Llama 3.1 70B Turbo vs Jamba 1.5 Large

Compare Llama 3.1 70B 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 70B Turbo Jamba 1.5 Large
CategoryOpen SourceEnterprise
Parameters70B398B (94B active)
Context Window128K256K
Input Price$0.04/1M tokens$0.08/1M tokens
Output Price$0.06/1M tokens$0.14/1M tokens
Latency~250ms~500ms

Choose Llama 3.1 70B Turbo when:

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

Fast inference, Good quality, Well-tested

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 70B Turbo vs Jamba 1.5 Large

For cost efficiency, Llama 3.1 70B Turbo wins at $0.04/1M input tokens. For speed, Llama 3.1 70B Turbo is faster at ~250ms. Llama 3.1 70B Turbo excels at Production APIs 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 70B Turbo costs $0.04/1M input tokens and $0.06/1M output tokens. Jamba 1.5 Large costs $0.08 input and $0.14 output. Llama 3.1 70B Turbo 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. Jamba 1.5 Large offers 256K context at ~500ms. Jamba 1.5 Large has the larger context window.

Best For

Llama 3.1 70B Turbo (Open Source) is optimized for: Production APIs, Fast generation, General purpose. 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 70B Turbo
response_a = client.chat.completions.create(
    model="llama-3-1-70b-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"}]
)

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 Jamba 1.5 Large?

Llama 3.1 70B Turbo (Open Source, 70B) offers Fast inference. Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. Choose Llama 3.1 70B Turbo for Production APIs or Jamba 1.5 Large for Full text processing.

How much does Llama 3.1 70B Turbo cost vs Jamba 1.5 Large?

Llama 3.1 70B Turbo: $0.04/1M input, $0.06/1M 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 70B 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.