DeepSeek V3.1 vs Jamba 1.5 Large
Compare DeepSeek V3.1 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 | DeepSeek V3.1 | Jamba 1.5 Large |
|---|---|---|
| Category | Open Source | Enterprise |
| Parameters | 685B (37B active) | 398B (94B active) |
| Context Window | 128K | 256K |
| Input Price | $0.06/1M tokens | $0.08/1M tokens |
| Output Price | $0.10/1M tokens | $0.14/1M tokens |
| Latency | ~400ms | ~500ms |
Choose DeepSeek V3.1 when:
- ✓ Production apps
- ✓ Content generation
- ✓ Multi-language
Improved quality, Better safety, Stronger multilingual
Choose Jamba 1.5 Large when:
- ✓ Full text processing
- ✓ Comprehensive reports
- ✓ Long analysis
256K context, SSM-Transformer hybrid, Good summarization
Verdict: DeepSeek V3.1 vs Jamba 1.5 Large
For cost efficiency, DeepSeek V3.1 wins at $0.06/1M input tokens. For speed, DeepSeek V3.1 is faster at ~400ms. DeepSeek V3.1 excels at Production apps 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
DeepSeek V3.1 costs $0.06/1M input tokens and $0.10/1M output tokens. Jamba 1.5 Large costs $0.08 input and $0.14 output. DeepSeek V3.1 is 1.3x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
DeepSeek V3.1 has a 128K context window with ~400ms latency. Jamba 1.5 Large offers 256K context at ~500ms. Jamba 1.5 Large has the larger context window.
Best For
DeepSeek V3.1 (Open Source) is optimized for: Production apps, Content generation, Multi-language. 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 DeepSeek V3.1
response_a = client.chat.completions.create(
model="deepseek-v3-1",
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, DeepSeek V3.1 or Jamba 1.5 Large?
DeepSeek V3.1 (Open Source, 685B (37B active)) offers Improved quality. Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. Choose DeepSeek V3.1 for Production apps or Jamba 1.5 Large for Full text processing.
How much does DeepSeek V3.1 cost vs Jamba 1.5 Large?
DeepSeek V3.1: $0.06/1M input, $0.10/1M 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 DeepSeek V3.1 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.