Llama 3.2 3B vs Amazon Titan Embed v2

Compare Llama 3.2 3B 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

All Meta models All Amazon models What is an LLM API? Python Quickstart What is inference?
Feature Llama 3.2 3B Amazon Titan Embed v2
CategoryCompactEmbedding
Parameters3B~200M
Context Window128K8K
Input Price$0.006/1M tokens$0.001/1M tokens
Output Price$0.012/1M tokensN/A/1M tokens
Latency~40ms~15ms

Choose Llama 3.2 3B when:

  • ✓ Mobile apps
  • ✓ Edge inference
  • ✓ Preprocessing
Key Strengths:

Ultra-small, Edge-ready, Minimal latency

Choose Amazon Titan Embed v2 when:

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

AWS native, Low cost, Reliable

Verdict: Llama 3.2 3B 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. Llama 3.2 3B excels at Mobile apps 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

Llama 3.2 3B costs $0.006/1M input tokens and $0.012/1M output tokens. Amazon Titan Embed v2 costs $0.001 input and N/A output. Amazon Titan Embed v2 is 6.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Llama 3.2 3B has a 128K context window with ~40ms latency. Amazon Titan Embed v2 offers 8K context at ~15ms. Llama 3.2 3B has the larger context window.

Best For

Llama 3.2 3B (Compact) is optimized for: Mobile apps, Edge inference, Preprocessing. 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 Llama 3.2 3B
response_a = client.chat.completions.create(
    model="llama-3-2-3b",
    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, Llama 3.2 3B or Amazon Titan Embed v2?

Llama 3.2 3B (Compact, 3B) offers Ultra-small. Amazon Titan Embed v2 (Embedding, ~200M) offers AWS native. Choose Llama 3.2 3B for Mobile apps or Amazon Titan Embed v2 for AWS RAG pipelines.

How much does Llama 3.2 3B cost vs Amazon Titan Embed v2?

Llama 3.2 3B: $0.006/1M input, $0.012/1M 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 Llama 3.2 3B 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.