Jamba 1.5 Large vs o3 Pro
Compare Jamba 1.5 Large and o3 Pro: pricing, performance, context window, latency, and best use cases. Side-by-side comparison on XALEN.
Updated 2026-05-21 · By Abhishek Raj · Our methodology
| Feature | Jamba 1.5 Large | o3 Pro |
|---|---|---|
| Category | Enterprise | Reasoning |
| Parameters | 398B (94B active) | ~1T |
| Context Window | 256K | 200K |
| Input Price | $0.08/1M tokens | $0.15/1M tokens |
| Output Price | $0.14/1M tokens | $0.60/1M tokens |
| Latency | ~500ms | ~5000ms |
Choose Jamba 1.5 Large when:
- ✓ Full text processing
- ✓ Comprehensive reports
- ✓ Long analysis
256K context, SSM-Transformer hybrid, Good summarization
Choose o3 Pro when:
- ✓ Research-grade reasoning
- ✓ Mathematical proofs
- ✓ Hardest problems
Deepest reasoning, Best for hard problems, Highest accuracy
Verdict: Jamba 1.5 Large vs o3 Pro
For cost efficiency, Jamba 1.5 Large wins at $0.08/1M input tokens. For speed, o3 Pro is faster at ~5000ms. Jamba 1.5 Large excels at Full text processing while o3 Pro is better for Research-grade 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. o3 Pro costs $0.15 input and $0.60 output. Jamba 1.5 Large is 1.9x 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. o3 Pro offers 200K context at ~5000ms. 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. o3 Pro (Reasoning) works best for: Research-grade reasoning, Mathematical proofs, Hardest problems.
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 o3 Pro
response_b = client.chat.completions.create(
model="o3-pro",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Jamba 1.5 Large or o3 Pro?
Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. o3 Pro (Reasoning, ~1T) offers Deepest reasoning. Choose Jamba 1.5 Large for Full text processing or o3 Pro for Research-grade reasoning.
How much does Jamba 1.5 Large cost vs o3 Pro?
Jamba 1.5 Large: $0.08/1M input, $0.14/1M output. o3 Pro: $0.15/1M input, $0.60/1M 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 o3 Pro by changing the model parameter. No code changes needed.
Related Comparisons
Last updated: 2026-05-21. Pricing and specifications may change. Check pricing page for latest rates.