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Gemini 3.5 Flash Lite vs Step 3.5 Flash

Updated October 21, 2026. 32 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Gemini 3.5 Flash LiteGoogle
Coding
49.0
Overall
22.2
Output $/M
$2.50
31
Step 3.5 FlashStepFun
Coding
No data
Overall
17.0
Output $/M
$0.30
1
vs boards won of 32 shared

Decision reading

Only Gemini 3.5 Flash Lite has a coding score, 49.0 on the Vibe Coding Index; Step 3.5 Flash has none, so the two cannot be ranked on coding.

Step 3.5 Flash has the edge where output tokens cost 8.3x less, and where the benchmark that matters is Humanity's Last Exam (Artificial Analysis run), where it leads.

Shared results
32
Gemini 3.5 Flash Lite only
51
Step 3.5 Flash only
3
Like-for-like categories
6 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Gemini 3.5 Flash Lite 49.0 from 3 benchmarks, Step 3.5 Flash not benchmarked.
Widest category
General, 7.5 points apart on average over 18 shared benchmarks.
Widest single gap
Long context reasoning (AA-LCR): Gemini 3.5 Flash Lite 76.0% against Step 3.5 Flash 63.0%, 13.0 points apart on a 0 to 100 scale.
Output price
Gemini 3.5 Flash Lite $2.50 against Step 3.5 Flash $0.30 per million output tokens, 8.3x apart.
Context window
Gemini 3.5 Flash Lite takes 1.05M tokens, Step 3.5 Flash 262K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryGemini 3.5 Flash LiteBarsStep 3.5 FlashTies
Coding20
Intelligence10
Reasoning41
Math20
Knowledge40
General180
All shared boards311
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for Gemini 3.5 Flash Lite and Step 3.5 Flash
BenchmarkGemini 3.5 Flash LiteStep 3.5 FlashLeader
LMArena WebDev1435Not measuredOnly Gemini 3.5 Flash Lite measured
AA Coding Index49.3Not measuredOnly Gemini 3.5 Flash Lite measured
LiveCodeBench (Vals AI)79.0%Not measuredOnly Gemini 3.5 Flash Lite measured
SWE-bench Verified (Vals AI)75.0%Not measuredOnly Gemini 3.5 Flash Lite measured
Vibe Code Bench (Vals AI)37.2%Not measuredOnly Gemini 3.5 Flash Lite measured
Code migration (Vals AI)6.2%Not measuredOnly Gemini 3.5 Flash Lite measured
ProgramBench (Vals AI)0.0%Not measuredOnly Gemini 3.5 Flash Lite measured
Terminal-Bench 2.1 (Vals AI)50.2%Not measuredOnly Gemini 3.5 Flash Lite measured
CyberBench (Vals AI)59.1%Not measuredOnly Gemini 3.5 Flash Lite measured
SciCode41.3%Not measuredOnly Gemini 3.5 Flash Lite measured
Terminal-Bench Hard (Artificial Analysis run)Not measured32.6%Only Step 3.5 Flash measured
WeirdML39.0%Not measuredOnly Gemini 3.5 Flash Lite measured
ALE-Bench765.3Not measuredOnly Gemini 3.5 Flash Lite measured
LMArena Text: coding14531436Gemini 3.5 Flash Lite
LMArena Text: software and IT14511434Gemini 3.5 Flash Lite
LMArena WebDev: React1408Not measuredOnly Gemini 3.5 Flash Lite measured
LMArena WebDev: from an image1448Not measuredOnly Gemini 3.5 Flash Lite measured
Neither model has a result on the other 21 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Gemini 3.5 Flash Lite and Step 3.5 Flash
BenchmarkGemini 3.5 Flash LiteStep 3.5 FlashLeader
AA Intelligence Index22.217.0Gemini 3.5 Flash Lite
Epoch Capabilities Index144.9Not measuredOnly Gemini 3.5 Flash Lite measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Agentic work benchmarks for Gemini 3.5 Flash Lite and Step 3.5 Flash
BenchmarkGemini 3.5 Flash LiteStep 3.5 FlashLeader
AA Agentic Index14.3Not measuredOnly Gemini 3.5 Flash Lite measured
Finance Agent (Vals AI)47.4%Not measuredOnly Gemini 3.5 Flash Lite measured
Tax Agent Bench (Vals AI)7.2%Not measuredOnly Gemini 3.5 Flash Lite measured
Legal Research Bench (Vals AI)13.9%Not measuredOnly Gemini 3.5 Flash Lite measured
Excel Modeling Benchmark (Vals AI)43.2%Not measuredOnly Gemini 3.5 Flash Lite measured
τ²-Bench TelecomNot measured94.4%Only Step 3.5 Flash measured
APEX-Agents29.3%Not measuredOnly Gemini 3.5 Flash Lite measured
Neither model has a result on the other 32 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index41
Reasoning benchmarks for Gemini 3.5 Flash Lite and Step 3.5 Flash
BenchmarkGemini 3.5 Flash LiteStep 3.5 FlashLeader
GPQA Diamond83.8%Not measuredOnly Gemini 3.5 Flash Lite measured
MMMU Pro (Vals AI)83.6%Not measuredOnly Gemini 3.5 Flash Lite measured
GPQA Diamond (Artificial Analysis run)83.8%83.1%Gemini 3.5 Flash Lite
Humanity's Last Exam (Artificial Analysis run)18.8%24.5%Step 3.5 Flash
GPQA Diamond (Epoch AI run)83.3%Not measuredOnly Gemini 3.5 Flash Lite measured
