DeepSeek R1 vs DeepSeek V3

Compare DeepSeek R1 and DeepSeek V3: 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 R1 DeepSeek V3
CategoryReasoningOpen Source
Parameters671B671B (37B active)
Context Window128K128K
Input Price$0.08/1M tokens$0.05/1M tokens
Output Price$0.15/1M tokens$0.09/1M tokens
Latency~800ms~400ms

Choose DeepSeek R1 when:

  • ✓ Complex yoga calculations
  • ✓ Dasha analysis
  • ✓ Research-grade analysis
Key Strengths:

Chain-of-thought, Complex calculations, Transparent thinking

Choose DeepSeek V3 when:

  • ✓ API response generation
  • ✓ High-volume processing
  • ✓ Code
Key Strengths:

MoE efficiency, Strong coding, Good structured output

Verdict: DeepSeek R1 vs DeepSeek V3

For cost efficiency, DeepSeek V3 wins at $0.05/1M input tokens. For speed, DeepSeek V3 is faster at ~400ms. DeepSeek R1 excels at Complex yoga calculations while DeepSeek V3 is better for API response generation. 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. DeepSeek V3 costs $0.05 input and $0.09 output. DeepSeek V3 is 1.6x 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. DeepSeek V3 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. DeepSeek V3 (Open Source) works best for: API response generation, High-volume processing, Code.

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 DeepSeek V3
response_b = client.chat.completions.create(
    model="deepseek-v3",
    messages=[{"role": "user", "content": "Your question here"}]
)

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Get API Key Try in Playground

Frequently Asked Questions

Which is better, DeepSeek R1 or DeepSeek V3?

DeepSeek R1 (Reasoning, 671B) offers Chain-of-thought. DeepSeek V3 (Open Source, 671B (37B active)) offers MoE efficiency. Choose DeepSeek R1 for Complex yoga calculations or DeepSeek V3 for API response generation.

How much does DeepSeek R1 cost vs DeepSeek V3?

DeepSeek R1: $0.08/1M input, $0.15/1M output. DeepSeek V3: $0.05/1M input, $0.09/1M 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 DeepSeek V3 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.