Vedika Pro Ultra vs Vedika Seva Voice
Compare Vedika Pro Ultra and Vedika Seva Voice: 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 Pro Ultra | Vedika Seva Voice |
|---|---|---|
| Category | Domain Specialist | Voice |
| Parameters | 120B | Pipeline |
| Context Window | 256K | 30s |
| Input Price | $0.12/1M tokens | $0.015/min/1M tokens |
| Output Price | $0.20/1M tokens | $0.02/min/1M tokens |
| Latency | ~600ms | ~300ms |
Choose Vedika Pro Ultra when:
- ✓ Kundali matching reports
- ✓ Multi-chart analysis
- ✓ Enterprise platforms
256K context, Deep yoga reasoning, Multi-system comparison
Choose Vedika Seva Voice when:
- ✓ Booking confirmations
- ✓ Queue updates
- ✓ Service info
Clear diction, Service-oriented, Fast response
Verdict: Vedika Pro Ultra vs Vedika Seva Voice
For cost efficiency, Vedika Seva Voice wins at $0.015/min/1M input tokens. For speed, Vedika Seva Voice is faster at ~300ms. Vedika Pro Ultra excels at Kundali matching reports while Vedika Seva Voice is better for Booking confirmations. 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 Pro Ultra costs $0.12/1M input tokens and $0.20/1M output tokens. Vedika Seva Voice costs $0.015/min input and $0.02/min output. Vedika Seva Voice is 8.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Vedika Pro Ultra has a 256K context window with ~600ms latency. Vedika Seva Voice offers 30s context at ~300ms. Vedika Pro Ultra has the larger context window.
Best For
Vedika Pro Ultra (Domain Specialist) is optimized for: Kundali matching reports, Multi-chart analysis, Enterprise platforms. Vedika Seva Voice (Voice) works best for: Booking confirmations, Queue updates, Service info.
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 Pro Ultra
response_a = client.chat.completions.create(
model="vedika-pro-ultra",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use Vedika Seva Voice
response_b = client.chat.completions.create(
model="vedika-seva-voice",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Vedika Pro Ultra or Vedika Seva Voice?
Vedika Pro Ultra (Domain Specialist, 120B) offers 256K context. Vedika Seva Voice (Voice, Pipeline) offers Clear diction. Choose Vedika Pro Ultra for Kundali matching reports or Vedika Seva Voice for Booking confirmations.
How much does Vedika Pro Ultra cost vs Vedika Seva Voice?
Vedika Pro Ultra: $0.12/1M input, $0.20/1M output. Vedika Seva Voice: $0.015/min/1M input, $0.02/min/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 Pro Ultra and Vedika Seva Voice 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.