DeepSeek Coder V2 vs Arctic Large

Compare DeepSeek Coder V2 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

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Feature DeepSeek Coder V2 Arctic Large
CategoryCodeEnterprise
Parameters236B (21B active)480B (17B active)
Context Window128K128K
Input Price$0.03/1M tokens$0.06/1M tokens
Output Price$0.06/1M tokens$0.10/1M tokens
Latency~250ms~400ms

Choose DeepSeek Coder V2 when:

  • ✓ System development
  • ✓ API clients
  • ✓ Backend services
Key Strengths:

MoE efficiency, Strong coding, Multiple languages

Choose Arctic Large when:

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

Strong SQL, Data analysis, Enterprise features

Verdict: DeepSeek Coder V2 vs Arctic Large

For cost efficiency, DeepSeek Coder V2 wins at $0.03/1M input tokens. For speed, DeepSeek Coder V2 is faster at ~250ms. DeepSeek Coder V2 excels at System development 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 Coder V2 costs $0.03/1M input tokens and $0.06/1M output tokens. Arctic Large costs $0.06 input and $0.10 output. DeepSeek Coder V2 is 2.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

DeepSeek Coder V2 has a 128K context window with ~250ms latency. Arctic Large offers 128K context at ~400ms. Both have identical context windows.

Best For

DeepSeek Coder V2 (Code) is optimized for: System development, API clients, Backend services. 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 Coder V2
response_a = client.chat.completions.create(
    model="deepseek-coder-v2",
    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"}]
)

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Frequently Asked Questions

Which is better, DeepSeek Coder V2 or Arctic Large?

DeepSeek Coder V2 (Code, 236B (21B active)) offers MoE efficiency. Arctic Large (Enterprise, 480B (17B active)) offers Strong SQL. Choose DeepSeek Coder V2 for System development or Arctic Large for Data analysis.

How much does DeepSeek Coder V2 cost vs Arctic Large?

DeepSeek Coder V2: $0.03/1M input, $0.06/1M 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 Coder V2 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.