Llama 3.1 405B vs DeepSeek R1 0528

Compare Llama 3.1 405B 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 Llama 3.1 405B DeepSeek R1 0528
CategoryOpen SourceReasoning
Parameters405B671B
Context Window128K128K
Input Price$0.08/1M tokens$0.08/1M tokens
Output Price$0.14/1M tokens$0.15/1M tokens
Latency~600ms~800ms

Choose Llama 3.1 405B when:

  • ✓ Premium tasks
  • ✓ Research
  • ✓ Fine-tuning base
Key Strengths:

Largest open model, Highest open-source quality

Choose DeepSeek R1 0528 when:

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

Improved accuracy, Reduced hallucination, Strong math

Verdict: Llama 3.1 405B vs DeepSeek R1 0528

For cost efficiency, DeepSeek R1 0528 wins at $0.08/1M input tokens. For speed, Llama 3.1 405B is faster at ~600ms. Llama 3.1 405B excels at Premium tasks 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

Llama 3.1 405B costs $0.08/1M input tokens and $0.14/1M output tokens. DeepSeek R1 0528 costs $0.08 input and $0.15 output. Both models are similarly priced. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Llama 3.1 405B has a 128K context window with ~600ms latency. DeepSeek R1 0528 offers 128K context at ~800ms. Both have identical context windows.

Best For

Llama 3.1 405B (Open Source) is optimized for: Premium tasks, Research, Fine-tuning base. 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 Llama 3.1 405B
response_a = client.chat.completions.create(
    model="llama-3-1-405b",
    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

200+ AI models. One API. Pay-as-you-go.

Get API Key Try in Playground

Frequently Asked Questions

Which is better, Llama 3.1 405B or DeepSeek R1 0528?

Llama 3.1 405B (Open Source, 405B) offers Largest open model. DeepSeek R1 0528 (Reasoning, 671B) offers Improved accuracy. Choose Llama 3.1 405B for Premium tasks or DeepSeek R1 0528 for Calculation verification.

How much does Llama 3.1 405B cost vs DeepSeek R1 0528?

Llama 3.1 405B: $0.08/1M input, $0.14/1M 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 Llama 3.1 405B 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.