Yi Large vs Jamba 1.5 Large

Compare Yi Large 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 Yi Large Jamba 1.5 Large
CategoryOpen SourceEnterprise
Parameters300B398B (94B active)
Context Window200K256K
Input Price$0.06/1M tokens$0.08/1M tokens
Output Price$0.12/1M tokens$0.14/1M tokens
Latency~450ms~500ms

Choose Yi Large when:

  • ✓ Long document analysis
  • ✓ Research
  • ✓ Complex tasks
Key Strengths:

200K context, Strong analysis, Good reasoning

Choose Jamba 1.5 Large when:

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

256K context, SSM-Transformer hybrid, Good summarization

Verdict: Yi Large vs Jamba 1.5 Large

For cost efficiency, Yi Large wins at $0.06/1M input tokens. For speed, Yi Large is faster at ~450ms. Yi Large excels at Long document analysis 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

Yi Large costs $0.06/1M input tokens and $0.12/1M output tokens. Jamba 1.5 Large costs $0.08 input and $0.14 output. Yi Large is 1.3x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Yi Large has a 200K context window with ~450ms latency. Jamba 1.5 Large offers 256K context at ~500ms. Jamba 1.5 Large has the larger context window.

Best For

Yi Large (Open Source) is optimized for: Long document analysis, Research, Complex tasks. 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 Yi Large
response_a = client.chat.completions.create(
    model="yi-large",
    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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Get API Key Try in Playground

Frequently Asked Questions

Which is better, Yi Large or Jamba 1.5 Large?

Yi Large (Open Source, 300B) offers 200K context. Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. Choose Yi Large for Long document analysis or Jamba 1.5 Large for Full text processing.

How much does Yi Large cost vs Jamba 1.5 Large?

Yi Large: $0.06/1M input, $0.12/1M 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 Yi Large 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.