Jamba 1.5 Large vs Nemotron 4 340B

Compare Jamba 1.5 Large 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

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Feature Jamba 1.5 Large Nemotron 4 340B
CategoryEnterpriseOpen Source
Parameters398B (94B active)340B
Context Window256K128K
Input Price$0.08/1M tokens$0.07/1M tokens
Output Price$0.14/1M tokens$0.12/1M tokens
Latency~500ms~500ms

Choose Jamba 1.5 Large when:

  • ✓ Full text processing
  • ✓ Comprehensive reports
  • ✓ Long analysis
Key Strengths:

256K context, SSM-Transformer hybrid, Good summarization

Choose Nemotron 4 340B when:

  • ✓ Data generation
  • ✓ Training data
  • ✓ Research
Key Strengths:

Synthetic data generation, Large scale, Good quality

Verdict: Jamba 1.5 Large vs Nemotron 4 340B

For cost efficiency, Nemotron 4 340B wins at $0.07/1M input tokens. For speed, Nemotron 4 340B is faster at ~500ms. Jamba 1.5 Large excels at Full text processing 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 Large costs $0.08/1M input tokens and $0.14/1M output tokens. Nemotron 4 340B costs $0.07 input and $0.12 output. Nemotron 4 340B is 1.1x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Jamba 1.5 Large has a 256K context window with ~500ms latency. Nemotron 4 340B offers 128K context at ~500ms. Jamba 1.5 Large has the larger context window.

Best For

Jamba 1.5 Large (Enterprise) is optimized for: Full text processing, Comprehensive reports, Long analysis. 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 Large
response_a = client.chat.completions.create(
    model="jamba-1-5-large",
    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"}]
)

Start Building with XALEN

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Get API Key Try in Playground

Frequently Asked Questions

Which is better, Jamba 1.5 Large or Nemotron 4 340B?

Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. Nemotron 4 340B (Open Source, 340B) offers Synthetic data generation. Choose Jamba 1.5 Large for Full text processing or Nemotron 4 340B for Data generation.

How much does Jamba 1.5 Large cost vs Nemotron 4 340B?

Jamba 1.5 Large: $0.08/1M input, $0.14/1M 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 Large 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.