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ModelActiveClosed / proprietary

Gemini 3.5 Flash

Googlefamily · Gemini 3.5ai.google.dev/gemini-api/docs/models/gemini-3.5-

Our legacy Flash model, providing baseline speed and foundational performance for routine, high-throughput workloads.

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data quality74

Updated 4 h ago · first seen 11 Sept 2026

model_01M293V7SSHKYPK7DZ0A8A1T9H

Overview

Identity

Canonical model
Yesidentity confidence: highOne row per real model release. Artifacts (checkpoints, quantisations, conversions) and folded evaluation variants point here.
Official checkpoints
None recorded — closed weightsofficial_checkpoints = hf_repo identifiers carried by the model itself; artifacts are separate entities pointing here through canonical_id.
Artifacts
None recordedSeparate entities (checkpoint · quantization · conversion · packaging) pointing to this model through canonical_id.
Provider deployments
2
API aliases
gemini-3-5-flashgemini-3-5-flash-mediumgemini-3-5-flash-minimalgemini-3.5-flashgoogle/gemini-3.5-flashIdentifiers under which providers and evaluators refer to this model.
Folded evaluation variants
3Effort / thinking variants (…-high, …-non-reasoning) are result configurations of this model, not separate models. Their old URLs redirect here.

Openness

Closed / proprietary— weights not available; 7 dimensions unknown.

Weights are not available; the model is reachable only through an API or a product.

  • Weights

    No

  • Inference code

    —

  • Training code

    —

  • Training data

    —

  • Dataset

    —

  • Commercial use

    —

  • Redistribution

    —

  • Derivatives

    —

dimensions marked null are unknown, not false

Key facts

Release date

Source:OpenRouter public model & pricing listingT2observed 14 h agomedium

Status

Source:Google AI for Developers (Gemini API docs)T1observed 14 h agohigh

Knowledge cutoff

Source:OpenRouter public model & pricing listingT2observed 14 h agomedium

API model id

Source:Google AI for Developers (Gemini API docs)T1observed 14 h agohigh

Openrouter id

Source:OpenRouter public model & pricing listingT2observed 14 h agomedium

Architecture

Tokenizer

Source:OpenRouter public model & pricing listingT2observed 14 h agomedium

Capabilities

Modalities

Modalities
audiodocumentimagetextvideo
Input
audiodocumentimagetextvideo
Output
text

