Jamba 1.5 Large vs DeepSeek V2.5

Compare Jamba 1.5 Large and DeepSeek V2.5: 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 DeepSeek V2.5
CategoryEnterpriseOpen Source
Parameters398B (94B active)236B (21B active)
Context Window256K128K
Input Price$0.08/1M tokens$0.04/1M tokens
Output Price$0.14/1M tokens$0.07/1M tokens
Latency~500ms~350ms

Choose Jamba 1.5 Large when:

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

256K context, SSM-Transformer hybrid, Good summarization

Choose DeepSeek V2.5 when:

  • ✓ General purpose
  • ✓ Code generation
  • ✓ Legacy apps
Key Strengths:

Proven model, MoE efficient, Good coding

Verdict: Jamba 1.5 Large vs DeepSeek V2.5

For cost efficiency, DeepSeek V2.5 wins at $0.04/1M input tokens. For speed, DeepSeek V2.5 is faster at ~350ms. Jamba 1.5 Large excels at Full text processing while DeepSeek V2.5 is better for General purpose. 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. DeepSeek V2.5 costs $0.04 input and $0.07 output. DeepSeek V2.5 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. DeepSeek V2.5 offers 128K context at ~350ms. 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. DeepSeek V2.5 (Open Source) works best for: General purpose, Code generation, Legacy apps.

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 DeepSeek V2.5
response_b = client.chat.completions.create(
    model="deepseek-v2-5",
    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, Jamba 1.5 Large or DeepSeek V2.5?

Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. DeepSeek V2.5 (Open Source, 236B (21B active)) offers Proven model. Choose Jamba 1.5 Large for Full text processing or DeepSeek V2.5 for General purpose.

How much does Jamba 1.5 Large cost vs DeepSeek V2.5?

Jamba 1.5 Large: $0.08/1M input, $0.14/1M output. DeepSeek V2.5: $0.04/1M input, $0.07/1M 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 DeepSeek V2.5 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.