Arctic Large vs DBRX
Compare Arctic Large and DBRX: 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 | DBRX |
|---|---|---|
| Category | Enterprise | Enterprise |
| Parameters | 480B (17B active) | 132B (36B active) |
| Context Window | 128K | 32K |
| Input Price | $0.06/1M tokens | $0.04/1M tokens |
| Output Price | $0.10/1M tokens | $0.08/1M tokens |
| Latency | ~400ms | ~300ms |
Choose Arctic Large when:
- ✓ Data analysis
- ✓ SQL generation
- ✓ Business intelligence
Strong SQL, Data analysis, Enterprise features
Choose DBRX when:
- ✓ Data pipelines
- ✓ Analytics
- ✓ Enterprise workflows
MoE efficient, Good for data, Enterprise-grade
Verdict: Arctic Large vs DBRX
For cost efficiency, DBRX wins at $0.04/1M input tokens. For speed, DBRX is faster at ~300ms. Arctic Large excels at Data analysis while DBRX is better for Data 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. DBRX costs $0.04 input and $0.08 output. DBRX is 1.5x 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. DBRX offers 32K context at ~300ms. Arctic Large has the larger context window.
Best For
Arctic Large (Enterprise) is optimized for: Data analysis, SQL generation, Business intelligence. DBRX (Enterprise) works best for: Data pipelines, Analytics, Enterprise workflows.
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 DBRX
response_b = client.chat.completions.create(
model="dbrx",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Arctic Large or DBRX?
Arctic Large (Enterprise, 480B (17B active)) offers Strong SQL. DBRX (Enterprise, 132B (36B active)) offers MoE efficient. Choose Arctic Large for Data analysis or DBRX for Data pipelines.
How much does Arctic Large cost vs DBRX?
Arctic Large: $0.06/1M input, $0.10/1M output. DBRX: $0.04/1M input, $0.08/1M 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 DBRX 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.