Models / Google/ Gemini 3.5 Flash

Gemini 3.5 Flash

Google · released May 19, 2026

Input: text, images, audio, video and documents. Output: text.InputOutput
Type
Closed
Input
$1.50
Output
$9.00
Cached
None held

List price · per 1M tokens · Google AI at 1M context · machine-readable source ↗

Our take

Written Sep 2, 2026

Gemini 3.5 Flash handles up to one million tokens in a single request and accepts text, images, files, audio and video. It is a strong pick for mathematics and coding workloads, though its agentic and data-analysis scores lag well behind its headline numbers.

Who should pick it

Choose this for long-document analysis at one million tokens, or for mathematics and coding where its benchmark scores are high. Use it for multimodal pipelines needing several input types in one endpoint, and seek out the lower-priced tiers for budget-conscious deployment. Skip it if you need autonomous agent behaviour, reliable data analysis, or guaranteed fast throughput at the cheapest rate.

The case for it

  • LiveBench Mathematics score of 88.24% on the refreshed 2026 benchmark.
  • Strong coding scores: 78.18% on LiveBench and 1507.74 on Arena Coding.
  • One-million-token request limit, rare among workhorse models.
  • Broad modality support: text, images, files, audio and video input in a single endpoint.

The case against it

  • Agentic coding falls 29 percentage points below standard coding, at 48.99%.
  • Data analysis is the weakest LiveBench sub-score, at 64.86%.
  • All Arena Agent dimensions score below zero, including recovery and steerability.
00

How good is it?

A general text model for everyday questions, drafting and coding, though it can struggle to get back on track after a failed step.

Good at
  • answering everyday questionsArena Text (overall) · 19th of 168
  • drafting and editing textArena Creative Writing · 13th of 168
  • writing and completing codeArena Coding · 42nd of 168
Less good at
  • getting back on track after a failed stepArena Agent · Recovery · 43rd of 55

EverydayGeneral questions and everyday reasoning

4 of 5

Arena Text (overall)19th of 168 · 1477

Arena Hard Prompts 29th of 168Arena Maths 14th of 163LiveBench Mathematics 36th of 58LiveBench Reasoning 38th of 58LiveBench Data Analysis 52nd of 58

Also on this board: 1474 (Sep 25, 2026). Read the pair, not the higher one.

CodingWriting and fixing code on its own

4 of 5

Arena Coding42nd of 168 · 1507

Arena Code (WebDev) 41st of 95LiveBench Coding 28th of 58

Also on this board: 1506 (Sep 25, 2026). Read the pair, not the higher one.

AgenticPlanning, calling tools, staying on task

2 of 5

Arena Agent38th of 55 · −0.035

LiveBench Agentic Coding 39th of 58

Also on this board: −0.047 (Sep 5, 2026). Read the pair, not the higher one.

WritingDrafting and rewriting prose

4 of 5

Arena Creative Writing13th of 168 · 1466

LiveBench Language 13th of 58

Also on this board: 1463 (Sep 25, 2026). Read the pair, not the higher one.

How it behaves in an agent loop
Tool usereaches for the right one, and does not invent one33rd of 55
Steerabilitydoes what it was asked, and changes course when told35th of 55
Recoverygets back on track after a command fails43rd of 55
Task outcomefinishes what the session set out to do29th of 55

Placings on Arena's agent boards, from live sessions people ran themselves. A model can lead on one of these and sit mid-field on the others.

Other boards it appears on
Arena Instruction Following 28th of 168LiveBench Instruction Following 6th of 58LiveBench 32nd of 58Arena Agent · Task outcome 29th of 55Arena Agent · Tool use 33rd of 55Arena Agent · Steerability 35th of 55Arena Agent · Recovery 43rd of 55

Boards this model appears on that none of the ratings above are built on.

Every published score for this model20 scoresEvery figure we hold, from 20 boards, with who ran it and a link to the source — including the boards no rating above is built on.
LiveBenchreasoning
74.64source ↗
48.99source ↗
78.18source ↗
64.86source ↗
75.6source ↗
84.58source ↗
88.24source ↗
82source ↗
−0.035source ↗
−0.062source ↗
−0.034source ↗
−0.016source ↗
0.002source ↗
1507source ↗
1466source ↗
1495source ↗
1465source ↗
1496source ↗
1477source ↗
1499source ↗
01

Where to rent it

Prices checked between 59 min and 1 hour ago — each listing carries its own date.