Capabilities

  • Tool calling

    Yes

    Google AI for Developers (Gemini API docs) · T1

  • Structured output

    Yes

    Google AI for Developers (Gemini API docs) · T1

  • Reasoning

    Yes

    Google AI for Developers (Gemini API docs) · T1

  • Vision

    Yes

    Google AI for Developers (Gemini API docs) · T1

  • Audio

    Yes

    Google AI for Developers (Gemini API docs) · T1

  • Fine-tuning available

    Unavailable

Context window

Source:Google AI for Developers (Gemini API docs)T1observed 4 h agohigh

Max output

Source:Google AI for Developers (Gemini API docs)T1observed 14 h agohigh

Knowledge cutoff

Source:OpenRouter public model & pricing listingT2observed 14 h agomedium

Tokenizer

Source:OpenRouter public model & pricing listingT2observed 14 h agomedium

Benchmarks56

Compare with another model →

Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric

Benchmark results grouped by comparability group
Benchmark · groupBest scoreTrustConfigurationResultsvs leaderEvaluatedSource
Terminal-Benchagentic · accuracy · variant=v4.0 · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisvariantv4.0reasoningonconditions differ across rows → partially comparable2non-primary groupobs. 12 Sept 2026artificialanalysis.aiT2
Terminal-Benchagentic · accuracy · variant=hard · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisvarianthardreasoning_effortminimalconditions differ across rows → partially comparable6−19.7 ptvs gpt-5.6-solobs. 12 Sept 2026artificialanalysis.aiT2
Terminal-Benchagentic · accuracy · variant=v2.1 · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisvariantv2.1reasoningonconditions differ across rows → partially comparable2non-primary groupobs. 12 Sept 2026artificialanalysis.aiT2
τ²-benchagentic · pass^1 · variant=Telecom · evaluator=Artificial AnalysisIndependentevaluatorArtificial AnalysisvariantTelecomreasoning_effortmediumconditions differ across rows → partially comparable3non-primary groupobs. 12 Sept 2026artificialanalysis.aiT2
τ²-benchagentic · pass^1 · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoning_effortmediumconditions differ across rows → partially comparable3−3.51 ptvs Z.ai GLM 5.2obs. 11 Sept 2026artificialanalysis.aiT2
LiveBench Agentic Codingcoding · average score · variant=Agentic CodingOfficial boardvariantAgentic Codingreasoning_efforthighrelease2026-06-25conditions differ across rows → partially comparable1−28.3 ptvs DeepSeek-V4.1-Flash25 Jun 2026livebench.aiT2
LiveBench Codingcoding · average score · variant=CodingOfficial boardvariantCodingreasoning_efforthighrelease2026-06-25conditions differ across rows → partially comparable1−8.19 ptvs Claude Fable 5.125 Jun 2026livebench.aiT2
SciCodecoding · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoningonconditions differ across rows → partially comparable2−9.14 ptvs Claude Fable 5.1obs. 12 Sept 2026artificialanalysis.aiT2
Artificial Analysis Intelligence Indexcomposite · indexIndependentreasoning_effortmediumversion4.3conditions differ across rows → partially comparable6−19.7vs Claude Fable 5.1obs. 12 Sept 2026artificialanalysis.aiT2
LiveBenchgeneral · global_averageOfficial boardreasoning_efforthighrelease2026-06-25conditions differ across rows → partially comparable1−8.78 ptvs Claude Fable 5.125 Jun 2026livebench.aiT2
LiveBench Data Analysisgeneral · average score · variant=Data AnalysisOfficial boardvariantData Analysisreasoning_efforthighrelease2026-06-25conditions differ across rows → partially comparable1−18.1 ptvs gpt-6-astra25 Jun 2026livebench.aiT2
LiveBench Languagegeneral · average score · variant=LanguageOfficial boardvariantLanguagereasoning_efforthighrelease2026-06-25conditions differ across rows → partially comparable1−6.10 ptvs Claude Fable 525 Jun 2026livebench.aiT2
IFBenchinstruction-following · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoningonconditions differ across rows → partially comparable6−7.00 ptvs Grok 4.3obs. 12 Sept 2026artificialanalysis.aiT2
LiveBench Instruction Followinginstruction-following · average score · variant=IFOfficial boardvariantIFreasoning_efforthighrelease2026-06-25conditions differ across rows → partially comparable1−5.81 ptvs Gemini 3.8 Flash25 Jun 2026livebench.aiT2
Humanity's Last Examknowledge · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoningonconditions differ across rows → partially comparable6−16.5 ptvs Claude Fable 5.1obs. 12 Sept 2026artificialanalysis.aiT2
LiveBench Mathematicsmath · average score · variant=MathematicsOfficial boardvariantMathematicsreasoning_efforthighrelease2026-06-25conditions differ across rows → partially comparable1−8.76 ptvs Claude Fable 5.125 Jun 2026livebench.aiT2
MMMU-Promultimodal · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoningonconditions differ across rows → partially comparable6−2.60 ptvs gpt-6-astraobs. 12 Sept 2026artificialanalysis.aiT2
GPQA Diamondreasoning · accuracy · variant=Diamond · evaluator=Artificial AnalysisIndependentevaluatorArtificial AnalysisvariantDiamondreasoningonconditions differ across rows → partially comparable3non-primary groupobs. 12 Sept 2026artificialanalysis.aiT2
GPQA Diamondreasoning · accuracy · variant=GPQA Diamond · evaluator=Artificial AnalysisIndependentevaluatorArtificial AnalysisvariantGPQA Diamond3−4.04 ptvs gpt-6-astraobs. 11 Sept 2026artificialanalysis.aiT2
LiveBench Reasoningreasoning · average score · variant=ReasoningOfficial boardvariantReasoningreasoning_efforthighrelease2026-06-25conditions differ across rows → partially comparable1−10.6 ptvs gpt-6-astra25 Jun 2026livebench.aiT2

Current rows only, grouped by benchmark → canonical metric → comparability group (task configuration). Effort variants folded into this model appear as rows of the same group. 56 current rows in total. “vs leader” compares with the current leader of the benchmark's primary group only; other groups are not directly comparable. Comparability rules →

