Vedika Vision vs Llama 3.2 1B

Compare Vedika Vision 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

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Feature Vedika Vision Llama 3.2 1B
CategoryVisionCompact
Parameters26B1B
Context Window32K128K
Input Price$0.08/1M tokens$0.004/1M tokens
Output Price$0.12/1M tokens$0.008/1M tokens
Latency~500ms~25ms

Choose Vedika Vision when:

  • ✓ Chart image analysis
  • ✓ Temple photo description
  • ✓ Vastu photo analysis
Key Strengths:

Chart image analysis, Yantra recognition, Sacred geometry

Choose Llama 3.2 1B when:

  • ✓ Intent detection
  • ✓ Routing
  • ✓ Edge classification
Key Strengths:

Smallest footprint, Fastest inference, Classification

Verdict: Vedika Vision vs Llama 3.2 1B

For cost efficiency, Llama 3.2 1B wins at $0.004/1M input tokens. For speed, Llama 3.2 1B is faster at ~25ms. Vedika Vision excels at Chart image analysis 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 Vision costs $0.08/1M input tokens and $0.12/1M output tokens. Llama 3.2 1B costs $0.004 input and $0.008 output. Llama 3.2 1B is 20.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Vedika Vision has a 32K context window with ~500ms latency. Llama 3.2 1B offers 128K context at ~25ms. Llama 3.2 1B has the larger context window.

Best For

Vedika Vision (Vision) is optimized for: Chart image analysis, Temple photo description, Vastu photo analysis. 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 Vision
response_a = client.chat.completions.create(
    model="vedika-vision",
    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"}]
)

Start Building with XALEN

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Get API Key Try in Playground

Frequently Asked Questions

Which is better, Vedika Vision or Llama 3.2 1B?

Vedika Vision (Vision, 26B) offers Chart image analysis. Llama 3.2 1B (Compact, 1B) offers Smallest footprint. Choose Vedika Vision for Chart image analysis or Llama 3.2 1B for Intent detection.

How much does Vedika Vision cost vs Llama 3.2 1B?

Vedika Vision: $0.08/1M input, $0.12/1M 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 Vision 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.