Whisper Large V3 vs Deepgram Nova-3: Which AI Model Should You Choose?

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

OpenAI
Speech-to-Text
vs
xAI
Speech-to-Text
Verdict

Whisper Large V3 and Deepgram Nova-3 are closely matched on pricing and context. The right choice depends on your specific workload β€” see the table below for the full breakdown.

Side-by-side specs

SpecWhisper Large V3Deepgram Nova-3
ProviderOpenAIxAI
CategorySpeech-to-TextSpeech-to-Text
Input cost / 1M tokensFreeFree
Output cost / 1M tokensFreeFree
Context windowβ€”β€”
Max output tokensβ€”β€”
Avg. latency5.0sβ€”
FeaturedYesβ€”
Newβ€”β€”
Capabilities
json
text
srt
vtt
audio

Pricing example

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

Whisper Large V3
€0.0000

100K in Γ— Free + 50K out Γ— Free

Deepgram Nova-3
€0.0000

100K in Γ— Free + 50K out Γ— Free

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 β€” using Whisper Large V3
let r = await client.chat.completions.create({
  model: "whisper-1",
  messages: [{ role: "user", content: "Hello" }],
});

// After β€” switched to Deepgram Nova-3
r = await client.chat.completions.create({
  model: "nova-3",
  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 β€” using Whisper Large V3
r = client.chat.completions.create(
    model="whisper-1",
    messages=[{"role": "user", "content": "Hello"}],
)

# After β€” switched to Deepgram Nova-3
r = client.chat.completions.create(
    model="nova-3",
    messages=[{"role": "user", "content": "Hello"}],
)
cURL
# Before β€” using Whisper Large V3
curl https://railwail.com/v1/chat/completions \
  -H "Authorization: Bearer $RAILWAIL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "whisper-1",
    "messages": [{"role": "user", "content": "Hello"}]
  }'

# After β€” switched to Deepgram Nova-3
curl https://railwail.com/v1/chat/completions \
  -H "Authorization: Bearer $RAILWAIL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "nova-3",
    "messages": [{"role": "user", "content": "Hello"}]
  }'

Which one wins for...

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

Coding
Whisper Large V3

Higher coding category match or larger context wins.

Writing
Whisper Large V3

Bigger context window helps maintain long-form coherence.

Long documents
Whisper Large V3

The larger context window is the deciding factor.

Vision
Tie

Multimodal/vision support is required for image inputs.

Real-time chat
Whisper Large V3

Lower average latency wins for interactive UX.

Cost-sensitive
Tie

The model with the lower input-token price wins.

Frequently asked questions

Which is cheaper, Whisper Large V3 or Deepgram Nova-3?
Pricing for Whisper Large V3 and Deepgram Nova-3 is comparable on input tokens. For a 100K input + 50K output workload, Whisper Large V3 costs about €0.0000 and Deepgram Nova-3 costs about €0.0000.
Which has more context, Whisper Large V3 or Deepgram Nova-3?
Whisper Large V3 and Deepgram Nova-3 have similar context windows (β€” vs β€”).
Is Whisper Large V3 better than Deepgram Nova-3 for coding?
For coding-heavy workloads we lean toward Whisper Large V3 on this comparison β€” 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 Whisper Large V3 and Deepgram Nova-3 via Railwail?
Yes. Both Whisper Large V3 and Deepgram Nova-3 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 β€” no SDK swap, no separate billing.
How do I switch from Whisper Large V3 to Deepgram Nova-3?
Replace the model identifier "whisper-1" with "nova-3" in your request payload. Everything else β€” API key, base URL, request shape β€” stays the same. See the code example on this page for the exact one-line change.

Try Whisper Large V3 and Deepgram Nova-3 side by side

One API key, one endpoint, both models. Start free β€” no credit card required.