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Nano Banana (Gemini 2.5 Flash Image) vs GPT-5.2-Codex

Nano Banana (Gemini 2.5 Flash Image) costs 5.6x less per output token than GPT-5.2-Codex ($2.50 vs $14.00 per million). Updated October 21, 2026; no benchmark has tested both models yet.

Nano Banana (Gemini 2.5 Flash Image)Google
Coding
No data
Overall
No data
Output $/M
$2.50
GPT-5.2-CodexOpenAI
Coding
45.4
Overall
28.5
Output $/M
$14.00
vs $2.50 vs $14.00 per 1M output tokens. Nano Banana (Gemini 2.5 Flash Image) is 5.6x cheaper.

Nano Banana (Gemini 2.5 Flash Image) or GPT-5.2-Codex: which to pick

Only GPT-5.2-Codex has a coding score, 45.4 on the Vibe Coding Index; Nano Banana (Gemini 2.5 Flash Image) has none, so the two cannot be ranked on coding.

Pick Nano Banana (Gemini 2.5 Flash Image) for output tokens 5.6x cheaper ($2.50 vs $14.00 per million).

No benchmark has tested both yet. Nano Banana (Gemini 2.5 Flash Image) has results on Design Arena: images, Design Arena: graphic design and Design Arena: logos; GPT-5.2-Codex on SWE-bench Verified, SWE-bench Multilingual and LMArena WebDev. 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 (Gemini 2.5 Flash Image) not benchmarked, GPT-5.2-Codex 45.4 from 3 benchmarks.
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 (Gemini 2.5 Flash Image) $2.50 against GPT-5.2-Codex $14.00 per million output tokens, 5.6x apart.
Context window
Nano Banana (Gemini 2.5 Flash Image) takes 33K tokens, GPT-5.2-Codex 400K.

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.

CodingDirectional onlySix of these boards feed the Vibe Coding Index11 boards measured
Coding benchmarks for Nano Banana (Gemini 2.5 Flash Image) and GPT-5.2-Codex
BenchmarkNano Banana (Gemini 2.5 Flash Image)GPT-5.2-CodexLeader
SWE-bench VerifiedNot measured72.8%Only GPT-5.2-Codex measured
SWE-bench MultilingualNot measured66.3%Only GPT-5.2-Codex measured
LMArena WebDevNot measured1339Only GPT-5.2-Codex measured
LiveCodeBench (Vals AI)Not measured88.0%Only GPT-5.2-Codex measured
SWE-bench Verified (Vals AI)Not measured72.4%Only GPT-5.2-Codex measured
Vibe Code Bench (Vals AI)Not measured37.9%Only GPT-5.2-Codex measured
Terminal-Bench Hard (Artificial Analysis run)Not measured37.1%Only GPT-5.2-Codex measured
Terminal-BenchNot measured66.5%Only GPT-5.2-Codex measured
ALE-BenchNot measured1299.9Only GPT-5.2-Codex measured
LMArena WebDev: ReactNot measured1329Only GPT-5.2-Codex measured
LMArena WebDev: HTMLNot measured1348Only GPT-5.2-Codex measured
Neither model has a result on the other 27 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Intelligence benchmarks for Nano Banana (Gemini 2.5 Flash Image) and GPT-5.2-Codex
BenchmarkNano Banana (Gemini 2.5 Flash Image)GPT-5.2-CodexLeader
AA Intelligence IndexNot measured28.5Only GPT-5.2-Codex measured
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
Agentic work benchmarks for Nano Banana (Gemini 2.5 Flash Image) and GPT-5.2-Codex
BenchmarkNano Banana (Gemini 2.5 Flash Image)GPT-5.2-CodexLeader
Design Arena: agents building web appsNot measured1051Only GPT-5.2-Codex measured
Design Arena: agents building full-stack appsNot measured993Only GPT-5.2-Codex measured
Design Arena: agents building mobile appsNot measured1090Only GPT-5.2-Codex measured
Design Arena: agents building Android appsNot measured1176Only GPT-5.2-Codex measured
Design Arena: agents building Godot gamesNot measured1142Only GPT-5.2-Codex measured
τ²-Bench TelecomNot measured92.1%Only GPT-5.2-Codex measured
Neither model has a result on the other 33 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Reasoning benchmarks for Nano Banana (Gemini 2.5 Flash Image) and GPT-5.2-Codex
BenchmarkNano Banana (Gemini 2.5 Flash Image)GPT-5.2-CodexLeader
GPQA Diamond (Artificial Analysis run)Not measured89.9%Only GPT-5.2-Codex measured
Humanity's Last Exam (Artificial Analysis run)Not measured35.7%Only GPT-5.2-Codex measured
Neither model has a result on the other 19 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
General benchmarks for Nano Banana (Gemini 2.5 Flash Image) and GPT-5.2-Codex
BenchmarkNano Banana (Gemini 2.5 Flash Image)GPT-5.2-CodexLeader
IFBenchNot measured77.6%Only GPT-5.2-Codex measured
Long context reasoning (AA-LCR)Not measured82.3%Only GPT-5.2-Codex measured
Neither model has a result on the other 44 boards here
Image generationDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
Image generation benchmarks for Nano Banana (Gemini 2.5 Flash Image) and GPT-5.2-Codex
BenchmarkNano Banana (Gemini 2.5 Flash Image)GPT-5.2-CodexLeader
Design Arena: images1179Not measuredOnly Nano Banana (Gemini 2.5 Flash Image) measured
Design Arena: graphic design1151Not measuredOnly Nano Banana (Gemini 2.5 Flash Image) measured
Design Arena: logos1169Not measuredOnly Nano Banana (Gemini 2.5 Flash Image) measured
Neither model has a result on the other 2 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

