GPT-5.4 vs o3-mini: Which AI Model Should You Choose?
Pricing, context windows, latency, capabilities, and a one-line code switch โ everything you need to pick the right model.
Choose o3-mini for cost-sensitive workloads โ it is roughly 2.3ร cheaper on input tokens. Choose GPT-5.4 when you need its broader capabilities or stronger benchmarks.
Choose GPT-5.4 for long documents (1.1M tokens context). Choose o3-mini for shorter prompts where the smaller window keeps latency and cost down.
These models serve different use cases (Multimodal vs Text & Chat) โ pick the one whose category matches your workload.
Side-by-side specs
| Spec | GPT-5.4 | o3-mini |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Category | Multimodal | Text & Chat |
| Input cost / 1M tokens | $3.00 | $1.32 |
| Output cost / 1M tokens | $18.00 | $5.28 |
| Context window | 1.1M tokens | 200K tokens |
| Max output tokens | 128,000 | 100,000 |
| Avg. latency | โ | 10.0s |
| Featured | Yes | Yes |
| New | Yes | Yes |
| Capabilities | text image | โ |
Pricing example
A typical chat workload of 100,000 input tokens plus 50,000 output tokens.
100K in ร $3.00 + 50K out ร $18.00
100K in ร $1.32 + 50K out ร $5.28
For this workload, o3-mini is cheaper than GPT-5.4 by $0.80 per request.
Switch in one line
Both models live behind Railwail's OpenAI-compatible endpoint. Replace the model string and you are done.
import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.RAILWAIL_API_KEY,
baseURL: "https://railwail.com/v1",
});
// Before โ using GPT-5.4
let r = await client.chat.completions.create({
model: "gpt-5.4",
messages: [{ role: "user", content: "Hello" }],
});
// After โ switched to o3-mini
r = await client.chat.completions.create({
model: "o3-mini",
messages: [{ role: "user", content: "Hello" }],
});from openai import OpenAI
client = OpenAI(
api_key=os.environ["RAILWAIL_API_KEY"],
base_url="https://railwail.com/v1",
)
# Before โ using GPT-5.4
r = client.chat.completions.create(
model="gpt-5.4",
messages=[{"role": "user", "content": "Hello"}],
)
# After โ switched to o3-mini
r = client.chat.completions.create(
model="o3-mini",
messages=[{"role": "user", "content": "Hello"}],
)# Before โ using GPT-5.4
curl https://railwail.com/v1/chat/completions \
-H "Authorization: Bearer $RAILWAIL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-5.4",
"messages": [{"role": "user", "content": "Hello"}]
}'
# After โ switched to o3-mini
curl https://railwail.com/v1/chat/completions \
-H "Authorization: Bearer $RAILWAIL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "o3-mini",
"messages": [{"role": "user", "content": "Hello"}]
}'Which one wins for...
Quick verdicts derived from public specs. Always validate on your own workload.
Higher coding category match or larger context wins.
Bigger context window helps maintain long-form coherence.
The larger context window is the deciding factor.
Multimodal/vision support is required for image inputs.
Lower average latency wins for interactive UX.
The model with the lower input-token price wins.
Frequently asked questions
Try GPT-5.4 and o3-mini side by side
One API key, one endpoint, both models. Start free โ no credit card required.