Jamba 1.5 Mini vs Nemotron 4 340B
Compare Jamba 1.5 Mini and Nemotron 4 340B: 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 | Nemotron 4 340B |
|---|---|---|
| Category | Compact | Open Source |
| Parameters | 52B (12B active) | 340B |
| Context Window | 256K | 128K |
| Input Price | $0.02/1M tokens | $0.07/1M tokens |
| Output Price | $0.04/1M tokens | $0.12/1M tokens |
| Latency | ~200ms | ~500ms |
Choose Jamba 1.5 Mini when:
- ✓ Long document Q&A
- ✓ Budget apps
- ✓ Summarization
256K context, Low cost, SSM efficiency
Choose Nemotron 4 340B when:
- ✓ Data generation
- ✓ Training data
- ✓ Research
Synthetic data generation, Large scale, Good quality
Verdict: Jamba 1.5 Mini vs Nemotron 4 340B
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 Nemotron 4 340B is better for Data generation. 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. Nemotron 4 340B costs $0.07 input and $0.12 output. Jamba 1.5 Mini is 3.5x 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. Nemotron 4 340B offers 128K context at ~500ms. 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. Nemotron 4 340B (Open Source) works best for: Data generation, Training data, Research.
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 Nemotron 4 340B
response_b = client.chat.completions.create(
model="nemotron-4-340b",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Jamba 1.5 Mini or Nemotron 4 340B?
Jamba 1.5 Mini (Compact, 52B (12B active)) offers 256K context. Nemotron 4 340B (Open Source, 340B) offers Synthetic data generation. Choose Jamba 1.5 Mini for Long document Q&A or Nemotron 4 340B for Data generation.
How much does Jamba 1.5 Mini cost vs Nemotron 4 340B?
Jamba 1.5 Mini: $0.02/1M input, $0.04/1M output. Nemotron 4 340B: $0.07/1M input, $0.12/1M 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 Nemotron 4 340B 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.