Llama 3.1 405B vs DBRX
Compare Llama 3.1 405B 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
| Feature | Llama 3.1 405B | DBRX |
|---|---|---|
| Category | Open Source | Enterprise |
| Parameters | 405B | 132B (36B active) |
| Context Window | 128K | 32K |
| Input Price | $0.08/1M tokens | $0.04/1M tokens |
| Output Price | $0.14/1M tokens | $0.08/1M tokens |
| Latency | ~600ms | ~300ms |
Choose Llama 3.1 405B when:
- ✓ Premium tasks
- ✓ Research
- ✓ Fine-tuning base
Largest open model, Highest open-source quality
Choose DBRX when:
- ✓ Data pipelines
- ✓ Analytics
- ✓ Enterprise workflows
MoE efficient, Good for data, Enterprise-grade
Verdict: Llama 3.1 405B vs DBRX
For cost efficiency, DBRX wins at $0.04/1M input tokens. For speed, DBRX is faster at ~300ms. Llama 3.1 405B excels at Premium tasks 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 405B costs $0.08/1M input tokens and $0.14/1M output tokens. DBRX costs $0.04 input and $0.08 output. DBRX is 2.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Llama 3.1 405B has a 128K context window with ~600ms latency. DBRX offers 32K context at ~300ms. Llama 3.1 405B has the larger context window.
Best For
Llama 3.1 405B (Open Source) is optimized for: Premium tasks, Research, Fine-tuning base. 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 405B
response_a = client.chat.completions.create(
model="llama-3-1-405b",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use DBRX
response_b = client.chat.completions.create(
model="dbrx",
messages=[{"role": "user", "content": "Your question here"}]
)
Frequently Asked Questions
Which is better, Llama 3.1 405B or DBRX?
Llama 3.1 405B (Open Source, 405B) offers Largest open model. DBRX (Enterprise, 132B (36B active)) offers MoE efficient. Choose Llama 3.1 405B for Premium tasks or DBRX for Data pipelines.
How much does Llama 3.1 405B cost vs DBRX?
Llama 3.1 405B: $0.08/1M input, $0.14/1M 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 405B 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.