Vedika Seva Voice vs Llama 3.2 90B Vision

Compare Vedika Seva Voice and Llama 3.2 90B Vision: pricing, performance, context window, latency, and best use cases. Side-by-side comparison on XALEN.

Updated 2026-05-21 · By Abhishek Raj · Our methodology

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Feature Vedika Seva Voice Llama 3.2 90B Vision
CategoryVoiceVision
ParametersPipeline90B
Context Window30s128K
Input Price$0.015/min/1M tokens$0.06/1M tokens
Output Price$0.02/min/1M tokens$0.10/1M tokens
Latency~300ms~500ms

Choose Vedika Seva Voice when:

  • ✓ Booking confirmations
  • ✓ Queue updates
  • ✓ Service info
Key Strengths:

Clear diction, Service-oriented, Fast response

Choose Llama 3.2 90B Vision when:

  • ✓ Chart image analysis
  • ✓ Document scanning
  • ✓ Visual Q&A
Key Strengths:

Vision + language, Open weights, Good reasoning

Verdict: Vedika Seva Voice vs Llama 3.2 90B Vision

For cost efficiency, Vedika Seva Voice wins at $0.015/min/1M input tokens. For speed, Vedika Seva Voice is faster at ~300ms. Vedika Seva Voice excels at Booking confirmations while Llama 3.2 90B Vision is better for Chart image 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 Seva Voice costs $0.015/min/1M input tokens and $0.02/min/1M output tokens. Llama 3.2 90B Vision costs $0.06 input and $0.10 output. Vedika Seva Voice is 4.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Vedika Seva Voice has a 30s context window with ~300ms latency. Llama 3.2 90B Vision offers 128K context at ~500ms. Llama 3.2 90B Vision has the larger context window.

Best For

Vedika Seva Voice (Voice) is optimized for: Booking confirmations, Queue updates, Service info. Llama 3.2 90B Vision (Vision) works best for: Chart image analysis, Document scanning, Visual Q&A.

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 Seva Voice
response_a = client.chat.completions.create(
    model="vedika-seva-voice",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use Llama 3.2 90B Vision
response_b = client.chat.completions.create(
    model="llama-3-2-90b-vision",
    messages=[{"role": "user", "content": "Your question here"}]
)

Start Building with XALEN

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Get API Key Try in Playground

Frequently Asked Questions

Which is better, Vedika Seva Voice or Llama 3.2 90B Vision?

Vedika Seva Voice (Voice, Pipeline) offers Clear diction. Llama 3.2 90B Vision (Vision, 90B) offers Vision + language. Choose Vedika Seva Voice for Booking confirmations or Llama 3.2 90B Vision for Chart image analysis.

How much does Vedika Seva Voice cost vs Llama 3.2 90B Vision?

Vedika Seva Voice: $0.015/min/1M input, $0.02/min/1M output. Llama 3.2 90B Vision: $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 Seva Voice and Llama 3.2 90B Vision 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.