Cheapest published offer

Google AI, direct

The lab is the cheapest at this context. The strip above and this offer are the same one, compared at 1M of context. 2 cheaper rows below are outside that comparison: a non-standard pricing tier.

per 1M tokens
$1.50 in / $9.00 out
Context served
1M
Throughput
Not measured
Current provider offers with price, context and prompt-privacy answers
ProviderIn / out per 1M tokensContextThroughputTrains on promptsLogs promptsZero retention
Google AI Studioflex tierThrough OpenRouter$0.75 / $4.50checked 1 hour ago1M66K max reply108 tok/sNoYes55 daysUnknown
Google Vertex AIflex tierglobalThrough OpenRouter$0.75 / $4.50checked 1 hour ago1M66K max reply3 tok/sNoNoConfirmed
Google AIDirect$1.50 / $9.00checked 59 min ago1M66K max replynot measuredUnknownUnknownUnknown
Google AI StudioThrough OpenRouter$1.50 / $9.00checked 1 hour ago1M66K max reply103 tok/sNoYes55 daysUnknown
Google Vertex AIglobalThrough OpenRouter$1.50 / $9.00checked 1 hour ago1M66K max reply74 tok/sNoNoConfirmed
OpenRouterOpenRouter's own listing$1.50 / $9.00checked 1 hour ago1Mnot measuredUnknownUnknownUnknown
DeepInfraDirect$1.50 / $9.00checked 1 hour ago1Mnot measuredUnknownUnknownUnknown
Google Vertex AIusThrough OpenRouter$1.65 / $9.90checked 1 hour ago1M66K max reply8 tok/sNoNoConfirmed
Google Vertex AIpriority tierglobalThrough OpenRouter$2.70 / $16.20checked 1 hour ago1M66K max reply144 tok/sNoNoConfirmed
Google AI Studiopriority tierThrough OpenRouter$2.70 / $16.20checked 1 hour ago1M66K max reply59 tok/sNoYes55 daysUnknown

Across the 10 listings we hold: 7 say they do not train on prompts, 0 say they do and 3 do not say. 4 appear in the zero-retention registry we check; the rest are unknown to us.

What each host's API supports

From the parameter list each endpoint publishes. Streaming is omitted: nothing we hold reports it, for any model.

API features per host
ProviderTool callingJSON outputStrict schema
Google AI StudioflexThrough OpenRouter✓✓✓
Google Vertex AIflex · globalThrough OpenRouter✓✓✓
Google AIDirect
Google AI StudioThrough OpenRouter✓✓✓
Google Vertex AIglobalThrough OpenRouter✓✓✓
OpenRouterOpenRouter's own listing✓✓✓
DeepInfraDirect
Google Vertex AIusThrough OpenRouter✓✓✓
Google Vertex AIpriority · globalThrough OpenRouter✓✓✓
Google AI StudiopriorityThrough OpenRouter✓✓✓

Tool calling: 8 of 10 listings say yes, 2 publish no parameter list. JSON output: 8 of 10 listings say yes, 2 publish no parameter list. Strict schema: 8 of 10 listings say yes, 2 publish no parameter list.

02

Models people weigh against Gemini 3.5 Flash

03

When we formed this view

Recent changes

Sep 25, 2026BenchmarkScored 1507 via High on Arena Coding
What movedleaderboard
Sep 25, 2026BenchmarkScored 1466 via Medium on Arena Creative Writing
What movedleaderboard
Sep 25, 2026BenchmarkScored 1495 via High on Arena Hard Prompts
What movedleaderboard
Sep 25, 2026BenchmarkScored 1465 via High on Arena Instruction Following
What movedleaderboard
Sep 25, 2026BenchmarkScored 1496 via High on Arena Maths
What movedleaderboard
Sep 25, 2026BenchmarkScored 1477 via High on Arena Text (overall)
What movedleaderboard
Sep 25, 2026BenchmarkScored 1499 via High on Arena Code (WebDev)
What movedleaderboard
Sep 5, 2026BenchmarkScored −0.035 via High on Arena Agent
What movedleaderboard
Sep 5, 2026BenchmarkScored −0.062 via Medium on Arena Agent · Recovery
What movedleaderboard
Sep 5, 2026BenchmarkScored −0.034 via Medium on Arena Agent · Steerability
What movedleaderboard

Each date is the day we first saw the change, or the day the maker announced it.

What we do not know about this model yet

  • 2 of 10 listings publish no parameter list, so what their API accepts is unknown to us.
  • Nothing we hold says whether an endpoint streams, so we do not show it either way.
  • 3 of 10 listings do not say whether they train on prompts.
  • We hold no batch or off-peak rate for any of its listings.
04

Licence and identifiers

What the licence allowsWe hold no licence record for this model. Inside are the identifiers you need to pull it — its Hugging Face repo where we have one, our slug and a machine-readable card.

Licence

We hold no licence record for this model, and no record of published weights either — so we can neither summarise its terms nor point you at the weights.

Identifiers

Takes in, gives back
Text, images, audio, video and documents in, text out
Catalogue slug
google-gemini-3-5-flash

Machine-readable model card (omc.json) →

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