Llama 3.1 405B vs DeepSeek V3
Compare Llama 3.1 405B and DeepSeek V3: 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 | DeepSeek V3 |
|---|---|---|
| Category | Open Source | Open Source |
| Parameters | 405B | 671B (37B active) |
| Context Window | 128K | 128K |
| Input Price | $0.08/1M tokens | $0.05/1M tokens |
| Output Price | $0.14/1M tokens | $0.09/1M tokens |
| Latency | ~600ms | ~400ms |
Choose Llama 3.1 405B when:
- ✓ Premium tasks
- ✓ Research
- ✓ Fine-tuning base
Largest open model, Highest open-source quality
Choose DeepSeek V3 when:
- ✓ API response generation
- ✓ High-volume processing
- ✓ Code
MoE efficiency, Strong coding, Good structured output
Verdict: Llama 3.1 405B vs DeepSeek V3
For cost efficiency, DeepSeek V3 wins at $0.05/1M input tokens. For speed, DeepSeek V3 is faster at ~400ms. Llama 3.1 405B excels at Premium tasks while DeepSeek V3 is better for API response generation. 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. DeepSeek V3 costs $0.05 input and $0.09 output. DeepSeek V3 is 1.6x 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. DeepSeek V3 offers 128K context at ~400ms. Both have identical context windows.
Best For
Llama 3.1 405B (Open Source) is optimized for: Premium tasks, Research, Fine-tuning base. DeepSeek V3 (Open Source) works best for: API response generation, High-volume processing, Code.
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 DeepSeek V3
response_b = client.chat.completions.create(
model="deepseek-v3",
messages=[{"role": "user", "content": "Your question here"}]
)
Frequently Asked Questions
Which is better, Llama 3.1 405B or DeepSeek V3?
Llama 3.1 405B (Open Source, 405B) offers Largest open model. DeepSeek V3 (Open Source, 671B (37B active)) offers MoE efficiency. Choose Llama 3.1 405B for Premium tasks or DeepSeek V3 for API response generation.
How much does Llama 3.1 405B cost vs DeepSeek V3?
Llama 3.1 405B: $0.08/1M input, $0.14/1M output. DeepSeek V3: $0.05/1M input, $0.09/1M 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 DeepSeek V3 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.