Phi-3.5 Mini vs Amazon Titan Embed v2

Compare Phi-3.5 Mini 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 Microsoft models All Amazon models What is an LLM API? Python Quickstart What is inference?
Feature Phi-3.5 Mini Amazon Titan Embed v2
CategoryCompactEmbedding
Parameters3.8B~200M
Context Window128K8K
Input Price$0.005/1M tokens$0.001/1M tokens
Output Price$0.01/1M tokensN/A/1M tokens
Latency~50ms~15ms

Choose Phi-3.5 Mini when:

  • ✓ Simple Q&A
  • ✓ Classification
  • ✓ Edge inference
Key Strengths:

128K context in tiny model, Ultra-low cost, Fast

Choose Amazon Titan Embed v2 when:

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

AWS native, Low cost, Reliable

Verdict: Phi-3.5 Mini 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. Phi-3.5 Mini excels at Simple Q&A 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

Phi-3.5 Mini costs $0.005/1M input tokens and $0.01/1M output tokens. Amazon Titan Embed v2 costs $0.001 input and N/A output. Amazon Titan Embed v2 is 5.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Phi-3.5 Mini has a 128K context window with ~50ms latency. Amazon Titan Embed v2 offers 8K context at ~15ms. Phi-3.5 Mini has the larger context window.

Best For

Phi-3.5 Mini (Compact) is optimized for: Simple Q&A, Classification, Edge inference. 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 Phi-3.5 Mini
response_a = client.chat.completions.create(
    model="phi-3-5-mini",
    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, Phi-3.5 Mini or Amazon Titan Embed v2?

Phi-3.5 Mini (Compact, 3.8B) offers 128K context in tiny model. Amazon Titan Embed v2 (Embedding, ~200M) offers AWS native. Choose Phi-3.5 Mini for Simple Q&A or Amazon Titan Embed v2 for AWS RAG pipelines.

How much does Phi-3.5 Mini cost vs Amazon Titan Embed v2?

Phi-3.5 Mini: $0.005/1M input, $0.01/1M 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 Phi-3.5 Mini and Amazon Titan Embed v2 by changing the model parameter. No code changes needed.

Related Comparisons

Phi-3.5 Mini vs GPT-4.1 Nano Phi-3.5 Mini vs GPT-4o Mini Phi-3.5 Mini vs Text Embedding 3 Large Phi-3.5 Mini vs Claude Haiku 3.5 Phi-3.5 Mini vs Gemma 3 12B Phi-3.5 Mini vs Gemma 3 4B

Last updated: 2026-05-21. Pricing and specifications may change. Check pricing page for latest rates.