Llama 3.1 405B vs DeepSeek V2.5
Compare Llama 3.1 405B and DeepSeek V2.5: 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 V2.5 |
|---|---|---|
| Category | Open Source | Open Source |
| Parameters | 405B | 236B (21B active) |
| Context Window | 128K | 128K |
| Input Price | $0.08/1M tokens | $0.04/1M tokens |
| Output Price | $0.14/1M tokens | $0.07/1M tokens |
| Latency | ~600ms | ~350ms |
Choose Llama 3.1 405B when:
- ✓ Premium tasks
- ✓ Research
- ✓ Fine-tuning base
Largest open model, Highest open-source quality
Choose DeepSeek V2.5 when:
- ✓ General purpose
- ✓ Code generation
- ✓ Legacy apps
Proven model, MoE efficient, Good coding
Verdict: Llama 3.1 405B vs DeepSeek V2.5
For cost efficiency, DeepSeek V2.5 wins at $0.04/1M input tokens. For speed, DeepSeek V2.5 is faster at ~350ms. Llama 3.1 405B excels at Premium tasks while DeepSeek V2.5 is better for General purpose. 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 V2.5 costs $0.04 input and $0.07 output. DeepSeek V2.5 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. DeepSeek V2.5 offers 128K context at ~350ms. Both have identical context windows.
Best For
Llama 3.1 405B (Open Source) is optimized for: Premium tasks, Research, Fine-tuning base. DeepSeek V2.5 (Open Source) works best for: General purpose, Code generation, Legacy apps.
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 V2.5
response_b = client.chat.completions.create(
model="deepseek-v2-5",
messages=[{"role": "user", "content": "Your question here"}]
)
Frequently Asked Questions
Which is better, Llama 3.1 405B or DeepSeek V2.5?
Llama 3.1 405B (Open Source, 405B) offers Largest open model. DeepSeek V2.5 (Open Source, 236B (21B active)) offers Proven model. Choose Llama 3.1 405B for Premium tasks or DeepSeek V2.5 for General purpose.
How much does Llama 3.1 405B cost vs DeepSeek V2.5?
Llama 3.1 405B: $0.08/1M input, $0.14/1M output. DeepSeek V2.5: $0.04/1M input, $0.07/1M 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 V2.5 by changing the model parameter. No code changes needed.
Related Comparisons
Last updated: 2026-05-21. Pricing and specifications may change. Check pricing page for latest rates.