Vedika Fast vs Jamba 1.5 Large
Compare Vedika Fast and Jamba 1.5 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 | Jamba 1.5 Large |
|---|---|---|
| Category | Domain Specialist | Enterprise |
| Parameters | 8B | 398B (94B active) |
| Context Window | 32K | 256K |
| Input Price | $0.04/1M tokens | $0.08/1M tokens |
| Output Price | $0.06/1M tokens | $0.14/1M tokens |
| Latency | ~120ms | ~500ms |
Choose Vedika Fast when:
- ✓ Voice astrology bots
- ✓ Real-time chatbots
- ✓ Temple kiosks
Sub-200ms latency, Voice-optimized, Real-time chat
Choose Jamba 1.5 Large when:
- ✓ Full text processing
- ✓ Comprehensive reports
- ✓ Long analysis
256K context, SSM-Transformer hybrid, Good summarization
Verdict: Vedika Fast vs Jamba 1.5 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 Jamba 1.5 Large is better for Full text processing. 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. Jamba 1.5 Large costs $0.08 input and $0.14 output. Vedika Fast is 2.0x 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. Jamba 1.5 Large offers 256K context at ~500ms. Jamba 1.5 Large has the larger context window.
Best For
Vedika Fast (Domain Specialist) is optimized for: Voice astrology bots, Real-time chatbots, Temple kiosks. Jamba 1.5 Large (Enterprise) works best for: Full text processing, Comprehensive reports, Long analysis.
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 Jamba 1.5 Large
response_b = client.chat.completions.create(
model="jamba-1-5-large",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Vedika Fast or Jamba 1.5 Large?
Vedika Fast (Domain Specialist, 8B) offers Sub-200ms latency. Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. Choose Vedika Fast for Voice astrology bots or Jamba 1.5 Large for Full text processing.
How much does Vedika Fast cost vs Jamba 1.5 Large?
Vedika Fast: $0.04/1M input, $0.06/1M output. Jamba 1.5 Large: $0.08/1M input, $0.14/1M 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 Jamba 1.5 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.