Llama 3.1 70B Turbo vs StarCoder2 15B

Compare Llama 3.1 70B Turbo and StarCoder2 15B: 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 Meta models All BigCode models What is an LLM API? Python Quickstart What is inference?
Feature Llama 3.1 70B Turbo StarCoder2 15B
CategoryOpen SourceCode
Parameters70B15B
Context Window128K16K
Input Price$0.04/1M tokens$0.02/1M tokens
Output Price$0.06/1M tokens$0.03/1M tokens
Latency~250ms~150ms

Choose Llama 3.1 70B Turbo when:

  • ✓ Production APIs
  • ✓ Fast generation
  • ✓ General purpose
Key Strengths:

Fast inference, Good quality, Well-tested

Choose StarCoder2 15B when:

  • ✓ Code completion
  • ✓ Code generation
  • ✓ Bug fixing
Key Strengths:

Strong coding, 600+ languages, Open weights

Verdict: Llama 3.1 70B Turbo vs StarCoder2 15B

For cost efficiency, StarCoder2 15B wins at $0.02/1M input tokens. For speed, StarCoder2 15B is faster at ~150ms. Llama 3.1 70B Turbo excels at Production APIs while StarCoder2 15B is better for Code completion. 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 70B Turbo costs $0.04/1M input tokens and $0.06/1M output tokens. StarCoder2 15B costs $0.02 input and $0.03 output. StarCoder2 15B is 2.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Llama 3.1 70B Turbo has a 128K context window with ~250ms latency. StarCoder2 15B offers 16K context at ~150ms. Llama 3.1 70B Turbo has the larger context window.

Best For

Llama 3.1 70B Turbo (Open Source) is optimized for: Production APIs, Fast generation, General purpose. StarCoder2 15B (Code) works best for: Code completion, Code generation, Bug fixing.

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 70B Turbo
response_a = client.chat.completions.create(
    model="llama-3-1-70b-turbo",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use StarCoder2 15B
response_b = client.chat.completions.create(
    model="starcoder2-15b",
    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 70B Turbo or StarCoder2 15B?

Llama 3.1 70B Turbo (Open Source, 70B) offers Fast inference. StarCoder2 15B (Code, 15B) offers Strong coding. Choose Llama 3.1 70B Turbo for Production APIs or StarCoder2 15B for Code completion.

How much does Llama 3.1 70B Turbo cost vs StarCoder2 15B?

Llama 3.1 70B Turbo: $0.04/1M input, $0.06/1M output. StarCoder2 15B: $0.02/1M input, $0.03/1M 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 70B Turbo and StarCoder2 15B 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.