Codestral vs Jamba 1.5 Large

Compare Codestral 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

All Mistral models All AI21 models What is an LLM API? Python Quickstart What is inference?
Feature Codestral Jamba 1.5 Large
CategoryCodeEnterprise
Parameters22B398B (94B active)
Context Window256K256K
Input Price$0.03/1M tokens$0.08/1M tokens
Output Price$0.05/1M tokens$0.14/1M tokens
Latency~200ms~500ms

Choose Codestral when:

  • ✓ API integration code
  • ✓ SDK generation
  • ✓ Code review
Key Strengths:

256K context for code, Strong code generation, Good APIs

Choose Jamba 1.5 Large when:

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

256K context, SSM-Transformer hybrid, Good summarization

Verdict: Codestral vs Jamba 1.5 Large

For cost efficiency, Codestral wins at $0.03/1M input tokens. For speed, Codestral is faster at ~200ms. Codestral 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

Codestral costs $0.03/1M input tokens and $0.05/1M output tokens. Jamba 1.5 Large costs $0.08 input and $0.14 output. Codestral is 2.7x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Codestral has a 256K context window with ~200ms latency. Jamba 1.5 Large offers 256K context at ~500ms. Both have identical context windows.

Best For

Codestral (Code) is optimized for: API integration code, SDK generation, Code review. 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 Codestral
response_a = client.chat.completions.create(
    model="codestral",
    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"}]
)

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, Codestral or Jamba 1.5 Large?

Codestral (Code, 22B) offers 256K context for code. Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. Choose Codestral for API integration code or Jamba 1.5 Large for Full text processing.

How much does Codestral cost vs Jamba 1.5 Large?

Codestral: $0.03/1M input, $0.05/1M 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 Codestral 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.