Llama 3.1 8B Turbo vs StarCoder2 7B

Compare Llama 3.1 8B Turbo and StarCoder2 7B: 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 8B Turbo StarCoder2 7B
CategoryCompactCode
Parameters8B7B
Context Window128K16K
Input Price$0.01/1M tokens$0.008/1M tokens
Output Price$0.02/1M tokens$0.015/1M tokens
Latency~60ms~60ms

Choose Llama 3.1 8B Turbo when:

  • ✓ Intent classification
  • ✓ Content filtering
  • ✓ Simple Q&A
Key Strengths:

Extremely fast, Very low cost, 128K context

Choose StarCoder2 7B when:

  • ✓ Code completion
  • ✓ Quick generation
  • ✓ Editor integration
Key Strengths:

Open weights, Many languages, Fast

Verdict: Llama 3.1 8B Turbo vs StarCoder2 7B

For cost efficiency, StarCoder2 7B wins at $0.008/1M input tokens. For speed, StarCoder2 7B is faster at ~60ms. Llama 3.1 8B Turbo excels at Intent classification while StarCoder2 7B 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 8B Turbo costs $0.01/1M input tokens and $0.02/1M output tokens. StarCoder2 7B costs $0.008 input and $0.015 output. StarCoder2 7B is 1.3x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Llama 3.1 8B Turbo has a 128K context window with ~60ms latency. StarCoder2 7B offers 16K context at ~60ms. Llama 3.1 8B Turbo has the larger context window.

Best For

Llama 3.1 8B Turbo (Compact) is optimized for: Intent classification, Content filtering, Simple Q&A. StarCoder2 7B (Code) works best for: Code completion, Quick generation, Editor integration.

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 8B Turbo
response_a = client.chat.completions.create(
    model="llama-3-1-8b-turbo",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use StarCoder2 7B
response_b = client.chat.completions.create(
    model="starcoder2-7b",
    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 8B Turbo or StarCoder2 7B?

Llama 3.1 8B Turbo (Compact, 8B) offers Extremely fast. StarCoder2 7B (Code, 7B) offers Open weights. Choose Llama 3.1 8B Turbo for Intent classification or StarCoder2 7B for Code completion.

How much does Llama 3.1 8B Turbo cost vs StarCoder2 7B?

Llama 3.1 8B Turbo: $0.01/1M input, $0.02/1M output. StarCoder2 7B: $0.008/1M input, $0.015/1M 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 8B Turbo and StarCoder2 7B 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.