Vedika Fast vs Arctic Large
Compare Vedika Fast and Arctic 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 Fast | Arctic Large |
|---|---|---|
| Category | Domain Specialist | Enterprise |
| Parameters | 8B | 480B (17B active) |
| Context Window | 32K | 128K |
| Input Price | $0.04/1M tokens | $0.06/1M tokens |
| Output Price | $0.06/1M tokens | $0.10/1M tokens |
| Latency | ~120ms | ~400ms |
Choose Vedika Fast when:
- ✓ Voice astrology bots
- ✓ Real-time chatbots
- ✓ Temple kiosks
Sub-200ms latency, Voice-optimized, Real-time chat
Choose Arctic Large when:
- ✓ Data analysis
- ✓ SQL generation
- ✓ Business intelligence
Strong SQL, Data analysis, Enterprise features
Verdict: Vedika Fast vs Arctic Large
For cost efficiency, Vedika Fast wins at $0.04/1M input tokens. For speed, Vedika Fast is faster at ~120ms. Vedika Fast excels at Voice astrology bots while Arctic Large is better for Data 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 Fast costs $0.04/1M input tokens and $0.06/1M output tokens. Arctic Large costs $0.06 input and $0.10 output. Vedika Fast is 1.5x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Vedika Fast has a 32K context window with ~120ms latency. Arctic Large offers 128K context at ~400ms. Arctic Large has the larger context window.
Best For
Vedika Fast (Domain Specialist) is optimized for: Voice astrology bots, Real-time chatbots, Temple kiosks. Arctic Large (Enterprise) works best for: Data analysis, SQL generation, Business intelligence.
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 Fast
response_a = client.chat.completions.create(
model="vedika-fast",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use Arctic Large
response_b = client.chat.completions.create(
model="arctic-large",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Vedika Fast or Arctic Large?
Vedika Fast (Domain Specialist, 8B) offers Sub-200ms latency. Arctic Large (Enterprise, 480B (17B active)) offers Strong SQL. Choose Vedika Fast for Voice astrology bots or Arctic Large for Data analysis.
How much does Vedika Fast cost vs Arctic Large?
Vedika Fast: $0.04/1M input, $0.06/1M output. Arctic Large: $0.06/1M 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 Fast and Arctic 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.