Vedika Fast vs Llama 3.2 1B
Compare Vedika Fast and Llama 3.2 1B: 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 | Llama 3.2 1B |
|---|---|---|
| Category | Domain Specialist | Compact |
| Parameters | 8B | 1B |
| Context Window | 32K | 128K |
| Input Price | $0.04/1M tokens | $0.004/1M tokens |
| Output Price | $0.06/1M tokens | $0.008/1M tokens |
| Latency | ~120ms | ~25ms |
Choose Vedika Fast when:
- ✓ Voice astrology bots
- ✓ Real-time chatbots
- ✓ Temple kiosks
Sub-200ms latency, Voice-optimized, Real-time chat
Choose Llama 3.2 1B when:
- ✓ Intent detection
- ✓ Routing
- ✓ Edge classification
Smallest footprint, Fastest inference, Classification
Verdict: Vedika Fast vs Llama 3.2 1B
For cost efficiency, Llama 3.2 1B wins at $0.004/1M input tokens. For speed, Vedika Fast is faster at ~120ms. Vedika Fast excels at Voice astrology bots while Llama 3.2 1B is better for Intent detection. 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. Llama 3.2 1B costs $0.004 input and $0.008 output. Llama 3.2 1B is 10.0x 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. Llama 3.2 1B offers 128K context at ~25ms. Llama 3.2 1B has the larger context window.
Best For
Vedika Fast (Domain Specialist) is optimized for: Voice astrology bots, Real-time chatbots, Temple kiosks. Llama 3.2 1B (Compact) works best for: Intent detection, Routing, Edge classification.
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 Llama 3.2 1B
response_b = client.chat.completions.create(
model="llama-3-2-1b",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Vedika Fast or Llama 3.2 1B?
Vedika Fast (Domain Specialist, 8B) offers Sub-200ms latency. Llama 3.2 1B (Compact, 1B) offers Smallest footprint. Choose Vedika Fast for Voice astrology bots or Llama 3.2 1B for Intent detection.
How much does Vedika Fast cost vs Llama 3.2 1B?
Vedika Fast: $0.04/1M input, $0.06/1M output. Llama 3.2 1B: $0.004/1M input, $0.008/1M 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 Llama 3.2 1B 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.