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Model comparison · Updated 10 Oct 2026

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) vs Qwen3 14B

Qwen3 14B is about 2.1× cheaper on input ($0.12 against $0.25 per 1M tokens) and on output. Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) has the larger context window (66K against 41K tokens). For a support chatbot at 10,000 chats a day, the standard-tier bill is about $248 a month for Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) and $75.60 for Qwen3 14B.

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ModelsAtlas. “Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) vs Qwen3 14B”. Retrieved 10 Oct 2026. https://modelsatlas.com/compare/google/gemini-3-1-flash-lite-image/vs/qwen/3-14b

Model A

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)

by Google · weights not marked open · GRIDC2

Input / 1M
$0.25
observed We measured
Source
Our catalogue
Retrieved
17 Aug 2026
Output / 1M$1.50
Context66K
vs

Model B

Qwen3 14B

by Qwen (Alibaba) · open weights · GRIDC2

Input / 1M
$0.12
observed We measured
Source
Our catalogue
Retrieved
17 Aug 2026
Output / 1M$0.24
Context41K

Key numbers

Standard tier · highlighted = better

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)
Qwen3 14B
Input / 1M tokens
$0.25
$0.12
Output / 1M tokens
$1.50
$0.24
Batch input / output
Not listed
Not listed
Context window
65,536
40,960
Input types
Not disclosed
text
Weights
Not marked open
Open
License
Not disclosed
apache-2.0
Tiers listed
standard
standard
Prices checked
2026-08-17
2026-10-10

What it costs for real workloads

Monthly, standard tier, 30 days

Support chatbot10k chats/day · 1.5k in, 300 out
$248/mo
$75.60/mo
RAG over documents2k queries/day · 12k in, 500 out
$225/mo
$93.60/mo
Coding agent300 tasks/day · 60k in, 8k out
$243/mo
$82.08/mo

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)   Qwen3 14B · Derived from the standard-tier prices above, input and output tokens per request as stated, 30 days. Excludes caching discounts and batch. Try your own numbers.

On the atlas

Price band (A–H) × context band (1–6)

Same square. Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) and Qwen3 14B share C2.

Same square as Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image): Qwen2.5 7B Instruct ($0.10), Voxtral Small 24B 2507 ($0.10), Qwen3 30B A3B ($0.12). Open C2

AFreeB<$0.10C$0.10–0.30D$0.30–1E$1–3F$3–10G$10–30H$30+1<32K232–128K3128–256K4256K–1M51M6>1MINPUT PRICE PER 1M TOKENS →CONTEXT WINDOW ↑ · position within a square follows the real valueSaba · C2Command R (08-2024) · C2Qwen3 30B A3B · C2Voxtral Small 24B 2507 · C2Qwen2.5 7B Instruct · C2Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)Qwen3 14BQwen3 14B
Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)Qwen3 14BNearest neighboursOpen weights
View the map as a table (1 squares)
SquarePrice bandContext bandModels
GRIDC2$0.10–0.3032–128KNano Banana 2 Lite (Gemini 3.1 Flash Lite Image), Qwen3 14B, Saba, Command R (08-2024), Qwen3 30B A3B, Voxtral Small 24B 2507, Qwen2.5 7B Instruct

Capabilities side by side

Only what our records list

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)
Qwen3 14B
Vision input
Not disclosed
Not recorded
Audio input
Not disclosed
Not recorded
Open weights
Not marked open
Supported
Batch tier
Not listed
Not listed
Free tier
Not listed
Not listed
Thinking tier
Not listed
Not listed

Which should you choose?

Editorial

Choose Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) if…

  • your prompts are long: it takes 65,536 tokens against 40,960

Choose Qwen3 14B if…

  • you pay by the token: it costs $0.12 per 1M input against $0.25
  • output dominates your bill: $0.24 per 1M output against $1.50
  • you want open weights, so you can run the model yourself

Each reason is a fact from the tables above. Picking between them is our judgement, and we do not benchmark quality: price and context are what we can measure, so test both on your own prompts before you commit.

Questions

Is Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) better than Qwen3 14B?
We do not benchmark quality, so we cannot say. On the recorded numbers: Qwen3 14B is about 2.1× cheaper on input ($0.12 against $0.25 per 1M tokens) and on output. Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) has the larger context window (66K against 41K tokens). For a support chatbot at 10,000 chats a day, the standard-tier bill is about $248 a month for Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) and $75.60 for Qwen3 14B. Which is better for you depends on your task; test both on your own prompts.
Which is cheaper, Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) or Qwen3 14B?
Qwen3 14B: $0.12 against $0.25 per 1M input tokens, and $0.24 against $1.50 per 1M output, on standard pricing.
How much does each cost per 1M tokens?
Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image): $0.25 input and $1.50 output. Qwen3 14B: $0.12 input and $0.24 output. Standard tier, USD.
Which has the larger context window?
Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image), with 65,536 tokens. Qwen3 14B has 40,960 tokens.
Do both offer batch pricing?
Neither lists a batch tier in our catalogue.
Can both read images or audio?
Input types recorded for Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image): none recorded. For Qwen3 14B: text. Where a record lists none we say so rather than guess; check each vendor's documentation before relying on a capability.
Is either model open-weight?
Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image): not marked open-weight in our records. Qwen3 14B: open weights.
What would each cost for a support chatbot?
At 10,000 chats a day, 1,500 input and 300 output tokens each, 30 days, standard tier: about $248 a month for Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) and $75.60 for Qwen3 14B. This is our calculation from the listed prices, not a quote.

About the two models

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)

By Google. $0.25 input and $1.50 output per 1M tokens, 66K context, atlas square C2. Tiers listed: standard.

Full specs & pricing →

Qwen3 14B

By Qwen (Alibaba), open weights. $0.12 input and $0.24 output per 1M tokens, 41K context, atlas square C2. Tiers listed: standard.

Full specs & pricing →

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