Vedika Pro Ultra vs Command A
Compare Vedika Pro Ultra and Command A: 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 A |
|---|---|---|
| Category | Domain Specialist | Enterprise |
| Parameters | 120B | 111B (37B active) |
| Context Window | 256K | 256K |
| Input Price | $0.12/1M tokens | $0.025/1M tokens |
| Output Price | $0.20/1M tokens | $0.10/1M 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 Command A when:
- ✓ Enterprise RAG
- ✓ Document Q&A
- ✓ Agentic workflows
Strong RAG, Agentic, 256K context
Verdict: Vedika Pro Ultra vs Command A
For cost efficiency, Command A wins at $0.025/1M input tokens. For speed, Command A is faster at ~300ms. Vedika Pro Ultra excels at Kundali matching reports while Command A is better for Enterprise RAG. 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 A costs $0.025 input and $0.10 output. Command A is 4.8x 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 A offers 256K context at ~300ms. Both have identical context windows.
Best For
Vedika Pro Ultra (Domain Specialist) is optimized for: Kundali matching reports, Multi-chart analysis, Enterprise platforms. Command A (Enterprise) works best for: Enterprise RAG, Document Q&A, Agentic workflows.
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 A
response_b = client.chat.completions.create(
model="command-a",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Vedika Pro Ultra or Command A?
Vedika Pro Ultra (Domain Specialist, 120B) offers 256K context. Command A (Enterprise, 111B (37B active)) offers Strong RAG. Choose Vedika Pro Ultra for Kundali matching reports or Command A for Enterprise RAG.
How much does Vedika Pro Ultra cost vs Command A?
Vedika Pro Ultra: $0.12/1M input, $0.20/1M output. Command A: $0.025/1M input, $0.10/1M 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 A 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.