Arctic Large vs DeepSeek V2.5

Compare Arctic Large and DeepSeek V2.5: pricing, performance, context window, latency, and best use cases. Side-by-side comparison on XALEN.

Updated 2026-05-21 · By Abhishek Raj · Our methodology

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Feature Arctic Large DeepSeek V2.5
CategoryEnterpriseOpen Source
Parameters480B (17B active)236B (21B active)
Context Window128K128K
Input Price$0.06/1M tokens$0.04/1M tokens
Output Price$0.10/1M tokens$0.07/1M tokens
Latency~400ms~350ms

Choose Arctic Large when:

  • ✓ Data analysis
  • ✓ SQL generation
  • ✓ Business intelligence
Key Strengths:

Strong SQL, Data analysis, Enterprise features

Choose DeepSeek V2.5 when:

  • ✓ General purpose
  • ✓ Code generation
  • ✓ Legacy apps
Key Strengths:

Proven model, MoE efficient, Good coding

Verdict: Arctic Large vs DeepSeek V2.5

For cost efficiency, DeepSeek V2.5 wins at $0.04/1M input tokens. For speed, DeepSeek V2.5 is faster at ~350ms. Arctic Large excels at Data analysis while DeepSeek V2.5 is better for General purpose. 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. DeepSeek V2.5 costs $0.04 input and $0.07 output. DeepSeek V2.5 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. DeepSeek V2.5 offers 128K context at ~350ms. Both have identical context windows.

Best For

Arctic Large (Enterprise) is optimized for: Data analysis, SQL generation, Business intelligence. DeepSeek V2.5 (Open Source) works best for: General purpose, Code generation, Legacy apps.

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 DeepSeek V2.5
response_b = client.chat.completions.create(
    model="deepseek-v2-5",
    messages=[{"role": "user", "content": "Your question here"}]
)

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Get API Key Try in Playground

Frequently Asked Questions

Which is better, Arctic Large or DeepSeek V2.5?

Arctic Large (Enterprise, 480B (17B active)) offers Strong SQL. DeepSeek V2.5 (Open Source, 236B (21B active)) offers Proven model. Choose Arctic Large for Data analysis or DeepSeek V2.5 for General purpose.

How much does Arctic Large cost vs DeepSeek V2.5?

Arctic Large: $0.06/1M input, $0.10/1M output. DeepSeek V2.5: $0.04/1M input, $0.07/1M 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 DeepSeek V2.5 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.