Jamba 1.5 Large vs Code Llama 70B

Compare Jamba 1.5 Large and Code Llama 70B: 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 Jamba 1.5 Large Code Llama 70B
CategoryEnterpriseCode
Parameters398B (94B active)70B
Context Window256K100K
Input Price$0.08/1M tokens$0.04/1M tokens
Output Price$0.14/1M tokens$0.06/1M tokens
Latency~500ms~300ms

Choose Jamba 1.5 Large when:

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

256K context, SSM-Transformer hybrid, Good summarization

Choose Code Llama 70B when:

  • ✓ Large codebases
  • ✓ Code review
  • ✓ Refactoring
Key Strengths:

100K context, Strong coding, Fill-in-middle

Verdict: Jamba 1.5 Large vs Code Llama 70B

For cost efficiency, Code Llama 70B wins at $0.04/1M input tokens. For speed, Code Llama 70B is faster at ~300ms. Jamba 1.5 Large excels at Full text processing while Code Llama 70B is better for Large codebases. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.

Detailed Analysis

Pricing Comparison

Jamba 1.5 Large costs $0.08/1M input tokens and $0.14/1M output tokens. Code Llama 70B costs $0.04 input and $0.06 output. Code Llama 70B is 2.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Jamba 1.5 Large has a 256K context window with ~500ms latency. Code Llama 70B offers 100K context at ~300ms. Jamba 1.5 Large has the larger context window.

Best For

Jamba 1.5 Large (Enterprise) is optimized for: Full text processing, Comprehensive reports, Long analysis. Code Llama 70B (Code) works best for: Large codebases, Code review, Refactoring.

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

# Use Code Llama 70B
response_b = client.chat.completions.create(
    model="codellama-70b",
    messages=[{"role": "user", "content": "Your question here"}]
)

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Get API Key Try in Playground

Frequently Asked Questions

Which is better, Jamba 1.5 Large or Code Llama 70B?

Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. Code Llama 70B (Code, 70B) offers 100K context. Choose Jamba 1.5 Large for Full text processing or Code Llama 70B for Large codebases.

How much does Jamba 1.5 Large cost vs Code Llama 70B?

Jamba 1.5 Large: $0.08/1M input, $0.14/1M output. Code Llama 70B: $0.04/1M input, $0.06/1M 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 Jamba 1.5 Large and Code Llama 70B 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.