o3 vs Jamba 1.5 Large

Compare o3 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 o3 Jamba 1.5 Large
CategoryReasoningEnterprise
Parameters~1T398B (94B active)
Context Window200K256K
Input Price$0.10/1M tokens$0.08/1M tokens
Output Price$0.40/1M tokens$0.14/1M tokens
Latency~2000ms~500ms

Choose o3 when:

  • ✓ Complex calculations
  • ✓ Multi-factor analysis
  • ✓ Research-grade work
Key Strengths:

Extended thinking, Complex logic, Mathematical reasoning

Choose Jamba 1.5 Large when:

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

256K context, SSM-Transformer hybrid, Good summarization

Verdict: o3 vs Jamba 1.5 Large

For cost efficiency, Jamba 1.5 Large wins at $0.08/1M input tokens. For speed, o3 is faster at ~2000ms. o3 excels at Complex calculations 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

o3 costs $0.10/1M input tokens and $0.40/1M output tokens. Jamba 1.5 Large costs $0.08 input and $0.14 output. Jamba 1.5 Large is 1.3x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

o3 has a 200K context window with ~2000ms latency. Jamba 1.5 Large offers 256K context at ~500ms. Jamba 1.5 Large has the larger context window.

Best For

o3 (Reasoning) is optimized for: Complex calculations, Multi-factor analysis, Research-grade work. 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 o3
response_a = client.chat.completions.create(
    model="o3",
    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, o3 or Jamba 1.5 Large?

o3 (Reasoning, ~1T) offers Extended thinking. Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. Choose o3 for Complex calculations or Jamba 1.5 Large for Full text processing.

How much does o3 cost vs Jamba 1.5 Large?

o3: $0.10/1M input, $0.40/1M 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 o3 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.