Vedika Code vs Llama 3.1 405B

Compare Vedika Code and Llama 3.1 405B: 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 Code Llama 3.1 405B
CategoryCodeOpen Source
Parameters33B405B
Context Window64K128K
Input Price$0.04/1M tokens$0.08/1M tokens
Output Price$0.06/1M tokens$0.14/1M tokens
Latency~250ms~600ms

Choose Vedika Code when:

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

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

Choose Llama 3.1 405B when:

  • ✓ Premium tasks
  • ✓ Research
  • ✓ Fine-tuning base
Key Strengths:

Largest open model, Highest open-source quality

Verdict: Vedika Code vs Llama 3.1 405B

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 Llama 3.1 405B is better for Premium tasks. 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. Llama 3.1 405B costs $0.08 input and $0.14 output. Vedika Code is 2.0x 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. Llama 3.1 405B offers 128K context at ~600ms. Llama 3.1 405B has the larger context window.

Best For

Vedika Code (Code) is optimized for: API integration code, Temple systems, SDK examples. Llama 3.1 405B (Open Source) works best for: Premium tasks, Research, Fine-tuning base.

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 Llama 3.1 405B
response_b = client.chat.completions.create(
    model="llama-3-1-405b",
    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 Code or Llama 3.1 405B?

Vedika Code (Code, 33B) offers Faith-tech code patterns. Llama 3.1 405B (Open Source, 405B) offers Largest open model. Choose Vedika Code for API integration code or Llama 3.1 405B for Premium tasks.

How much does Vedika Code cost vs Llama 3.1 405B?

Vedika Code: $0.04/1M input, $0.06/1M output. Llama 3.1 405B: $0.08/1M input, $0.14/1M 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 Llama 3.1 405B 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.