Voyage AI voyage-3 vs OpenAI text-embedding-3-large: 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.
Choose Voyage AI voyage-3 for cost-sensitive workloads — it is roughly 2.2× cheaper on input tokens. Choose OpenAI text-embedding-3-large when you need its broader capabilities or stronger benchmarks.
Choose Voyage AI voyage-3 for long documents (32K tokens context). Choose OpenAI text-embedding-3-large for shorter prompts where the smaller window keeps latency and cost down.
Side-by-side specs
| Spec | Voyage AI voyage-3 | OpenAI text-embedding-3-large |
|---|---|---|
| Provider | xAI | OpenAI |
| Category | Embeddings | Embeddings |
| Input cost / 1M tokens | €0.060 | €0.130 |
| Output cost / 1M tokens | Free | Free |
| Context window | 32K tokens | 8K tokens |
| Max output tokens | — | — |
| Avg. latency | — | 600ms |
| Featured | Yes | Yes |
| New | — | — |
| Capabilities | text | text |
Pricing example
A typical chat workload of 100,000 input tokens plus 50,000 output tokens.
100K in × €0.060 + 50K out × Free
100K in × €0.130 + 50K out × Free
For this workload, Voyage AI voyage-3 is cheaper than OpenAI text-embedding-3-large by €0.0070 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 — using Voyage AI voyage-3
let r = await client.chat.completions.create({
model: "voyage-3",
messages: [{ role: "user", content: "Hello" }],
});
// After — switched to OpenAI text-embedding-3-large
r = await client.chat.completions.create({
model: "text-embedding-3-large",
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 — using Voyage AI voyage-3
r = client.chat.completions.create(
model="voyage-3",
messages=[{"role": "user", "content": "Hello"}],
)
# After — switched to OpenAI text-embedding-3-large
r = client.chat.completions.create(
model="text-embedding-3-large",
messages=[{"role": "user", "content": "Hello"}],
)# Before — using Voyage AI voyage-3
curl https://railwail.com/v1/chat/completions \
-H "Authorization: Bearer $RAILWAIL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "voyage-3",
"messages": [{"role": "user", "content": "Hello"}]
}'
# After — switched to OpenAI text-embedding-3-large
curl https://railwail.com/v1/chat/completions \
-H "Authorization: Bearer $RAILWAIL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "text-embedding-3-large",
"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 Voyage AI voyage-3 and OpenAI text-embedding-3-large side by side
One API key, one endpoint, both models. Start free — no credit card required.