Jamba 1.5 Large vs DeepSeek R1 Distill 32B

Compare Jamba 1.5 Large and DeepSeek R1 Distill 32B: 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 R1 Distill 32B
CategoryEnterpriseReasoning
Parameters398B (94B active)32B
Context Window256K128K
Input Price$0.08/1M tokens$0.03/1M tokens
Output Price$0.14/1M tokens$0.06/1M tokens
Latency~500ms~250ms

Choose Jamba 1.5 Large when:

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

256K context, SSM-Transformer hybrid, Good summarization

Choose DeepSeek R1 Distill 32B when:

  • ✓ Production reasoning
  • ✓ Analysis
  • ✓ Structured tasks
Key Strengths:

Good reasoning, Moderate cost, Fast

Verdict: Jamba 1.5 Large vs DeepSeek R1 Distill 32B

For cost efficiency, DeepSeek R1 Distill 32B wins at $0.03/1M input tokens. For speed, DeepSeek R1 Distill 32B is faster at ~250ms. Jamba 1.5 Large excels at Full text processing while DeepSeek R1 Distill 32B is better for Production reasoning. 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 R1 Distill 32B costs $0.03 input and $0.06 output. DeepSeek R1 Distill 32B is 2.7x 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 R1 Distill 32B offers 128K context at ~250ms. 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 R1 Distill 32B (Reasoning) works best for: Production reasoning, Analysis, Structured tasks.

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 R1 Distill 32B
response_b = client.chat.completions.create(
    model="deepseek-r1-distill-32b",
    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 R1 Distill 32B?

Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. DeepSeek R1 Distill 32B (Reasoning, 32B) offers Good reasoning. Choose Jamba 1.5 Large for Full text processing or DeepSeek R1 Distill 32B for Production reasoning.

How much does Jamba 1.5 Large cost vs DeepSeek R1 Distill 32B?

Jamba 1.5 Large: $0.08/1M input, $0.14/1M output. DeepSeek R1 Distill 32B: $0.03/1M input, $0.06/1M 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 R1 Distill 32B 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.