Arctic Large vs Amazon Titan Embed v2
Compare Arctic Large 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
| Feature | Arctic Large | Amazon Titan Embed v2 |
|---|---|---|
| Category | Enterprise | Embedding |
| Parameters | 480B (17B active) | ~200M |
| Context Window | 128K | 8K |
| Input Price | $0.06/1M tokens | $0.001/1M tokens |
| Output Price | $0.10/1M tokens | N/A/1M tokens |
| Latency | ~400ms | ~15ms |
Choose Arctic Large when:
- ✓ Data analysis
- ✓ SQL generation
- ✓ Business intelligence
Strong SQL, Data analysis, Enterprise features
Choose Amazon Titan Embed v2 when:
- ✓ AWS RAG pipelines
- ✓ Enterprise search
- ✓ Document indexing
AWS native, Low cost, Reliable
Verdict: Arctic Large 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. Arctic Large excels at Data analysis 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
Arctic Large costs $0.06/1M input tokens and $0.10/1M output tokens. Amazon Titan Embed v2 costs $0.001 input and N/A output. Amazon Titan Embed v2 is 60.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Arctic Large has a 128K context window with ~400ms latency. Amazon Titan Embed v2 offers 8K context at ~15ms. Arctic Large has the larger context window.
Best For
Arctic Large (Enterprise) is optimized for: Data analysis, SQL generation, Business intelligence. 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 Arctic Large
response_a = client.chat.completions.create(
model="arctic-large",
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"}]
)Frequently Asked Questions
Which is better, Arctic Large or Amazon Titan Embed v2?
Arctic Large (Enterprise, 480B (17B active)) offers Strong SQL. Amazon Titan Embed v2 (Embedding, ~200M) offers AWS native. Choose Arctic Large for Data analysis or Amazon Titan Embed v2 for AWS RAG pipelines.
How much does Arctic Large cost vs Amazon Titan Embed v2?
Arctic Large: $0.06/1M input, $0.10/1M 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 Arctic Large 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.