ARC-AGI53.5%Not measuredOnly Gemini 3.5 Flash Lite measured
ARC-AGI-210.3%Not measuredOnly Gemini 3.5 Flash Lite measured
Chess puzzles21.0%Not measuredOnly Gemini 3.5 Flash Lite measured
Mystery game puzzles19.0%Not measuredOnly Gemini 3.5 Flash Lite measured
LMArena Text: hard prompts14411411Gemini 3.5 Flash Lite
LMArena Text: expert14341421Gemini 3.5 Flash Lite
LMArena Text: hard prompts in English14401421Gemini 3.5 Flash Lite
LMArena Vision: diagrams1284Not measuredOnly Gemini 3.5 Flash Lite measured
LMArena Vision: homework1291Not measuredOnly Gemini 3.5 Flash Lite measured
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Gemini 3.5 Flash Lite and Step 3.5 Flash
BenchmarkGemini 3.5 Flash LiteStep 3.5 FlashLeader
OTIS Mock AIME71.1%Not measuredOnly Gemini 3.5 Flash Lite measured
FrontierMath, tiers 1 to 326.0%Not measuredOnly Gemini 3.5 Flash Lite measured
FrontierMath, tier 40.0%Not measuredOnly Gemini 3.5 Flash Lite measured
ProofBench13.0%Not measuredOnly Gemini 3.5 Flash Lite measured
LMArena Text: math14341408Gemini 3.5 Flash Lite
LMArena Text: mathematical work14331421Gemini 3.5 Flash Lite
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Gemini 3.5 Flash Lite and Step 3.5 Flash
BenchmarkGemini 3.5 Flash LiteStep 3.5 FlashLeader
MMLU Pro85.8%Not measuredOnly Gemini 3.5 Flash Lite measured
LegalBench (Vals AI)84.1%Not measuredOnly Gemini 3.5 Flash Lite measured
CorpFin (Vals AI)60.7%Not measuredOnly Gemini 3.5 Flash Lite measured
TaxEval (Vals AI)72.6%Not measuredOnly Gemini 3.5 Flash Lite measured
MortgageTax (Vals AI)68.7%Not measuredOnly Gemini 3.5 Flash Lite measured
MedCode (Vals AI)43.5%Not measuredOnly Gemini 3.5 Flash Lite measured
LMArena Text: science14511415Gemini 3.5 Flash Lite
LMArena Text: medicine and healthcare14381408Gemini 3.5 Flash Lite
LMArena Text: legal and government14311408Gemini 3.5 Flash Lite
LMArena Text: business and finance14231394Gemini 3.5 Flash Lite
Neither model has a result on the other 7 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Gemini 3.5 Flash Lite and Step 3.5 Flash
BenchmarkGemini 3.5 Flash LiteStep 3.5 FlashLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
General benchmarks for Gemini 3.5 Flash Lite and Step 3.5 Flash
BenchmarkGemini 3.5 Flash LiteStep 3.5 FlashLeader
Public Benefits Bench (Vals AI)51.8%Not measuredOnly Gemini 3.5 Flash Lite measured
SAGE (Vals AI)47.3%Not measuredOnly Gemini 3.5 Flash Lite measured
MedScribe (Vals AI)70.9%Not measuredOnly Gemini 3.5 Flash Lite measured
IFBenchNot measured66.5%Only Step 3.5 Flash measured
Long context reasoning (AA-LCR)76.0%63.0%Gemini 3.5 Flash Lite
DTBench83.5%Not measuredOnly Gemini 3.5 Flash Lite measured
LMCA37.6%Not measuredOnly Gemini 3.5 Flash Lite measured
LMArena Text14351403Gemini 3.5 Flash Lite
LMArena Text: instruction following14191385Gemini 3.5 Flash Lite
LMArena Text: creative writing14211357Gemini 3.5 Flash Lite
LMArena Vision1269Not measuredOnly Gemini 3.5 Flash Lite measured
LMArena Text: English14381417Gemini 3.5 Flash Lite
LMArena Text: non-English14271385Gemini 3.5 Flash Lite
LMArena Text: Chinese14681446Gemini 3.5 Flash Lite
LMArena Text: German14541405Gemini 3.5 Flash Lite
LMArena Text: Japanese14261353Gemini 3.5 Flash Lite
LMArena Text: Korean14071351Gemini 3.5 Flash Lite
LMArena Text: French14511421Gemini 3.5 Flash Lite
LMArena Text: Spanish14411419Gemini 3.5 Flash Lite
LMArena Text: Russian14431385Gemini 3.5 Flash Lite
LMArena Text: Polish14371389Gemini 3.5 Flash Lite
LMArena Text: multi-turn14451404Gemini 3.5 Flash Lite
LMArena Text: longer queries14351402Gemini 3.5 Flash Lite
LMArena Text: writing and language14281372Gemini 3.5 Flash Lite
LMArena Text: entertainment and media14141360Gemini 3.5 Flash Lite
LMArena Vision: English1269Not measuredOnly Gemini 3.5 Flash Lite measured
LMArena Vision: Chinese1311Not measuredOnly Gemini 3.5 Flash Lite measured
LMArena Vision: reading text1280Not measuredOnly Gemini 3.5 Flash Lite measured
LMArena Vision: humor1287Not measuredOnly Gemini 3.5 Flash Lite measured
LMArena Vision: creative writing1260Not measuredOnly Gemini 3.5 Flash Lite measured
Neither model has a result on the other 16 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 3.5 Flash Lite and Step 3.5 Flash
BenchmarkGemini 3.5 Flash LiteStep 3.5 FlashLeader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Gemini 3.5 Flash Lite$0.0015Fits in one request
Step 3.5 Flash$0.0003Fits in one request

