Amazon Titan Embed v2 vs Qwen 3 14B
Compare Amazon Titan Embed v2 and Qwen 3 14B: pricing, performance, context window, latency, and best use cases. Side-by-side comparison on XALEN.
Updated 2026-05-21 · By Abhishek Raj · Our methodology
| Feature | Amazon Titan Embed v2 | Qwen 3 14B |
|---|---|---|
| Category | Embedding | Compact |
| Parameters | ~200M | 14B |
| Context Window | 8K | 128K |
| Input Price | $0.001/1M tokens | $0.015/1M tokens |
| Output Price | N/A/1M tokens | $0.03/1M tokens |
| Latency | ~15ms | ~100ms |
Choose Amazon Titan Embed v2 when:
- ✓ AWS RAG pipelines
- ✓ Enterprise search
- ✓ Document indexing
AWS native, Low cost, Reliable
Choose Qwen 3 14B when:
- ✓ Moderate tasks
- ✓ Fast chatbots
- ✓ Budget apps
Good reasoning for size, Fast, 128K context
Verdict: Amazon Titan Embed v2 vs Qwen 3 14B
For cost efficiency, Amazon Titan Embed v2 wins at $0.001/1M input tokens. For speed, Qwen 3 14B is faster at ~100ms. Amazon Titan Embed v2 excels at AWS RAG pipelines while Qwen 3 14B is better for Moderate tasks. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.
Detailed Analysis
Pricing Comparison
Amazon Titan Embed v2 costs $0.001/1M input tokens and N/A/1M output tokens. Qwen 3 14B costs $0.015 input and $0.03 output. Amazon Titan Embed v2 is 15.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Amazon Titan Embed v2 has a 8K context window with ~15ms latency. Qwen 3 14B offers 128K context at ~100ms. Qwen 3 14B has the larger context window.
Best For
Amazon Titan Embed v2 (Embedding) is optimized for: AWS RAG pipelines, Enterprise search, Document indexing. Qwen 3 14B (Compact) works best for: Moderate tasks, Fast chatbots, Budget apps.
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 Amazon Titan Embed v2
response_a = client.chat.completions.create(
model="amazon-titan-embed-v2",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use Qwen 3 14B
response_b = client.chat.completions.create(
model="qwen-3-14b",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Amazon Titan Embed v2 or Qwen 3 14B?
Amazon Titan Embed v2 (Embedding, ~200M) offers AWS native. Qwen 3 14B (Compact, 14B) offers Good reasoning for size. Choose Amazon Titan Embed v2 for AWS RAG pipelines or Qwen 3 14B for Moderate tasks.
How much does Amazon Titan Embed v2 cost vs Qwen 3 14B?
Amazon Titan Embed v2: $0.001/1M input, N/A/1M output. Qwen 3 14B: $0.015/1M input, $0.03/1M 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 Amazon Titan Embed v2 and Qwen 3 14B 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.