DeepSeek V3.1 vs Arctic Large
Compare DeepSeek V3.1 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 V3.1 | Arctic Large |
|---|---|---|
| Category | Open Source | Enterprise |
| Parameters | 685B (37B active) | 480B (17B active) |
| Context Window | 128K | 128K |
| Input Price | $0.06/1M tokens | $0.06/1M tokens |
| Output Price | $0.10/1M tokens | $0.10/1M tokens |
| Latency | ~400ms | ~400ms |
Choose DeepSeek V3.1 when:
- ✓ Production apps
- ✓ Content generation
- ✓ Multi-language
Improved quality, Better safety, Stronger multilingual
Choose Arctic Large when:
- ✓ Data analysis
- ✓ SQL generation
- ✓ Business intelligence
Strong SQL, Data analysis, Enterprise features
Verdict: DeepSeek V3.1 vs Arctic Large
For cost efficiency, Arctic Large wins at $0.06/1M input tokens. For speed, Arctic Large is faster at ~400ms. DeepSeek V3.1 excels at Production apps 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 V3.1 costs $0.06/1M input tokens and $0.10/1M output tokens. Arctic Large costs $0.06 input and $0.10 output. Both models are similarly priced. XALEN offers batch processing at 50% discount on both models.
Performance & Context
DeepSeek V3.1 has a 128K context window with ~400ms latency. Arctic Large offers 128K context at ~400ms. Both have identical context windows.
Best For
DeepSeek V3.1 (Open Source) is optimized for: Production apps, Content generation, Multi-language. 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 V3.1
response_a = client.chat.completions.create(
model="deepseek-v3-1",
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 V3.1 or Arctic Large?
DeepSeek V3.1 (Open Source, 685B (37B active)) offers Improved quality. Arctic Large (Enterprise, 480B (17B active)) offers Strong SQL. Choose DeepSeek V3.1 for Production apps or Arctic Large for Data analysis.
How much does DeepSeek V3.1 cost vs Arctic Large?
DeepSeek V3.1: $0.06/1M input, $0.10/1M 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 V3.1 and Arctic Large by changing the model parameter. No code changes needed.
Related Comparisons
Last updated: 2026-05-21. Pricing and specifications may change. Check pricing page for latest rates.