Step 3.5 Flash costs less

Repository review

50K input + 3K output tokens

Gemini 3.5 Flash Lite$0.022Fits in one request
Step 3.5 Flash$0.0059Fits in one request

Step 3.5 Flash costs less

Agent loop

200K input + 10K output tokens

Gemini 3.5 Flash Lite$0.085Fits in one request
Step 3.5 Flash$0.023Fits in one request

Step 3.5 Flash costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Gemini 3.5 Flash Lite and Step 3.5 Flash
SpecificationGoogle Gemini 3.5 Flash LiteStepFun Step 3.5 Flash
MakerGoogleStepFun
WeightsNo public weights listedOpen weights
ReleasedJuly 21, 2026January 29, 2026
Context window1.05M262K
Input $/Mtok$0.30$0.10
Output $/Mtok$2.50$0.30
Coding index49.0Not benchmarked
Independent measurements behind it30
Cost per solved task$0.41Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.5 Flash Lite better than Step 3.5 Flash for coding?

Only Gemini 3.5 Flash Lite has a coding score, 49.0 on the Vibe Coding Index; Step 3.5 Flash has none, so the two cannot be ranked on coding. Step 3.5 Flash has the edge where output tokens cost 8.3x less, and where the benchmark that matters is Humanity's Last Exam (Artificial Analysis run), where it leads.

Which is cheaper, Gemini 3.5 Flash Lite or Step 3.5 Flash?

Gemini 3.5 Flash Lite costs $0.30 per million input tokens and $2.50 per million output tokens; Step 3.5 Flash costs $0.10 and $0.30. Cost per solved task is known for Gemini 3.5 Flash Lite only.

Which has the bigger context window, Gemini 3.5 Flash Lite or Step 3.5 Flash?

Gemini 3.5 Flash Lite, with 1.05M tokens against 262K.

How many benchmarks is the Gemini 3.5 Flash Lite vs Step 3.5 Flash comparison based on?

32 benchmarks have a result for both models as of October 21, 2026. Gemini 3.5 Flash Lite's coding index rests on 3 independent benchmarks and Step 3.5 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.

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