Llama 3.1 8B Turbo vs DBRX

Compare Llama 3.1 8B Turbo and DBRX: 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 8B Turbo DBRX
CategoryCompactEnterprise
Parameters8B132B (36B active)
Context Window128K32K
Input Price$0.01/1M tokens$0.04/1M tokens
Output Price$0.02/1M tokens$0.08/1M tokens
Latency~60ms~300ms

Choose Llama 3.1 8B Turbo when:

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

Extremely fast, Very low cost, 128K context

Choose DBRX when:

  • ✓ Data pipelines
  • ✓ Analytics
  • ✓ Enterprise workflows
Key Strengths:

MoE efficient, Good for data, Enterprise-grade

Verdict: Llama 3.1 8B Turbo vs DBRX

For cost efficiency, Llama 3.1 8B Turbo wins at $0.01/1M input tokens. For speed, DBRX is faster at ~300ms. Llama 3.1 8B Turbo excels at Intent classification while DBRX is better for Data pipelines. 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. DBRX costs $0.04 input and $0.08 output. Llama 3.1 8B Turbo is 4.0x 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. DBRX offers 32K context at ~300ms. 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. DBRX (Enterprise) works best for: Data pipelines, Analytics, Enterprise workflows.

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 DBRX
response_b = client.chat.completions.create(
    model="dbrx",
    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 DBRX?

Llama 3.1 8B Turbo (Compact, 8B) offers Extremely fast. DBRX (Enterprise, 132B (36B active)) offers MoE efficient. Choose Llama 3.1 8B Turbo for Intent classification or DBRX for Data pipelines.

How much does Llama 3.1 8B Turbo cost vs DBRX?

Llama 3.1 8B Turbo: $0.01/1M input, $0.02/1M output. DBRX: $0.04/1M input, $0.08/1M 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 DBRX 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.