Vedika Pro Ultra vs Qwen 2.5 72B Turbo
Compare Vedika Pro Ultra and Qwen 2.5 72B Turbo: 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 | Qwen 2.5 72B Turbo |
|---|---|---|
| Category | Domain Specialist | Open Source |
| Parameters | 120B | 72B |
| Context Window | 256K | 128K |
| Input Price | $0.12/1M tokens | $0.04/1M tokens |
| Output Price | $0.20/1M tokens | $0.08/1M 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 Qwen 2.5 72B Turbo when:
- ✓ Pan-India apps
- ✓ Multilingual Q&A
- ✓ Content generation
Strong Asian languages, Good reasoning, Fast inference
Verdict: Vedika Pro Ultra vs Qwen 2.5 72B Turbo
For cost efficiency, Qwen 2.5 72B Turbo wins at $0.04/1M input tokens. For speed, Qwen 2.5 72B Turbo is faster at ~300ms. Vedika Pro Ultra excels at Kundali matching reports while Qwen 2.5 72B Turbo is better for Pan-India apps. 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. Qwen 2.5 72B Turbo costs $0.04 input and $0.08 output. Qwen 2.5 72B Turbo is 3.0x 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. Qwen 2.5 72B Turbo offers 128K 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. Qwen 2.5 72B Turbo (Open Source) works best for: Pan-India apps, Multilingual Q&A, 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 Qwen 2.5 72B Turbo
response_b = client.chat.completions.create(
model="qwen-2-5-72b-turbo",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Vedika Pro Ultra or Qwen 2.5 72B Turbo?
Vedika Pro Ultra (Domain Specialist, 120B) offers 256K context. Qwen 2.5 72B Turbo (Open Source, 72B) offers Strong Asian languages. Choose Vedika Pro Ultra for Kundali matching reports or Qwen 2.5 72B Turbo for Pan-India apps.
How much does Vedika Pro Ultra cost vs Qwen 2.5 72B Turbo?
Vedika Pro Ultra: $0.12/1M input, $0.20/1M output. Qwen 2.5 72B Turbo: $0.04/1M input, $0.08/1M 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 Qwen 2.5 72B Turbo 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.