Vedika Pro Ultra vs Command R
Compare Vedika Pro Ultra and Command R: 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 | Command R |
|---|---|---|
| Category | Domain Specialist | Open Source |
| Parameters | 120B | 35B |
| Context Window | 256K | 128K |
| Input Price | $0.12/1M tokens | $0.03/1M tokens |
| Output Price | $0.20/1M tokens | $0.06/1M tokens |
| Latency | ~600ms | ~250ms |
Choose Vedika Pro Ultra when:
- ✓ Kundali matching reports
- ✓ Multi-chart analysis
- ✓ Enterprise platforms
256K context, Deep yoga reasoning, Multi-system comparison
Choose Command R when:
- ✓ RAG applications
- ✓ Q&A systems
- ✓ Content generation
Good RAG, Cost-efficient, 128K context
Verdict: Vedika Pro Ultra vs Command R
For cost efficiency, Command R wins at $0.03/1M input tokens. For speed, Command R is faster at ~250ms. Vedika Pro Ultra excels at Kundali matching reports while Command R is better for RAG applications. 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. Command R costs $0.03 input and $0.06 output. Command R is 4.0x 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. Command R offers 128K context at ~250ms. 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. Command R (Open Source) works best for: RAG applications, Q&A systems, Content generation.
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 Command R
response_b = client.chat.completions.create(
model="command-r",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Vedika Pro Ultra or Command R?
Vedika Pro Ultra (Domain Specialist, 120B) offers 256K context. Command R (Open Source, 35B) offers Good RAG. Choose Vedika Pro Ultra for Kundali matching reports or Command R for RAG applications.
How much does Vedika Pro Ultra cost vs Command R?
Vedika Pro Ultra: $0.12/1M input, $0.20/1M output. Command R: $0.03/1M input, $0.06/1M 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 Command R 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.