GoogleGemini 3.1 Flash-LiteVSOpenAIGPT-5.4 nano

Analysis by:the whichllmmodel Editorial Team|Updated: June 2026

Our Take

While these models specialize in different coding tasks: Gemini 3.1 Flash-Lite is suited for scripting single-file apps or clearly defined functions, while GPT-5.4 nano excels at complex codebases, multi-file repositories, and architectural planning, they share very similar reasoning capabilities. GPT-5.4 nano is the smarter buy here as it offers the same level of performance while being 1.2x cheaper than Gemini 3.1 Flash-Lite.

▶WHY?

Benchmark Calculations & Evidence:

Coding Evaluation: Gemini 3.1 Flash-Lite was evaluated on LiveCodeBench (scoring 72%), while GPT-5.4 nano was evaluated on SWE-bench Pro (scoring 52.4%).

Reasoning Accuracy: Both models were evaluated on the GPQA Diamond benchmark. Gemini 3.1 Flash-Lite scored 82.2%, while GPT-5.4 nano scored 82.8%.

Cost Ratio: Gemini 3.1 Flash-Lite blended CPM is 1.2x higher than GPT-5.4 nano.

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Model Specs

Gemini 3.1 Flash-Lite

Website

Benchmarks & Scores

Coding (live-code-bench)

72%

scripting single-file apps or clearly defined functions

Reasoning (gpqa-diamond)

82.2%

graduate-level science QA

Cost & Context

Cost (per 1M tokens)

$0.56Input: $0.25 | Output: $1.50

Context WindowLarger

1.05M tokens

Model Specs

GPT-5.4 nano

Website

Benchmarks & Scores

Coding (swe-bench-pro)

52.4%

complex codebases, multi-file repositories, and architectural planning

Reasoning (gpqa-diamond)Winner (+0.6%)

82.8%

graduate-level science QA

Cost & Context

Cost (per 1M tokens)1.2x cheaper

$0.46Input: $0.20 | Output: $1.25

Context Window

400k tokens

Read our data collection methodology

Frequently Asked Questions about Gemini 3.1 Flash-Lite vs GPT-5.4 nano

GPT-5.4 nano is cheaper than Gemini 3.1 Flash-Lite. GPT-5.4 nano has a blended cost of $0.46/1M tokens, which is about 1.2x cheaper than Gemini 3.1 Flash-Lite at $0.56/1M tokens.

For coding tasks, Gemini 3.1 Flash-Lite scores 72% on live-code-bench (scripting single-file apps or clearly defined functions), while GPT-5.4 nano scores 52.4% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning).

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