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Gemini 3.5 Flash-Lite

Google DeepMind · released Jul 21, 2026

Small & fastAPI only

Google's budget tier: a very fast, low-cost multimodal model for sub-agents, document processing and other high-throughput jobs. It is the fastest model tracked here by a wide margin.

Best for: Highest throughput · Document processing · Sub-agents

Announcement
Intelligence Index
22.2
#32 of 38
Price per 1M tokens
$0.30 in $2.5 out
Blended $0.85 at 3:1
Context window
1M
Up to 66K output
Output speed
346 tokens/s
$0.19 measured cost per task

Capability profile

One 0–100 score per area, placing this model between the weakest and strongest tracked model across that area's benchmarks.

  • Overall37 · #28 of 38

    Based on 2 of 3 benchmarks

  • Coding14 · #30 of 39

    Based on 3 of 5 benchmarks

  • Agents & knowledge work36 · #30 of 40

    Based on 1 of 6 benchmarks

  • Reasoning & science9 · #35 of 39

    Based on 2 of 2 benchmarks

  • Knowledge & reliability62 · #23 of 39

    Based on 2 of 2 benchmarks

  • Vision69 · #15 of 31

    Based on 2 of 2 benchmarks

Benchmark results

All third-party results on record. Rank is among the tracked models that have been tested on that benchmark.

Overall

  • Artificial Analysis Intelligence Index22.2

    #32 of 38· Artificial Analysis

  • Vals IndexNot tested
  • Arena · Text1455 ±4

    #19 of 33· 35,763 votes· Arena

Coding

  • Terminal-Bench 4.01.0%

    #27 of 38· Artificial Analysis

  • SciCode41.3%

    #33 of 38· Artificial Analysis

  • Arena · WebDev1440 ±41

    #29 of 34· 242 votes· Arena

  • Vibe Code BenchNot tested
  • Code MigrationNot tested

Agents & knowledge work

  • GDPval-AA24.3

    #31 of 39· Artificial Analysis

  • Arena · AgentNot tested
  • Finance Agent v2Not tested
  • Excel Modeling BenchmarkNot tested
  • Legal Research BenchNot tested
  • Tax Agent BenchNot tested

Reasoning & science

  • Humanity's Last Exam18.8%

    #35 of 39· Artificial Analysis

  • CritPt0.0%

    #38 of 39· Artificial Analysis

  • ARC-AGI-2saturatingNot tested
  • ARC-AGI-3Not tested
  • GPQA Diamondsaturating83.8%

    #21 of 27· Artificial Analysis

Knowledge & reliability

  • AA-Omniscience5

    #18 of 39· Artificial Analysis

  • AA-LCR76.0%

    #31 of 39· Artificial Analysis

Vision

  • MMMU-Pro79.0%

    #12 of 27· Artificial Analysis

  • Arena · Vision1264 ±8

    #11 of 19· 7,579 votes· Arena

Reported by Google DeepMind

Numbers the lab published at launch, run on its own harness and settings. Useful context, but not independently verified and never used in the rankings on this site.

  • SWE-bench Pro54.2%
  • OSWorld-Verified74%

Specifications

Lab
Google DeepMind
Released
Jul 21, 2026
Availability
Generally available
Context window
1,048,576 tokens
Max output
65,536 tokens
Accepts
Text, Images, Audio, Video, PDFs
Knowledge cutoff
Mar 2026
Weights
Closed
Reasoning control
Thinking level minimal to high
API model ID
gemini-3.5-flash-lite

Pricing

Input / 1M tokens
$0.30
Cached input / 1M
$0.03
Output / 1M tokens
$2.5
Blended (3:1)
$0.85
Measured cost / task
$0.19

One input rate covers text, image, video and audio. Batch is half price.

Official sources

  • Announcement
  • Documentation
  • Model card

Closest alternatives

The models nearest to this one on overall score.

  • MiniMax-M3
    Intelligence Index
    29.2
    Price / 1M
    $0.52
    Compare the two
  • Nemotron 3 Ultra
    Intelligence Index
    22.9
    Price / 1M
    $1.07
    Compare the two
  • Hy3
    Intelligence Index
    25.3
    Price / 1M
    $0.23
    Compare the two
  • Kimi K2.7 Code
    Intelligence Index
    25.8
    Price / 1M
    $1.71
    Compare the two

23 benchmarks tracked. See methodology and sources.

Model Index

An independent snapshot of frontier SI models and how they perform on third-party benchmarks.

Data as of Oct 8, 2026

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Sources

Benchmark results come from Artificial Analysis, Arena, Vals AI and ARC Prize. Specifications and prices come from each lab's own documentation.

Not affiliated with any lab or evaluator. Names and logos are trademarks of their respective owners and are used only to identify them. Scores change often — check the linked source before making a decision that depends on one.

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