Vedika Vision vs Llama 3.2 11B Vision

Compare Vedika Vision and Llama 3.2 11B 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

All Meta models What is an LLM API? Python Quickstart What is inference?
Feature Vedika Vision Llama 3.2 11B Vision
CategoryVisionVision
Parameters26B11B
Context Window32K128K
Input Price$0.08/1M tokens$0.02/1M tokens
Output Price$0.12/1M tokens$0.04/1M tokens
Latency~500ms~200ms

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 11B Vision when:

  • ✓ Image classification
  • ✓ OCR
  • ✓ Simple visual Q&A
Key Strengths:

Low cost vision, Fast, Compact

Verdict: Vedika Vision vs Llama 3.2 11B Vision

For cost efficiency, Llama 3.2 11B Vision wins at $0.02/1M input tokens. For speed, Llama 3.2 11B Vision is faster at ~200ms. Vedika Vision excels at Chart image analysis while Llama 3.2 11B Vision is better for Image classification. 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 11B Vision costs $0.02 input and $0.04 output. Llama 3.2 11B Vision is 4.0x 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 11B Vision offers 128K context at ~200ms. Llama 3.2 11B Vision 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 11B Vision (Vision) works best for: Image classification, OCR, Simple 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 Vision
response_a = client.chat.completions.create(
    model="vedika-vision",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use Llama 3.2 11B Vision
response_b = client.chat.completions.create(
    model="llama-3-2-11b-vision",
    messages=[{"role": "user", "content": "Your question here"}]
)

Start Building with XALEN

200+ AI models. One API. Pay-as-you-go.

Get API Key Try in Playground

Frequently Asked Questions

Which is better, Vedika Vision or Llama 3.2 11B Vision?

Vedika Vision (Vision, 26B) offers Chart image analysis. Llama 3.2 11B Vision (Vision, 11B) offers Low cost vision. Choose Vedika Vision for Chart image analysis or Llama 3.2 11B Vision for Image classification.

How much does Vedika Vision cost vs Llama 3.2 11B Vision?

Vedika Vision: $0.08/1M input, $0.12/1M output. Llama 3.2 11B Vision: $0.02/1M input, $0.04/1M 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 11B Vision by changing the model parameter. No code changes needed.

Related Comparisons

Vedika Vision vs Llama 3.2 90B Vision Vedika Vision vs Qwen 2.5 VL 72B Vedika Vision vs Qwen 2.5 VL 7B Vedika Vision vs Pixtral Large Vedika Vision vs Pixtral 12B Vedika Vision vs InternVL 2.5 78B

Last updated: 2026-05-21. Pricing and specifications may change. Check pricing page for latest rates.