Jamba 1.5 Mini vs DeepSeek V2.5
Compare Jamba 1.5 Mini and DeepSeek V2.5: 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 Mini | DeepSeek V2.5 |
|---|---|---|
| Category | Compact | Open Source |
| Parameters | 52B (12B active) | 236B (21B active) |
| Context Window | 256K | 128K |
| Input Price | $0.02/1M tokens | $0.04/1M tokens |
| Output Price | $0.04/1M tokens | $0.07/1M tokens |
| Latency | ~200ms | ~350ms |
Choose Jamba 1.5 Mini when:
- ✓ Long document Q&A
- ✓ Budget apps
- ✓ Summarization
256K context, Low cost, SSM efficiency
Choose DeepSeek V2.5 when:
- ✓ General purpose
- ✓ Code generation
- ✓ Legacy apps
Proven model, MoE efficient, Good coding
Verdict: Jamba 1.5 Mini vs DeepSeek V2.5
For cost efficiency, Jamba 1.5 Mini wins at $0.02/1M input tokens. For speed, Jamba 1.5 Mini is faster at ~200ms. Jamba 1.5 Mini excels at Long document Q&A while DeepSeek V2.5 is better for General purpose. 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 Mini costs $0.02/1M input tokens and $0.04/1M output tokens. DeepSeek V2.5 costs $0.04 input and $0.07 output. Jamba 1.5 Mini is 2.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Jamba 1.5 Mini has a 256K context window with ~200ms latency. DeepSeek V2.5 offers 128K context at ~350ms. Jamba 1.5 Mini has the larger context window.
Best For
Jamba 1.5 Mini (Compact) is optimized for: Long document Q&A, Budget apps, Summarization. DeepSeek V2.5 (Open Source) works best for: General purpose, Code generation, Legacy apps.
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 Mini
response_a = client.chat.completions.create(
model="jamba-1-5-mini",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use DeepSeek V2.5
response_b = client.chat.completions.create(
model="deepseek-v2-5",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Jamba 1.5 Mini or DeepSeek V2.5?
Jamba 1.5 Mini (Compact, 52B (12B active)) offers 256K context. DeepSeek V2.5 (Open Source, 236B (21B active)) offers Proven model. Choose Jamba 1.5 Mini for Long document Q&A or DeepSeek V2.5 for General purpose.
How much does Jamba 1.5 Mini cost vs DeepSeek V2.5?
Jamba 1.5 Mini: $0.02/1M input, $0.04/1M output. DeepSeek V2.5: $0.04/1M input, $0.07/1M 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 Mini and DeepSeek V2.5 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.