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Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) vs GPT-3.5 Turbo Instruct

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) costs 1.3x less per output token than GPT-3.5 Turbo Instruct ($1.50 vs $2.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)Google
Coding
No data
Overall
No data
Output $/M
$1.50
GPT-3.5 Turbo InstructOpenAI
Coding
No data
Overall
No data
Output $/M
$2.00
vs $1.50 vs $2.00 per 1M output tokens. Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) is 1.3x cheaper.

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) or GPT-3.5 Turbo Instruct: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) for output tokens 1.3x cheaper ($1.50 vs $2.00 per million) and a larger context window (66K against 4K tokens).

No benchmark has tested both yet. Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) has results on Design Arena: images, Design Arena: graphic design and Design Arena: logos; GPT-3.5 Turbo Instruct on METR time horizons. Compare them on price and context instead.

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
Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) not benchmarked, GPT-3.5 Turbo Instruct not benchmarked.
Widest category
None yet: no category has been tested on both models.
Widest single gap
None yet: no benchmark has tested both models.
Output price
Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) $1.50 against GPT-3.5 Turbo Instruct $2.00 per million output tokens, 1.3x apart.
Context window
Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) takes 66K tokens, GPT-3.5 Turbo Instruct 4K.

Benchmark by benchmark

Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.

Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Agentic work benchmarks for Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) and GPT-3.5 Turbo Instruct
BenchmarkNano Banana 2 Lite (Gemini 3.1 Flash Lite Image)GPT-3.5 Turbo InstructLeader
METR time horizonsNot measured21.5%Only GPT-3.5 Turbo Instruct measured
Neither model has a result on the other 40 boards here
Image generationDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
Image generation benchmarks for Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) and GPT-3.5 Turbo Instruct
BenchmarkNano Banana 2 Lite (Gemini 3.1 Flash Lite Image)GPT-3.5 Turbo InstructLeader
Design Arena: images1239Not measuredOnly Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) measured
Design Arena: graphic design1249Not measuredOnly Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) measured
Design Arena: logos1214Not measuredOnly Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) measured
LMArena Text to Image1250Not measuredOnly Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) measured
LMArena Image Edit1313Not measuredOnly Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) measured

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

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)$0.0010Fits in one request
GPT-3.5 Turbo Instruct$0.0025Fits in one request

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) costs less

Repository review

50K input + 3K output tokens

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)$0.017Fits in one request
GPT-3.5 Turbo Instruct$0.081Exceeds the context window

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) costs less

Agent loop

200K input + 10K output tokens

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)$0.065Exceeds the context window
GPT-3.5 Turbo Instruct$0.320Exceeds the context window

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) 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 Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) and GPT-3.5 Turbo Instruct
SpecificationGoogle Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)OpenAI GPT-3.5 Turbo Instruct
MakerGoogleOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedJune 30, 2026September 28, 2023
Context window66K4K
Input $/Mtok$0.25$1.50
Output $/Mtok$1.50$2.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) better than GPT-3.5 Turbo Instruct for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) for output tokens 1.3x cheaper ($1.50 vs $2.00 per million) and a larger context window (66K against 4K tokens).

Which is cheaper, Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) or GPT-3.5 Turbo Instruct?

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) costs $0.25 per million input tokens and $1.50 per million output tokens; GPT-3.5 Turbo Instruct costs $1.50 and $2.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) or GPT-3.5 Turbo Instruct?

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image), with 66K tokens against 4K.

Has any benchmark tested both Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) and GPT-3.5 Turbo Instruct?

No benchmark has tested both yet. Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) has results on Design Arena: images, Design Arena: graphic design and Design Arena: logos; GPT-3.5 Turbo Instruct on METR time horizons. Compare them on price and context instead. Data as of October 22, 2026.

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