DBRX vs Amazon Titan Embed v2
Compare DBRX 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 | DBRX | Amazon Titan Embed v2 |
|---|---|---|
| Category | Enterprise | Embedding |
| Parameters | 132B (36B active) | ~200M |
| Context Window | 32K | 8K |
| Input Price | $0.04/1M tokens | $0.001/1M tokens |
| Output Price | $0.08/1M tokens | N/A/1M tokens |
| Latency | ~300ms | ~15ms |
Choose DBRX when:
- ✓ Data pipelines
- ✓ Analytics
- ✓ Enterprise workflows
MoE efficient, Good for data, Enterprise-grade
Choose Amazon Titan Embed v2 when:
- ✓ AWS RAG pipelines
- ✓ Enterprise search
- ✓ Document indexing
AWS native, Low cost, Reliable
Verdict: DBRX 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. DBRX excels at Data pipelines 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
DBRX costs $0.04/1M input tokens and $0.08/1M 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
DBRX has a 32K context window with ~300ms latency. Amazon Titan Embed v2 offers 8K context at ~15ms. DBRX has the larger context window.
Best For
DBRX (Enterprise) is optimized for: Data pipelines, Analytics, Enterprise workflows. 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 DBRX
response_a = client.chat.completions.create(
model="dbrx",
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, DBRX or Amazon Titan Embed v2?
DBRX (Enterprise, 132B (36B active)) offers MoE efficient. Amazon Titan Embed v2 (Embedding, ~200M) offers AWS native. Choose DBRX for Data pipelines or Amazon Titan Embed v2 for AWS RAG pipelines.
How much does DBRX cost vs Amazon Titan Embed v2?
DBRX: $0.04/1M input, $0.08/1M 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 DBRX 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.