Jamba 1.5 Large vs OLMo 2 13B

Compare Jamba 1.5 Large and OLMo 2 13B: 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 OLMo 2 13B
CategoryEnterpriseOpen Source
Parameters398B (94B active)13B
Context Window256K32K
Input Price$0.08/1M tokens$0.015/1M tokens
Output Price$0.14/1M tokens$0.03/1M tokens
Latency~500ms~120ms

Choose Jamba 1.5 Large when:

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

256K context, SSM-Transformer hybrid, Good summarization

Choose OLMo 2 13B when:

  • ✓ Research
  • ✓ Custom training
  • ✓ Transparency-required apps
Key Strengths:

Fully open (weights + data), Transparent, Research-friendly

Verdict: Jamba 1.5 Large vs OLMo 2 13B

For cost efficiency, OLMo 2 13B wins at $0.015/1M input tokens. For speed, OLMo 2 13B is faster at ~120ms. Jamba 1.5 Large excels at Full text processing while OLMo 2 13B is better for Research. 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. OLMo 2 13B costs $0.015 input and $0.03 output. OLMo 2 13B is 5.3x 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. OLMo 2 13B offers 32K context at ~120ms. 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. OLMo 2 13B (Open Source) works best for: Research, Custom training, Transparency-required 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 OLMo 2 13B
response_b = client.chat.completions.create(
    model="olmo-2-13b",
    messages=[{"role": "user", "content": "Your question here"}]
)

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Get API Key Try in Playground

Frequently Asked Questions

Which is better, Jamba 1.5 Large or OLMo 2 13B?

Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. OLMo 2 13B (Open Source, 13B) offers Fully open (weights + data). Choose Jamba 1.5 Large for Full text processing or OLMo 2 13B for Research.

How much does Jamba 1.5 Large cost vs OLMo 2 13B?

Jamba 1.5 Large: $0.08/1M input, $0.14/1M output. OLMo 2 13B: $0.015/1M input, $0.03/1M 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 OLMo 2 13B 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.