Compare

Gemini 3.1 Flash Lite vs GPT-5.4 Nano

Pricing per million tokens, context window, capabilities — pulled from each provider's public docs. All 2 are available via the same AIgateway OpenAI-compatible endpoint; flip the model string to switch.

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Gemini 3.1 Flash Lite
google/gemini-3.1-flash-lite
GPT-5.4 Nano
openai/gpt-5.4-nano
Provider
Google
OpenAI
Family
Gemini 3
GPT-5
Modality
text
text
Context window
1,000,000 tok
128,000 tok
Max output
8,192 tok
16,384 tok
Released
2026-05-22
2026-05-22
License
Proprietary
Proprietary
Input price
$0.250 /1M
$0.200 /1M
Output price
$1.50 /1M
$1.25 /1M
Cache read
$0.025 /1M
$0.020 /1M
Tools
yes
yes
Streaming
yes
yes
Vision
yes
JSON mode
yes
yes
Reasoning
yes
Prompt caching
yes
Batch API
yes
Try it
Open in playground →
Open in playground →
Gemini 3.1 Flash Lite
google/gemini-3.1-flash-lite
Full spec →

Google's lightest and most cost-efficient Gemini model for high-throughput tasks.

Strengths
  • Cheapest Gemini
  • Multi-modal native
  • Very fast
Use cases
Bulk ingestionClassificationThrowaway drafts
GPT-5.4 Nano
openai/gpt-5.4-nano
Full spec →

GPT-5.4 nano is OpenAI's smallest and fastest model, optimized for edge and low-latency use cases.

Strengths
  • Dirt cheap
  • Fast
  • JSON mode
Use cases
ClassifiersData extractionRouting

Compare with another

GPT-5 vs GPT-5.4 Nano
openai/gpt-5 · openai/gpt-5.4-nano
GPT-5 Chat vs GPT-5.4 Nano
openai/gpt-5-chat · openai/gpt-5.4-nano
GPT-5 Mini vs GPT-5.4 Nano
openai/gpt-5-mini · openai/gpt-5.4-nano
GPT-5 Nano vs GPT-5.4 Nano
openai/gpt-5-nano · openai/gpt-5.4-nano
GPT-5.1 vs GPT-5.4 Nano
openai/gpt-5.1 · openai/gpt-5.4-nano
SWITCH BETWEEN THEM

One key, all 2, one line different.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.aigateway.sh/v1",
    api_key="sk-aig-...",
)

# Gemini 3.1 Flash Lite
client.chat.completions.create(
    model="google/gemini-3.1-flash-lite",
    messages=[{"role":"user","content":"hello"}],
)

# GPT-5.4 Nano
client.chat.completions.create(
    model="openai/gpt-5.4-nano",
    messages=[{"role":"user","content":"hello"}],
)
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