Vedika Vision vs Deepgram Nova 3
Compare Vedika Vision and Deepgram Nova 3: pricing, performance, context window, latency, and best use cases. Side-by-side comparison on XALEN.
Updated 2026-05-21 · By Abhishek Raj · Our methodology
| Feature | Vedika Vision | Deepgram Nova 3 |
|---|---|---|
| Category | Vision | Speech |
| Parameters | 26B | ~1B |
| Context Window | 32K | Streaming |
| Input Price | $0.08/1M tokens | $0.004/min/1M tokens |
| Output Price | $0.12/1M tokens | N/A/1M tokens |
| Latency | ~500ms | ~100ms |
Choose Vedika Vision when:
- ✓ Chart image analysis
- ✓ Temple photo description
- ✓ Vastu photo analysis
Chart image analysis, Yantra recognition, Sacred geometry
Choose Deepgram Nova 3 when:
- ✓ Real-time transcription
- ✓ Call centers
- ✓ Meeting notes
Ultra-low latency, Streaming native, Very cheap
Verdict: Vedika Vision vs Deepgram Nova 3
For cost efficiency, Deepgram Nova 3 wins at $0.004/min/1M input tokens. For speed, Deepgram Nova 3 is faster at ~100ms. Vedika Vision excels at Chart image analysis while Deepgram Nova 3 is better for Real-time transcription. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.
Detailed Analysis
Pricing Comparison
Vedika Vision costs $0.08/1M input tokens and $0.12/1M output tokens. Deepgram Nova 3 costs $0.004/min input and N/A output. Deepgram Nova 3 is 20.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Vedika Vision has a 32K context window with ~500ms latency. Deepgram Nova 3 offers Streaming context at ~100ms. Both have identical context windows.
Best For
Vedika Vision (Vision) is optimized for: Chart image analysis, Temple photo description, Vastu photo analysis. Deepgram Nova 3 (Speech) works best for: Real-time transcription, Call centers, Meeting notes.
Try Both on XALEN
Both models are available through XALEN's OpenAI-compatible API. Switch between them by changing the model parameter:
from xalen import XALEN
client = XALEN(api_key="xln_test_YOUR_KEY")
# Use Vedika Vision
response_a = client.chat.completions.create(
model="vedika-vision",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use Deepgram Nova 3
response_b = client.chat.completions.create(
model="deepgram-nova-3",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Vedika Vision or Deepgram Nova 3?
Vedika Vision (Vision, 26B) offers Chart image analysis. Deepgram Nova 3 (Speech, ~1B) offers Ultra-low latency. Choose Vedika Vision for Chart image analysis or Deepgram Nova 3 for Real-time transcription.
How much does Vedika Vision cost vs Deepgram Nova 3?
Vedika Vision: $0.08/1M input, $0.12/1M output. Deepgram Nova 3: $0.004/min/1M input, N/A/1M output. Both available on XALEN with batch processing at 50% discount.
Can I use both models on XALEN?
Yes. XALEN provides 200+ models through a single OpenAI-compatible API. Switch between Vedika Vision and Deepgram Nova 3 by changing the model parameter. No code changes needed.
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Last updated: 2026-05-21. Pricing and specifications may change. Check pricing page for latest rates.