers-1-3-v2-Private

    Best published score · Higher is better

    • Gemini 3.7 Flash
      71.6%
      #27 of 87
    • Pareto 26.10
      Not reported
    Runs and sources
    Gemini 3.7 Flash
    • high71.6%
    Pareto 26.10

    Not reported

  • GPQA diamond

    Best published score · Higher is better

    • Gemini 3.7 Flash
      94.8%
      #7 of 161
    • Pareto 26.10
      Not reported
    Runs and sources
    Gemini 3.7 Flash
    • high94.8%
    Pareto 26.10

    Not reported

  • OTIS Mock AIME 2024-2025

    Best published score · Higher is better

    • Gemini 3.7 Flash
      97.2%
      #32 of 158
    • Pareto 26.10
      Not reported
    Runs and sources
    Gemini 3.7 Flash
    • high97.2%
    Pareto 26.10

    Not reported

  • SimpleQA Verified

    Best published score · Higher is better

    • Gemini 3.7 Flash
      69.2%
      #12 of 87
    • Pareto 26.10
      Not reported
    Runs and sources
    Gemini 3.7 Flash
    • high69.2%
    Pareto 26.10

    Not reported

Each model's best published result is shown; "Not reported" means no matched evaluation, not a score of zero. Arena and DeepSWE ranks are the leaderboards' own; other ranks are among catalogue models with a score. Results from different harnesses or settings are not directly comparable.

Original-source terms apply to evaluations credited to their original publishers.

DeepSWE 1.1 results: official leaderboard, data generated 2026-09-22. Only exact model versions in the official dataset are matched.

Benchmark compilation: Epoch AI, Capabilities & benchmarking (CC BY attribution). Scores are converted to percentages and model names matched to the Vertical Tabs catalog. Individual evaluations are credited to their original sources. External results may carry separate licences and evaluation configurations; do not interpret scores from different harnesses as directly comparable.

Arena ratings: Arena (lmarena-ai/leaderboard-dataset), licensed CC BY 4.0. Ratings come from pairwise human votes and are only comparable within one leaderboard; the interval is Arena's 95% confidence interval. Model names are matched to the Vertical Tabs catalog.

Model specifications

Release date
August 13, 2026
October 15, 2026
Context window
1M
1M
Native context
—
—
Max output tokens
65,536
131,072
Knowledge cutoff
2026-03
—
Open weights
Closed
Unknown
Parameter count
—
—

API pricing · USD per 1M tokens

Input
$0.75
$0.80
Output
$3.75
$3.20
Cached input
$0.075
$0.03
Cache write
$0.0417
—

Capabilities and modalities

Input modalities
text, image, video, file, audio
text, image
Output modalities
text
text
Tool calling
Supported
Supported
Reasoning option
Supported
—
Supported options
include_reasoning, max_tokens, reasoning, reasoning_effort, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_p
max_tokens, temperature, tool_choice, tools, top_p
Capabilities
—
—

Architecture and availability

Architecture
—
—
Model families
—
—
Tokenizer
Gemini
Other
Instruction format
—
—
License
—
—
Providers
2
1
Provider endpoints
14
1
Ollama variants
0
0
Metadata source
models.dev
ai-research

A dash means the field is not reported. Provider-specific performance and pricing may differ.

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