DeepSeek R1 0528 vs Code Llama 70B

Compare DeepSeek R1 0528 and Code Llama 70B: pricing, performance, context window, latency, and best use cases. Side-by-side comparison on XALEN.

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

All DeepSeek models All Meta models What is an LLM API? Python Quickstart What is inference?
Feature DeepSeek R1 0528 Code Llama 70B
CategoryReasoningCode
Parameters671B70B
Context Window128K100K
Input Price$0.08/1M tokens$0.04/1M tokens
Output Price$0.15/1M tokens$0.06/1M tokens
Latency~800ms~300ms

Choose DeepSeek R1 0528 when:

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

Improved accuracy, Reduced hallucination, Strong math

Choose Code Llama 70B when:

  • ✓ Large codebases
  • ✓ Code review
  • ✓ Refactoring
Key Strengths:

100K context, Strong coding, Fill-in-middle

Verdict: DeepSeek R1 0528 vs Code Llama 70B

For cost efficiency, Code Llama 70B wins at $0.04/1M input tokens. For speed, Code Llama 70B is faster at ~300ms. DeepSeek R1 0528 excels at Calculation verification while Code Llama 70B is better for Large codebases. 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 0528 costs $0.08/1M input tokens and $0.15/1M output tokens. Code Llama 70B costs $0.04 input and $0.06 output. Code Llama 70B is 2.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

DeepSeek R1 0528 has a 128K context window with ~800ms latency. Code Llama 70B offers 100K context at ~300ms. DeepSeek R1 0528 has the larger context window.

Best For

DeepSeek R1 0528 (Reasoning) is optimized for: Calculation verification, Classical text analysis, Quality-critical. Code Llama 70B (Code) works best for: Large codebases, Code review, Refactoring.

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

# Use Code Llama 70B
response_b = client.chat.completions.create(
    model="codellama-70b",
    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, DeepSeek R1 0528 or Code Llama 70B?

DeepSeek R1 0528 (Reasoning, 671B) offers Improved accuracy. Code Llama 70B (Code, 70B) offers 100K context. Choose DeepSeek R1 0528 for Calculation verification or Code Llama 70B for Large codebases.

How much does DeepSeek R1 0528 cost vs Code Llama 70B?

DeepSeek R1 0528: $0.08/1M input, $0.15/1M output. Code Llama 70B: $0.04/1M input, $0.06/1M 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 0528 and Code Llama 70B 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.