Vedika Code vs Yi Large

Compare Vedika Code and Yi 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 Yi Large
CategoryCodeOpen Source
Parameters33B300B
Context Window64K200K
Input Price$0.04/1M tokens$0.06/1M tokens
Output Price$0.06/1M tokens$0.12/1M tokens
Latency~250ms~450ms

Choose Vedika Code when:

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

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

Choose Yi Large when:

  • ✓ Long document analysis
  • ✓ Research
  • ✓ Complex tasks
Key Strengths:

200K context, Strong analysis, Good reasoning

Verdict: Vedika Code vs Yi 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 Yi Large is better for Long document 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. Yi Large costs $0.06 input and $0.12 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. Yi Large offers 200K context at ~450ms. Yi Large has the larger context window.

Best For

Vedika Code (Code) is optimized for: API integration code, Temple systems, SDK examples. Yi Large (Open Source) works best for: Long document analysis, Research, Complex tasks.

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

Start Building with XALEN

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

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Frequently Asked Questions

Which is better, Vedika Code or Yi Large?

Vedika Code (Code, 33B) offers Faith-tech code patterns. Yi Large (Open Source, 300B) offers 200K context. Choose Vedika Code for API integration code or Yi Large for Long document analysis.

How much does Vedika Code cost vs Yi Large?

Vedika Code: $0.04/1M input, $0.06/1M output. Yi Large: $0.06/1M input, $0.12/1M 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 Yi 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.