Railwail
Sign In

Granite Code 8B vs GPT-5.4 Nano: Which AI Model Should You Choose?

Pricing, context windows, latency, capabilities, and a one-line code switch — everything you need to pick the right model.

Replicate
Code
vs
OpenAI
Multimodal
Verdict

Choose Granite Code 8B for cost-sensitive workloads — it is roughly 4.0× cheaper on input tokens. Choose GPT-5.4 Nano when you need its broader capabilities or stronger benchmarks.

Choose GPT-5.4 Nano for long documents (400K tokens context). Choose Granite Code 8B for shorter prompts where the smaller window keeps latency and cost down.

These models serve different use cases (Code vs Multimodal) — pick the one whose category matches your workload.

Side-by-side specs

SpecGranite Code 8BGPT-5.4 Nano
ProviderReplicateOpenAI
CategoryCodeMultimodal
Input cost / 1M tokens$0.060$0.24
Output cost / 1M tokens$0.30$1.50
Context window128K tokens400K tokens
Max output tokens8,19232,000
Avg. latency——
Featured——
New—Yes
Capabilities
text
text
image

Pricing example

A typical chat workload of 100,000 input tokens plus 50,000 output tokens.

Granite Code 8B
$0.021

100K in × $0.060 + 50K out × $0.30

GPT-5.4 Nano
$0.099

100K in × $0.24 + 50K out × $1.50

For this workload, Granite Code 8B is cheaper than GPT-5.4 Nano by $0.078 per request.

Switch in one line

Both models live behind Railwail's OpenAI-compatible endpoint. Replace the model string and you are done.

JavaScript / TypeScript
import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.RAILWAIL_API_KEY,
  baseURL: "https://railwail.com/v1",
});

// Before — using Granite Code 8B
let r = await client.chat.completions.create({
  model: "ibm-granite/granite-8b-code-instruct-128k",
  messages: [{ role: "user", content: "Hello" }],
});

// After — switched to GPT-5.4 Nano
r = await client.chat.completions.create({
  model: "gpt-5.4-nano",
  messages: [{ role: "user", content: "Hello" }],
});
Python
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["RAILWAIL_API_KEY"],
    base_url="https://railwail.com/v1",
)

# Before — using Granite Code 8B
r = client.chat.completions.create(
    model="ibm-granite/granite-8b-code-instruct-128k",
    messages=[{"role": "user", "content": "Hello"}],
)

# After — switched to GPT-5.4 Nano
r = client.chat.completions.create(
    model="gpt-5.4-nano",
    messages=[{"role": "user", "content": "Hello"}],
)
cURL
# Before — using Granite Code 8B
curl https://railwail.com/v1/chat/completions \
  -H "Authorization: Bearer $RAILWAIL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "ibm-granite/granite-8b-code-instruct-128k",
    "messages": [{"role": "user", "content": "Hello"}]
  }'

# After — switched to GPT-5.4 Nano
curl https://railwail.com/v1/chat/completions \
  -H "Authorization: Bearer $RAILWAIL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5.4-nano",
    "messages": [{"role": "user", "content": "Hello"}]
  }'

Which one wins for...

Quick verdicts derived from public specs. Always validate on your own workload.

Coding
Granite Code 8B

Higher coding category match or larger context wins.

Writing
GPT-5.4 Nano

Bigger context window helps maintain long-form coherence.

Long documents
GPT-5.4 Nano

The larger context window is the deciding factor.

Vision
GPT-5.4 Nano

Multimodal/vision support is required for image inputs.

Real-time chat
Tie

Lower average latency wins for interactive UX.

Cost-sensitive
Granite Code 8B

The model with the lower input-token price wins.

Frequently asked questions

Which is cheaper, Granite Code 8B or GPT-5.4 Nano?
Granite Code 8B is cheaper. On a 100K input + 50K output example, Granite Code 8B costs about $0.021 versus $0.099 for GPT-5.4 Nano — a saving of $0.078.
Which has more context, Granite Code 8B or GPT-5.4 Nano?
GPT-5.4 Nano has the larger context window at 400K tokens, compared to 128K tokens for Granite Code 8B.
Is Granite Code 8B better than GPT-5.4 Nano for coding?
For coding-heavy workloads we lean toward Granite Code 8B on this comparison — it scores higher on the relevant heuristics (category, tags, or context window). Both models are usable for code via Railwail's OpenAI-compatible endpoint, so the safest path is to A/B test on your own prompts.
Can I use both Granite Code 8B and GPT-5.4 Nano via Railwail?
Yes. Both Granite Code 8B and GPT-5.4 Nano are accessible through a single Railwail API key and the OpenAI-compatible /v1/chat/completions endpoint. You only change the "model" parameter to switch between them — no SDK swap, no separate billing.
How do I switch from Granite Code 8B to GPT-5.4 Nano?
Replace the model identifier "ibm-granite/granite-8b-code-instruct-128k" with "gpt-5.4-nano" in your request payload. Everything else — API key, base URL, request shape — stays the same. See the code example on this page for the exact one-line change.

Try Granite Code 8B and GPT-5.4 Nano side by side

One API key, one endpoint, both models. Start free — no credit card required.

Get Started FreeView Granite Code 8BView GPT-5.4 Nano