Gemma 3 27B vs DeepSeek R1 0528

Compare Gemma 3 27B and DeepSeek R1 0528: 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 Gemma 3 27B DeepSeek R1 0528
CategoryOpen SourceReasoning
Parameters27B671B
Context Window128K128K
Input Price$0.03/1M tokens$0.08/1M tokens
Output Price$0.05/1M tokens$0.15/1M tokens
Latency~180ms~800ms

Choose Gemma 3 27B when:

  • ✓ Fast chatbots
  • ✓ Content moderation
  • ✓ Temple kiosks
Key Strengths:

Fast inference, Reliable output, Strong English/Hindi

Choose DeepSeek R1 0528 when:

  • ✓ Calculation verification
  • ✓ Classical text analysis
  • ✓ Quality-critical
Key Strengths:

Improved accuracy, Reduced hallucination, Strong math

Verdict: Gemma 3 27B vs DeepSeek R1 0528

For cost efficiency, Gemma 3 27B wins at $0.03/1M input tokens. For speed, Gemma 3 27B is faster at ~180ms. Gemma 3 27B excels at Fast chatbots while DeepSeek R1 0528 is better for Calculation verification. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.

Detailed Analysis

Pricing Comparison

Gemma 3 27B costs $0.03/1M input tokens and $0.05/1M output tokens. DeepSeek R1 0528 costs $0.08 input and $0.15 output. Gemma 3 27B is 2.7x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Gemma 3 27B has a 128K context window with ~180ms latency. DeepSeek R1 0528 offers 128K context at ~800ms. Both have identical context windows.

Best For

Gemma 3 27B (Open Source) is optimized for: Fast chatbots, Content moderation, Temple kiosks. DeepSeek R1 0528 (Reasoning) works best for: Calculation verification, Classical text analysis, Quality-critical.

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 Gemma 3 27B
response_a = client.chat.completions.create(
    model="gemma-3-27b",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use DeepSeek R1 0528
response_b = client.chat.completions.create(
    model="deepseek-r1-0528",
    messages=[{"role": "user", "content": "Your question here"}]
)

Start Building with XALEN

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Get API Key Try in Playground

Frequently Asked Questions

Which is better, Gemma 3 27B or DeepSeek R1 0528?

Gemma 3 27B (Open Source, 27B) offers Fast inference. DeepSeek R1 0528 (Reasoning, 671B) offers Improved accuracy. Choose Gemma 3 27B for Fast chatbots or DeepSeek R1 0528 for Calculation verification.

How much does Gemma 3 27B cost vs DeepSeek R1 0528?

Gemma 3 27B: $0.03/1M input, $0.05/1M output. DeepSeek R1 0528: $0.08/1M input, $0.15/1M 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 Gemma 3 27B and DeepSeek R1 0528 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.