NVIDIA Nemotron 70B vs Amazon Titan Embed v2

Compare NVIDIA Nemotron 70B and Amazon Titan Embed v2: 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 NVIDIA Nemotron 70B Amazon Titan Embed v2
CategoryOpen SourceEmbedding
Parameters70B~200M
Context Window128K8K
Input Price$0.04/1M tokens$0.001/1M tokens
Output Price$0.06/1M tokensN/A/1M tokens
Latency~300ms~15ms

Choose NVIDIA Nemotron 70B when:

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

Optimized for helpfulness, Strong quality, Good reasoning

Choose Amazon Titan Embed v2 when:

  • ✓ AWS RAG pipelines
  • ✓ Enterprise search
  • ✓ Document indexing
Key Strengths:

AWS native, Low cost, Reliable

Verdict: NVIDIA Nemotron 70B vs Amazon Titan Embed v2

For cost efficiency, Amazon Titan Embed v2 wins at $0.001/1M input tokens. For speed, Amazon Titan Embed v2 is faster at ~15ms. NVIDIA Nemotron 70B excels at Helpful chatbots while Amazon Titan Embed v2 is better for AWS RAG pipelines. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.

Detailed Analysis

Pricing Comparison

NVIDIA Nemotron 70B costs $0.04/1M input tokens and $0.06/1M output tokens. Amazon Titan Embed v2 costs $0.001 input and N/A output. Amazon Titan Embed v2 is 40.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

NVIDIA Nemotron 70B has a 128K context window with ~300ms latency. Amazon Titan Embed v2 offers 8K context at ~15ms. NVIDIA Nemotron 70B has the larger context window.

Best For

NVIDIA Nemotron 70B (Open Source) is optimized for: Helpful chatbots, Customer service, Q&A. Amazon Titan Embed v2 (Embedding) works best for: AWS RAG pipelines, Enterprise search, Document indexing.

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

# Use Amazon Titan Embed v2
response_b = client.chat.completions.create(
    model="amazon-titan-embed-v2",
    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, NVIDIA Nemotron 70B or Amazon Titan Embed v2?

NVIDIA Nemotron 70B (Open Source, 70B) offers Optimized for helpfulness. Amazon Titan Embed v2 (Embedding, ~200M) offers AWS native. Choose NVIDIA Nemotron 70B for Helpful chatbots or Amazon Titan Embed v2 for AWS RAG pipelines.

How much does NVIDIA Nemotron 70B cost vs Amazon Titan Embed v2?

NVIDIA Nemotron 70B: $0.04/1M input, $0.06/1M output. Amazon Titan Embed v2: $0.001/1M input, N/A/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 NVIDIA Nemotron 70B and Amazon Titan Embed v2 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.