DeepSeek R1 vs Arctic Large
Compare DeepSeek R1 and Arctic Large: 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 | DeepSeek R1 | Arctic Large |
|---|---|---|
| Category | Reasoning | Enterprise |
| Parameters | 671B | 480B (17B active) |
| Context Window | 128K | 128K |
| Input Price | $0.08/1M tokens | $0.06/1M tokens |
| Output Price | $0.15/1M tokens | $0.10/1M tokens |
| Latency | ~800ms | ~400ms |
Choose DeepSeek R1 when:
- ✓ Complex yoga calculations
- ✓ Dasha analysis
- ✓ Research-grade analysis
Chain-of-thought, Complex calculations, Transparent thinking
Choose Arctic Large when:
- ✓ Data analysis
- ✓ SQL generation
- ✓ Business intelligence
Strong SQL, Data analysis, Enterprise features
Verdict: DeepSeek R1 vs Arctic Large
For cost efficiency, Arctic Large wins at $0.06/1M input tokens. For speed, Arctic Large is faster at ~400ms. DeepSeek R1 excels at Complex yoga calculations while Arctic Large is better for Data analysis. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.
Detailed Analysis
Pricing Comparison
DeepSeek R1 costs $0.08/1M input tokens and $0.15/1M output tokens. Arctic Large costs $0.06 input and $0.10 output. Arctic Large is 1.3x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
DeepSeek R1 has a 128K context window with ~800ms latency. Arctic Large offers 128K context at ~400ms. Both have identical context windows.
Best For
DeepSeek R1 (Reasoning) is optimized for: Complex yoga calculations, Dasha analysis, Research-grade analysis. Arctic Large (Enterprise) works best for: Data analysis, SQL generation, Business intelligence.
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 DeepSeek R1
response_a = client.chat.completions.create(
model="deepseek-r1",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use Arctic Large
response_b = client.chat.completions.create(
model="arctic-large",
messages=[{"role": "user", "content": "Your question here"}]
)
Frequently Asked Questions
Which is better, DeepSeek R1 or Arctic Large?
DeepSeek R1 (Reasoning, 671B) offers Chain-of-thought. Arctic Large (Enterprise, 480B (17B active)) offers Strong SQL. Choose DeepSeek R1 for Complex yoga calculations or Arctic Large for Data analysis.
How much does DeepSeek R1 cost vs Arctic Large?
DeepSeek R1: $0.08/1M input, $0.15/1M output. Arctic Large: $0.06/1M input, $0.10/1M 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 DeepSeek R1 and Arctic Large 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.