Qwen 2.5 72B Turbo vs Jamba 1.5 Large

Compare Qwen 2.5 72B Turbo 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 Qwen 2.5 72B Turbo Jamba 1.5 Large
CategoryOpen SourceEnterprise
Parameters72B398B (94B active)
Context Window128K256K
Input Price$0.04/1M tokens$0.08/1M tokens
Output Price$0.08/1M tokens$0.14/1M tokens
Latency~300ms~500ms

Choose Qwen 2.5 72B Turbo when:

  • ✓ Pan-India apps
  • ✓ Multilingual Q&A
  • ✓ Content generation
Key Strengths:

Strong Asian languages, Good reasoning, Fast inference

Choose Jamba 1.5 Large when:

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

256K context, SSM-Transformer hybrid, Good summarization

Verdict: Qwen 2.5 72B Turbo vs Jamba 1.5 Large

For cost efficiency, Qwen 2.5 72B Turbo wins at $0.04/1M input tokens. For speed, Qwen 2.5 72B Turbo is faster at ~300ms. Qwen 2.5 72B Turbo excels at Pan-India apps 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

Qwen 2.5 72B Turbo costs $0.04/1M input tokens and $0.08/1M output tokens. Jamba 1.5 Large costs $0.08 input and $0.14 output. Qwen 2.5 72B Turbo is 2.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Qwen 2.5 72B Turbo has a 128K context window with ~300ms latency. Jamba 1.5 Large offers 256K context at ~500ms. Jamba 1.5 Large has the larger context window.

Best For

Qwen 2.5 72B Turbo (Open Source) is optimized for: Pan-India apps, Multilingual Q&A, Content generation. 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 Qwen 2.5 72B Turbo
response_a = client.chat.completions.create(
    model="qwen-2-5-72b-turbo",
    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

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Get API Key Try in Playground

Frequently Asked Questions

Which is better, Qwen 2.5 72B Turbo or Jamba 1.5 Large?

Qwen 2.5 72B Turbo (Open Source, 72B) offers Strong Asian languages. Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. Choose Qwen 2.5 72B Turbo for Pan-India apps or Jamba 1.5 Large for Full text processing.

How much does Qwen 2.5 72B Turbo cost vs Jamba 1.5 Large?

Qwen 2.5 72B Turbo: $0.04/1M input, $0.08/1M 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 Qwen 2.5 72B Turbo 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.