Llama 3.1 405B vs Voyage Large 2
Compare Llama 3.1 405B and Voyage Large 2: 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 | Voyage Large 2 |
|---|---|---|
| Category | Open Source | Embedding |
| Parameters | 405B | ~500M |
| Context Window | 128K | 16K |
| Input Price | $0.08/1M tokens | $0.002/1M tokens |
| Output Price | $0.14/1M tokens | N/A/1M tokens |
| Latency | ~600ms | ~25ms |
Choose Llama 3.1 405B when:
- ✓ Premium tasks
- ✓ Research
- ✓ Fine-tuning base
Largest open model, Highest open-source quality
Choose Voyage Large 2 when:
- ✓ Code search
- ✓ Long document RAG
- ✓ Semantic matching
16K context, High quality, Good for code
Verdict: Llama 3.1 405B vs Voyage Large 2
For cost efficiency, Voyage Large 2 wins at $0.002/1M input tokens. For speed, Voyage Large 2 is faster at ~25ms. Llama 3.1 405B excels at Premium tasks while Voyage Large 2 is better for Code search. 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. Voyage Large 2 costs $0.002 input and N/A output. Voyage Large 2 is 40.0x 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. Voyage Large 2 offers 16K context at ~25ms. 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. Voyage Large 2 (Embedding) works best for: Code search, Long document RAG, Semantic matching.
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 Voyage Large 2
response_b = client.chat.completions.create(
model="voyage-large-2",
messages=[{"role": "user", "content": "Your question here"}]
)
Frequently Asked Questions
Which is better, Llama 3.1 405B or Voyage Large 2?
Llama 3.1 405B (Open Source, 405B) offers Largest open model. Voyage Large 2 (Embedding, ~500M) offers 16K context. Choose Llama 3.1 405B for Premium tasks or Voyage Large 2 for Code search.
How much does Llama 3.1 405B cost vs Voyage Large 2?
Llama 3.1 405B: $0.08/1M input, $0.14/1M output. Voyage Large 2: $0.002/1M input, N/A/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 Voyage Large 2 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.