Jamba 1.5 Large vs CodeGemma 7B

Compare Jamba 1.5 Large and CodeGemma 7B: 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 CodeGemma 7B
CategoryEnterpriseCode
Parameters398B (94B active)7B
Context Window256K8K
Input Price$0.08/1M tokens$0.008/1M tokens
Output Price$0.14/1M tokens$0.015/1M tokens
Latency~500ms~60ms

Choose Jamba 1.5 Large when:

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

256K context, SSM-Transformer hybrid, Good summarization

Choose CodeGemma 7B when:

  • ✓ Code completion
  • ✓ Simple generation
  • ✓ Editor plugins
Key Strengths:

Compact, Fast code completion, Open weights

Verdict: Jamba 1.5 Large vs CodeGemma 7B

For cost efficiency, CodeGemma 7B wins at $0.008/1M input tokens. For speed, Jamba 1.5 Large is faster at ~500ms. Jamba 1.5 Large excels at Full text processing while CodeGemma 7B is better for Code completion. 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. CodeGemma 7B costs $0.008 input and $0.015 output. CodeGemma 7B is 10.0x 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. CodeGemma 7B offers 8K context at ~60ms. 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. CodeGemma 7B (Code) works best for: Code completion, Simple generation, Editor plugins.

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 CodeGemma 7B
response_b = client.chat.completions.create(
    model="codegemma-7b",
    messages=[{"role": "user", "content": "Your question here"}]
)

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Frequently Asked Questions

Which is better, Jamba 1.5 Large or CodeGemma 7B?

Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. CodeGemma 7B (Code, 7B) offers Compact. Choose Jamba 1.5 Large for Full text processing or CodeGemma 7B for Code completion.

How much does Jamba 1.5 Large cost vs CodeGemma 7B?

Jamba 1.5 Large: $0.08/1M input, $0.14/1M output. CodeGemma 7B: $0.008/1M input, $0.015/1M 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 CodeGemma 7B 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.