Vedika Code vs Jamba 1.5 Large

Compare Vedika Code and Jamba 1.5 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 Jamba 1.5 Large
CategoryCodeEnterprise
Parameters33B398B (94B active)
Context Window64K256K
Input Price$0.04/1M tokens$0.08/1M tokens
Output Price$0.06/1M tokens$0.14/1M tokens
Latency~250ms~500ms

Choose Vedika Code when:

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

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

Choose Jamba 1.5 Large when:

  • ✓ Full text processing
  • ✓ Comprehensive reports
  • ✓ Long analysis
Key Strengths:

256K context, SSM-Transformer hybrid, Good summarization

Verdict: Vedika Code vs Jamba 1.5 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 Jamba 1.5 Large is better for Full text processing. 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. Jamba 1.5 Large 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. Jamba 1.5 Large offers 256K context at ~500ms. Jamba 1.5 Large has the larger context window.

Best For

Vedika Code (Code) is optimized for: API integration code, Temple systems, SDK examples. Jamba 1.5 Large (Enterprise) works best for: Full text processing, Comprehensive reports, Long analysis.

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 Jamba 1.5 Large
response_b = client.chat.completions.create(
    model="jamba-1-5-large",
    messages=[{"role": "user", "content": "Your question here"}]
)

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Frequently Asked Questions

Which is better, Vedika Code or Jamba 1.5 Large?

Vedika Code (Code, 33B) offers Faith-tech code patterns. Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. Choose Vedika Code for API integration code or Jamba 1.5 Large for Full text processing.

How much does Vedika Code cost vs Jamba 1.5 Large?

Vedika Code: $0.04/1M input, $0.06/1M output. Jamba 1.5 Large: $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 Jamba 1.5 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.