Providers & Pricing5

All offers in the price terminal →
Provider deployments, cheapest output first
ProviderContextInput / 1MCached inCache writeOutput / 1MBatch in / outPer image / requestNative unitsStatusObservedSource
Google Gemini APIcheapest outputgoogle/gemini-3.5-flash:batch1.05Mout 65.5K$0.075——$0 / ——active5 h agosince 11 Sept 2026openrouter.aiT2
OpenRoutergoogle/gemini-3.5-flash:batch1.05Mout 65.5K$0.075——$0 / ——active45 min agosince 12 Sept 2026openrouter.aiT2
Google Gemini APIgemini-3.5-flash—$0.15—$0.75 / $4.5—flex_input_per_mtok=0.75flex_output_per_mtok=4.5priority_input_per_mtok=2.7+3active23 min agosince 11 Sept 2026ai.google.devT1
Google Gemini APIgoogle/gemini-3.5-flash1.05Mout 65.5K$0.15$0.083—$0 / ——active5 h agosince 11 Sept 2026openrouter.aiT2
OpenRoutergoogle/gemini-3.5-flash1.05Mout 65.5K$0.15$0.083—$0 / ——active45 min agosince 12 Sept 2026openrouter.aiT2

USD per 1M tokens as published by each provider; native units (per-request fees, flex/priority tiers) are kept verbatim. Rows are append-only — every price change is kept in the history below. Cost of a workload →

Price history

Step lines per provider; amber markers are recorded changes. Click a marker or a row for the evidence behind that price.

Output price · USD / 1M tokens 2 providers

Output price history of Gemini 3.5 Flash$0$2$4$6$8$10$12Sept 26Sept 26Sept 26Sept 26Sept 26Google Gemini API: first observed → $9 · 11 Sept 2026Google Gemini API: $9 → $4.5 · 11 Sept 2026OpenRouter: first observed → $9 · 12 Sept 2026OpenRouter: $9 → $4.5 · 12 Sept 2026
  • Google Gemini API
  • OpenRouter
  • OpenRouter$9 → $4.512 Sept 2026
  • OpenRouterfirst observed $912 Sept 2026
  • Google Gemini API$9 → $4.511 Sept 2026
  • Google Gemini APIfirst observed $911 Sept 2026

Input price · USD / 1M tokens 2 providers

Input price history of Gemini 3.5 Flash$0$0.50$1$1.5$2Sept 26Sept 26Sept 26Sept 26Sept 26Google Gemini API: first observed → $1.5 · 11 Sept 2026Google Gemini API: $1.5 → $0.75 · 11 Sept 2026OpenRouter: first observed → $1.5 · 12 Sept 2026OpenRouter: $1.5 → $0.75 · 12 Sept 2026
  • Google Gemini API
  • OpenRouter
  • OpenRouter$1.5 → $0.7512 Sept 2026
  • OpenRouterfirst observed $1.512 Sept 2026
  • Google Gemini API$1.5 → $0.7511 Sept 2026
  • Google Gemini APIfirst observed $1.511 Sept 2026

Versions & Artifacts0

Version history

Context window2 changes

11 Sept 2026→11 Sept 2026→12 Sept 2026current

Knowledge cutofffirst observation only

11 Sept 2026current

Max outputfirst observation only

11 Sept 2026current

Opennessfirst observation only

11 Sept 2026current

Statusfirst observation only

11 Sept 2026current

Each hop is a claim: click a value for its source, tier and observation time. Nothing is overwritten — a new observation closes the previous claim.

Artifacts 0

No artifact (checkpoint, quantisation, conversion or packaging) points to this model yet.

Timeline30

Full timeline →

Change history

Temporal, append-only claims: a new observation closes the previous claim instead of overwriting it. Rewind the record with the as-of picker.
1 claims · 1 propertiesShow all properties

Aa opennessaa_openness1

Claim history for Aa openness
ValueValid from → toStatusSourceConfidenceExtractor
proprietary → currentcurrentArtificial AnalysisT2mediumdeterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

Provenance

Attributed facts

32

Source tiers

T1T219 / 13

Freshest observation

4 h ago

Conflicts

16 flagged

Source documents 6

Source documents
SourceDocumentTypeTierLast observedSnapshots
Google AI for Developers (Gemini API docs)ai.google.dev/gemini-api/docs/models/gemini-3.5-flash model_pageT1· Official23 min ago25
Google AI for Developers (Gemini API docs)ai.google.dev/gemini-api/docs/pricing pricingT1· Official23 min ago25
Google AI for Developers (Gemini API docs)ai.google.dev/gemini-api/docs/models model_docsT1· Official23 min ago25
OpenRouter public model & pricing listingopenrouter.ai/api/v1/models catalogueT2· Quality secondary45 min ago11
Artificial Analysisartificialanalysis.ai/leaderboards/models leaderboardT2· Quality secondary4 h ago2
LiveBenchlivebench.ai/table_2026_06_25.csv leaderboardT2· Quality secondary12 h ago1

Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.

Data quality (74/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →