Vedika Pro Ultra vs Yi Large
Compare Vedika Pro Ultra and Yi Large: 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 | Yi Large |
|---|---|---|
| Category | Domain Specialist | Open Source |
| Parameters | 120B | 300B |
| Context Window | 256K | 200K |
| Input Price | $0.12/1M tokens | $0.06/1M tokens |
| Output Price | $0.20/1M tokens | $0.12/1M tokens |
| Latency | ~600ms | ~450ms |
Choose Vedika Pro Ultra when:
- ✓ Kundali matching reports
- ✓ Multi-chart analysis
- ✓ Enterprise platforms
256K context, Deep yoga reasoning, Multi-system comparison
Choose Yi Large when:
- ✓ Long document analysis
- ✓ Research
- ✓ Complex tasks
200K context, Strong analysis, Good reasoning
Verdict: Vedika Pro Ultra vs Yi Large
For cost efficiency, Yi Large wins at $0.06/1M input tokens. For speed, Yi Large is faster at ~450ms. Vedika Pro Ultra excels at Kundali matching reports while Yi Large is better for Long document analysis. 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. Yi Large costs $0.06 input and $0.12 output. Yi Large is 2.0x 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. Yi Large offers 200K context at ~450ms. 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. Yi Large (Open Source) works best for: Long document analysis, Research, Complex tasks.
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 Yi Large
response_b = client.chat.completions.create(
model="yi-large",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Vedika Pro Ultra or Yi Large?
Vedika Pro Ultra (Domain Specialist, 120B) offers 256K context. Yi Large (Open Source, 300B) offers 200K context. Choose Vedika Pro Ultra for Kundali matching reports or Yi Large for Long document analysis.
How much does Vedika Pro Ultra cost vs Yi Large?
Vedika Pro Ultra: $0.12/1M input, $0.20/1M output. Yi Large: $0.06/1M input, $0.12/1M 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 Yi Large 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.