DeepSeek V3 vs Code Llama 70B

Compare DeepSeek V3 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

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Feature DeepSeek V3 Code Llama 70B
CategoryOpen SourceCode
Parameters671B (37B active)70B
Context Window128K100K
Input Price$0.05/1M tokens$0.04/1M tokens
Output Price$0.09/1M tokens$0.06/1M tokens
Latency~400ms~300ms

Choose DeepSeek V3 when:

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

MoE efficiency, Strong coding, Good structured output

Choose Code Llama 70B when:

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

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

Verdict: DeepSeek V3 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 V3 excels at API response generation 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 V3 costs $0.05/1M input tokens and $0.09/1M output tokens. Code Llama 70B costs $0.04 input and $0.06 output. Code Llama 70B is 1.3x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

DeepSeek V3 has a 128K context window with ~400ms latency. Code Llama 70B offers 100K context at ~300ms. DeepSeek V3 has the larger context window.

Best For

DeepSeek V3 (Open Source) is optimized for: API response generation, High-volume processing, Code. 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 V3
response_a = client.chat.completions.create(
    model="deepseek-v3",
    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"}]
)

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Frequently Asked Questions

Which is better, DeepSeek V3 or Code Llama 70B?

DeepSeek V3 (Open Source, 671B (37B active)) offers MoE efficiency. Code Llama 70B (Code, 70B) offers 100K context. Choose DeepSeek V3 for API response generation or Code Llama 70B for Large codebases.

How much does DeepSeek V3 cost vs Code Llama 70B?

DeepSeek V3: $0.05/1M input, $0.09/1M 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 V3 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.