Llama 3.1 8B Turbo vs Jamba 1.5 Large

Compare Llama 3.1 8B Turbo and Jamba 1.5 Large: 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 AI21 models What is an LLM API? Python Quickstart What is inference?
Feature Llama 3.1 8B Turbo Jamba 1.5 Large
CategoryCompactEnterprise
Parameters8B398B (94B active)
Context Window128K256K
Input Price$0.01/1M tokens$0.08/1M tokens
Output Price$0.02/1M tokens$0.14/1M tokens
Latency~60ms~500ms

Choose Llama 3.1 8B Turbo when:

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

Extremely fast, Very low cost, 128K context

Choose Jamba 1.5 Large when:

  • ✓ Full text processing
  • ✓ Comprehensive reports
  • ✓ Long analysis
Key Strengths:

256K context, SSM-Transformer hybrid, Good summarization

Verdict: Llama 3.1 8B Turbo vs Jamba 1.5 Large

For cost efficiency, Llama 3.1 8B Turbo wins at $0.01/1M input tokens. For speed, Jamba 1.5 Large is faster at ~500ms. Llama 3.1 8B Turbo excels at Intent classification while Jamba 1.5 Large is better for Full text processing. 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. Jamba 1.5 Large costs $0.08 input and $0.14 output. Llama 3.1 8B Turbo is 8.0x 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. Jamba 1.5 Large offers 256K context at ~500ms. Jamba 1.5 Large has the larger context window.

Best For

Llama 3.1 8B Turbo (Compact) is optimized for: Intent classification, Content filtering, Simple Q&A. Jamba 1.5 Large (Enterprise) works best for: Full text processing, Comprehensive reports, Long analysis.

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 Jamba 1.5 Large
response_b = client.chat.completions.create(
    model="jamba-1-5-large",
    messages=[{"role": "user", "content": "Your question here"}]
)

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Get API Key Try in Playground

Frequently Asked Questions

Which is better, Llama 3.1 8B Turbo or Jamba 1.5 Large?

Llama 3.1 8B Turbo (Compact, 8B) offers Extremely fast. Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. Choose Llama 3.1 8B Turbo for Intent classification or Jamba 1.5 Large for Full text processing.

How much does Llama 3.1 8B Turbo cost vs Jamba 1.5 Large?

Llama 3.1 8B Turbo: $0.01/1M input, $0.02/1M output. Jamba 1.5 Large: $0.08/1M input, $0.14/1M 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 Jamba 1.5 Large 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.