Gemini 3.1 Flash Lite vs GPT-5.4 Pro
At a Glance
| Compare |  Gemini 3.1 Flash LiteGoogle DeepMind |  GPT-5.4 ProOpenAI |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.25Google AI ↗ · Aug 29, 2026 | $30.00Openai ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | $1.50Google AI ↗ · Aug 29, 2026 | $180.00Openai ↗ · Sep 3, 2026 |
| Context windowMaximum documented tokens | 1,049K | 1,050K |
| Model facts checked | Aug 29, 2026View model evidence → | Sep 3, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
Side-by-Side Facts
| Field | Gemini 3.1 Flash-Lite | GPT-5.4 Pro |
|---|---|---|
| Developer | Google DeepMind | OpenAI |
| Family | Gemini 3 | Gpt 5 4 |
| Model | Gemini 3.1 Flash-Lite | GPT-5.4 Pro |
| Version | Gemini 3.1 Flash-Lite | GPT-5.4 Pro |
| Lifecycle | active | active |
| Released | Unknown | 2026-03-05 |
| Knowledge cutoff | Unknown | 2025-08-31 |
| Input modalities | Text, Image, Video, Audio, Document | Text, Image |
| Output modalities | Text | Text |
| Context window | 1,049K | 1,050K |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | No |
| API available | Yes | Yes |
| Self-hostable | No | No |
| Provider access | Google AI (Standard), Google Gemini (Standard) | Openai (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning, structured_outputs, tools |
Gemini 3.1 Flash Lite Capabilities
GPT-5.4 Pro Capabilities
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Primary Evidence
Sources and Freshness
Questions
Gemini 3.1 Flash Lite vs GPT-5.4 Pro FAQs
Is Gemini 3.1 Flash Lite or GPT-5.4 Pro better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 3.1 Flash Lite and GPT-5.4 Pro, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Gemini 3.1 Flash Lite or GPT-5.4 Pro?+
Gemini 3.1 Flash Lite is $0.25 and GPT-5.4 Pro is $30.00 per million tokens, so Gemini 3.1 Flash Lite is cheaper on this metric. Gemini 3.1 Flash Lite is $1.50 and GPT-5.4 Pro is $180.00 per million tokens, so Gemini 3.1 Flash Lite is cheaper on this metric.
Which has a larger context window, Gemini 3.1 Flash Lite or GPT-5.4 Pro?+
GPT-5.4 Pro has the larger sourced context window. Gemini 3.1 Flash Lite supports 1,049K and GPT-5.4 Pro supports 1,050K.
Which performs better in benchmarks, Gemini 3.1 Flash Lite or GPT-5.4 Pro?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Gemini 3.1 Flash Lite or GPT-5.4 Pro be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. Gemini 3.1 Flash Lite is not marked open weight; GPT-5.4 Pro is not marked open weight.
Can Gemini 3.1 Flash Lite and GPT-5.4 Pro understand images?+
Gemini 3.1 Flash Lite is documented with image input; GPT-5.4 Pro is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Gemini 3.1 Flash Lite or GPT-5.4 Pro?+
GPT-5.4 Pro has the larger sourced maximum output: Gemini 3.1 Flash Lite supports 66K and GPT-5.4 Pro supports 128K output tokens.
Do Gemini 3.1 Flash Lite and GPT-5.4 Pro support reasoning and tool use?+
Gemini 3.1 Flash Lite: reasoning, tool calling, and image input. GPT-5.4 Pro: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Gemini 3.1 Flash Lite or GPT-5.4 Pro?+
Gemini 3.1 Flash Lite has 2 sourced provider routes; GPT-5.4 Pro has 2, a tie.
Which offers better value, Gemini 3.1 Flash Lite or GPT-5.4 Pro?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.