Vedika Vision vs DeepSeek V3

Compare Vedika Vision and DeepSeek V3: 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 DeepSeek V3
CategoryVisionOpen Source
Parameters26B671B (37B active)
Context Window32K128K
Input Price$0.08/1M tokens$0.05/1M tokens
Output Price$0.12/1M tokens$0.09/1M tokens
Latency~500ms~400ms

Choose Vedika Vision when:

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

Chart image analysis, Yantra recognition, Sacred geometry

Choose DeepSeek V3 when:

  • ✓ API response generation
  • ✓ High-volume processing
  • ✓ Code
Key Strengths:

MoE efficiency, Strong coding, Good structured output

Verdict: Vedika Vision vs DeepSeek V3

For cost efficiency, DeepSeek V3 wins at $0.05/1M input tokens. For speed, DeepSeek V3 is faster at ~400ms. Vedika Vision excels at Chart image analysis while DeepSeek V3 is better for API response generation. 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. DeepSeek V3 costs $0.05 input and $0.09 output. DeepSeek V3 is 1.6x 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. DeepSeek V3 offers 128K context at ~400ms. DeepSeek V3 has the larger context window.

Best For

Vedika Vision (Vision) is optimized for: Chart image analysis, Temple photo description, Vastu photo analysis. DeepSeek V3 (Open Source) works best for: API response generation, High-volume processing, Code.

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 DeepSeek V3
response_b = client.chat.completions.create(
    model="deepseek-v3",
    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 DeepSeek V3?

Vedika Vision (Vision, 26B) offers Chart image analysis. DeepSeek V3 (Open Source, 671B (37B active)) offers MoE efficiency. Choose Vedika Vision for Chart image analysis or DeepSeek V3 for API response generation.

How much does Vedika Vision cost vs DeepSeek V3?

Vedika Vision: $0.08/1M input, $0.12/1M output. DeepSeek V3: $0.05/1M input, $0.09/1M 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 DeepSeek V3 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.