Llama 3.1 405B vs Jamba 1.5 Large

Compare Llama 3.1 405B 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 405B Jamba 1.5 Large
CategoryOpen SourceEnterprise
Parameters405B398B (94B active)
Context Window128K256K
Input Price$0.08/1M tokens$0.08/1M tokens
Output Price$0.14/1M tokens$0.14/1M tokens
Latency~600ms~500ms

Choose Llama 3.1 405B when:

  • ✓ Premium tasks
  • ✓ Research
  • ✓ Fine-tuning base
Key Strengths:

Largest open model, Highest open-source quality

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 405B vs Jamba 1.5 Large

For cost efficiency, Jamba 1.5 Large wins at $0.08/1M input tokens. For speed, Jamba 1.5 Large is faster at ~500ms. Llama 3.1 405B excels at Premium tasks 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 405B costs $0.08/1M input tokens and $0.14/1M output tokens. Jamba 1.5 Large costs $0.08 input and $0.14 output. Both models are similarly priced. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Llama 3.1 405B has a 128K context window with ~600ms latency. Jamba 1.5 Large offers 256K context at ~500ms. Jamba 1.5 Large has the larger context window.

Best For

Llama 3.1 405B (Open Source) is optimized for: Premium tasks, Research, Fine-tuning base. 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 405B
response_a = client.chat.completions.create(
    model="llama-3-1-405b",
    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

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Get API Key Try in Playground

Frequently Asked Questions

Which is better, Llama 3.1 405B or Jamba 1.5 Large?

Llama 3.1 405B (Open Source, 405B) offers Largest open model. Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. Choose Llama 3.1 405B for Premium tasks or Jamba 1.5 Large for Full text processing.

How much does Llama 3.1 405B cost vs Jamba 1.5 Large?

Llama 3.1 405B: $0.08/1M input, $0.14/1M 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 405B 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.