Gemini 2.5 Pro vs Jamba 1.5 Large
Compare Gemini 2.5 Pro 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
| Feature | Gemini 2.5 Pro | Jamba 1.5 Large |
|---|---|---|
| Category | Frontier | Enterprise |
| Parameters | ~1.5T | 398B (94B active) |
| Context Window | 2M | 256K |
| Input Price | $0.07/1M tokens | $0.08/1M tokens |
| Output Price | $0.21/1M tokens | $0.14/1M tokens |
| Latency | ~600ms | ~500ms |
Choose Gemini 2.5 Pro when:
- ✓ Classical text analysis
- ✓ Multi-document reports
- ✓ Research
2M context, Strong multimodal, Long text analysis
Choose Jamba 1.5 Large when:
- ✓ Full text processing
- ✓ Comprehensive reports
- ✓ Long analysis
256K context, SSM-Transformer hybrid, Good summarization
Verdict: Gemini 2.5 Pro vs Jamba 1.5 Large
For cost efficiency, Gemini 2.5 Pro wins at $0.07/1M input tokens. For speed, Jamba 1.5 Large is faster at ~500ms. Gemini 2.5 Pro excels at Classical text analysis 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
Gemini 2.5 Pro costs $0.07/1M input tokens and $0.21/1M output tokens. Jamba 1.5 Large costs $0.08 input and $0.14 output. Gemini 2.5 Pro is 1.1x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Gemini 2.5 Pro has a 2M context window with ~600ms latency. Jamba 1.5 Large offers 256K context at ~500ms. Gemini 2.5 Pro has the larger context window.
Best For
Gemini 2.5 Pro (Frontier) is optimized for: Classical text analysis, Multi-document reports, Research. 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 Gemini 2.5 Pro
response_a = client.chat.completions.create(
model="gemini-2-5-pro",
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"}]
)Frequently Asked Questions
Which is better, Gemini 2.5 Pro or Jamba 1.5 Large?
Gemini 2.5 Pro (Frontier, ~1.5T) offers 2M context. Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. Choose Gemini 2.5 Pro for Classical text analysis or Jamba 1.5 Large for Full text processing.
How much does Gemini 2.5 Pro cost vs Jamba 1.5 Large?
Gemini 2.5 Pro: $0.07/1M input, $0.21/1M 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 Gemini 2.5 Pro 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.