Jamba 1.5 Large vs NVIDIA Nemotron 70B

Compare Jamba 1.5 Large and NVIDIA Nemotron 70B: 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 NVIDIA Nemotron 70B
CategoryEnterpriseOpen Source
Parameters398B (94B active)70B
Context Window256K128K
Input Price$0.08/1M tokens$0.04/1M tokens
Output Price$0.14/1M tokens$0.06/1M tokens
Latency~500ms~300ms

Choose Jamba 1.5 Large when:

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

256K context, SSM-Transformer hybrid, Good summarization

Choose NVIDIA Nemotron 70B when:

  • ✓ Helpful chatbots
  • ✓ Customer service
  • ✓ Q&A
Key Strengths:

Optimized for helpfulness, Strong quality, Good reasoning

Verdict: Jamba 1.5 Large vs NVIDIA Nemotron 70B

For cost efficiency, NVIDIA Nemotron 70B wins at $0.04/1M input tokens. For speed, NVIDIA Nemotron 70B is faster at ~300ms. Jamba 1.5 Large excels at Full text processing while NVIDIA Nemotron 70B is better for Helpful chatbots. 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. NVIDIA Nemotron 70B costs $0.04 input and $0.06 output. NVIDIA Nemotron 70B is 2.0x 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. NVIDIA Nemotron 70B offers 128K context at ~300ms. 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. NVIDIA Nemotron 70B (Open Source) works best for: Helpful chatbots, Customer service, Q&A.

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 NVIDIA Nemotron 70B
response_b = client.chat.completions.create(
    model="nvidia-llama-3-1-nemotron-70b",
    messages=[{"role": "user", "content": "Your question here"}]
)

Start Building with XALEN

200+ AI models. One API. Pay-as-you-go.

Get API Key Try in Playground

Frequently Asked Questions

Which is better, Jamba 1.5 Large or NVIDIA Nemotron 70B?

Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. NVIDIA Nemotron 70B (Open Source, 70B) offers Optimized for helpfulness. Choose Jamba 1.5 Large for Full text processing or NVIDIA Nemotron 70B for Helpful chatbots.

How much does Jamba 1.5 Large cost vs NVIDIA Nemotron 70B?

Jamba 1.5 Large: $0.08/1M input, $0.14/1M output. NVIDIA Nemotron 70B: $0.04/1M input, $0.06/1M 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 NVIDIA Nemotron 70B 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.