DeepSeek V3.1 vs Jamba 1.5 Mini
Compare DeepSeek V3.1 and Jamba 1.5 Mini: 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 Mini |
|---|---|---|
| Category | Open Source | Compact |
| Parameters | 685B (37B active) | 52B (12B active) |
| Context Window | 128K | 256K |
| Input Price | $0.06/1M tokens | $0.02/1M tokens |
| Output Price | $0.10/1M tokens | $0.04/1M tokens |
| Latency | ~400ms | ~200ms |
Choose DeepSeek V3.1 when:
- ✓ Production apps
- ✓ Content generation
- ✓ Multi-language
Improved quality, Better safety, Stronger multilingual
Choose Jamba 1.5 Mini when:
- ✓ Long document Q&A
- ✓ Budget apps
- ✓ Summarization
256K context, Low cost, SSM efficiency
Verdict: DeepSeek V3.1 vs Jamba 1.5 Mini
For cost efficiency, Jamba 1.5 Mini wins at $0.02/1M input tokens. For speed, Jamba 1.5 Mini is faster at ~200ms. DeepSeek V3.1 excels at Production apps while Jamba 1.5 Mini is better for Long document Q&A. 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 Mini costs $0.02 input and $0.04 output. Jamba 1.5 Mini is 3.0x 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 Mini offers 256K context at ~200ms. Jamba 1.5 Mini has the larger context window.
Best For
DeepSeek V3.1 (Open Source) is optimized for: Production apps, Content generation, Multi-language. Jamba 1.5 Mini (Compact) works best for: Long document Q&A, Budget apps, Summarization.
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 Mini
response_b = client.chat.completions.create(
model="jamba-1-5-mini",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, DeepSeek V3.1 or Jamba 1.5 Mini?
DeepSeek V3.1 (Open Source, 685B (37B active)) offers Improved quality. Jamba 1.5 Mini (Compact, 52B (12B active)) offers 256K context. Choose DeepSeek V3.1 for Production apps or Jamba 1.5 Mini for Long document Q&A.
How much does DeepSeek V3.1 cost vs Jamba 1.5 Mini?
DeepSeek V3.1: $0.06/1M input, $0.10/1M output. Jamba 1.5 Mini: $0.02/1M input, $0.04/1M 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 Mini 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.