Vedika Code vs Arctic Large

Compare Vedika Code and Arctic Large: 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 Code Arctic Large
CategoryCodeEnterprise
Parameters33B480B (17B active)
Context Window64K128K
Input Price$0.04/1M tokens$0.06/1M tokens
Output Price$0.06/1M tokens$0.10/1M tokens
Latency~250ms~400ms

Choose Vedika Code when:

  • ✓ API integration code
  • ✓ Temple systems
  • ✓ SDK examples
Key Strengths:

Faith-tech code patterns, API integration code, Temple system boilerplate

Choose Arctic Large when:

  • ✓ Data analysis
  • ✓ SQL generation
  • ✓ Business intelligence
Key Strengths:

Strong SQL, Data analysis, Enterprise features

Verdict: Vedika Code vs Arctic Large

For cost efficiency, Vedika Code wins at $0.04/1M input tokens. For speed, Vedika Code is faster at ~250ms. Vedika Code excels at API integration code while Arctic Large is better for Data 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 Code costs $0.04/1M input tokens and $0.06/1M output tokens. Arctic Large costs $0.06 input and $0.10 output. Vedika Code is 1.5x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Vedika Code has a 64K context window with ~250ms latency. Arctic Large offers 128K context at ~400ms. Arctic Large has the larger context window.

Best For

Vedika Code (Code) is optimized for: API integration code, Temple systems, SDK examples. Arctic Large (Enterprise) works best for: Data analysis, SQL generation, Business intelligence.

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

# Use Arctic Large
response_b = client.chat.completions.create(
    model="arctic-large",
    messages=[{"role": "user", "content": "Your question here"}]
)

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Frequently Asked Questions

Which is better, Vedika Code or Arctic Large?

Vedika Code (Code, 33B) offers Faith-tech code patterns. Arctic Large (Enterprise, 480B (17B active)) offers Strong SQL. Choose Vedika Code for API integration code or Arctic Large for Data analysis.

How much does Vedika Code cost vs Arctic Large?

Vedika Code: $0.04/1M input, $0.06/1M output. Arctic Large: $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 Code and Arctic Large 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.