Nano Banana (Gemini 2.5 Flash Image)$0.0015Fits in one request
GPT-5.2-Codex$0.0088Fits in one request

Nano Banana (Gemini 2.5 Flash Image) costs less

Repository review

50K input + 3K output tokens

Nano Banana (Gemini 2.5 Flash Image)$0.022Exceeds the context window
GPT-5.2-Codex$0.130Fits in one request

Nano Banana (Gemini 2.5 Flash Image) costs less

Agent loop

200K input + 10K output tokens

Nano Banana (Gemini 2.5 Flash Image)$0.085Exceeds the context window
GPT-5.2-Codex$0.490Fits in one request

Nano Banana (Gemini 2.5 Flash 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 (Gemini 2.5 Flash Image) and GPT-5.2-Codex
SpecificationGoogle Nano Banana (Gemini 2.5 Flash Image)OpenAI GPT-5.2-Codex
MakerGoogleOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedOctober 7, 2025January 14, 2026
Context window33K400K
Input $/Mtok$0.30$1.75
Output $/Mtok$2.50$14.00
Coding indexNot benchmarked45.4
Independent measurements behind it03
Cost per solved taskNot computable$0.43
SourceOpenRouter listingOpenRouter listing

Questions

Is Nano Banana (Gemini 2.5 Flash Image) better than GPT-5.2-Codex for coding?

Only GPT-5.2-Codex has a coding score, 45.4 on the Vibe Coding Index; Nano Banana (Gemini 2.5 Flash Image) has none, so the two cannot be ranked on coding. Pick Nano Banana (Gemini 2.5 Flash Image) for output tokens 5.6x cheaper ($2.50 vs $14.00 per million).

Which is cheaper, Nano Banana (Gemini 2.5 Flash Image) or GPT-5.2-Codex?

Nano Banana (Gemini 2.5 Flash Image) costs $0.30 per million input tokens and $2.50 per million output tokens; GPT-5.2-Codex costs $1.75 and $14.00. Cost per solved task is known for GPT-5.2-Codex only.

Which has the bigger context window, Nano Banana (Gemini 2.5 Flash Image) or GPT-5.2-Codex?

GPT-5.2-Codex, with 400K tokens against 33K.

Has any benchmark tested both Nano Banana (Gemini 2.5 Flash Image) and GPT-5.2-Codex?

No benchmark has tested both yet. Nano Banana (Gemini 2.5 Flash Image) has results on Design Arena: images, Design Arena: graphic design and Design Arena: logos; GPT-5.2-Codex on SWE-bench Verified, SWE-bench Multilingual and LMArena WebDev. Compare them on price and context instead. Data as of October 21, 2026.

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