Vedika Vision vs Llama 3.1 405B
Compare Vedika Vision and Llama 3.1 405B: 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 | Vedika Vision | Llama 3.1 405B |
|---|---|---|
| Category | Vision | Open Source |
| Parameters | 26B | 405B |
| Context Window | 32K | 128K |
| Input Price | $0.08/1M tokens | $0.08/1M tokens |
| Output Price | $0.12/1M tokens | $0.14/1M tokens |
| Latency | ~500ms | ~600ms |
Choose Vedika Vision when:
- ✓ Chart image analysis
- ✓ Temple photo description
- ✓ Vastu photo analysis
Chart image analysis, Yantra recognition, Sacred geometry
Choose Llama 3.1 405B when:
- ✓ Premium tasks
- ✓ Research
- ✓ Fine-tuning base
Largest open model, Highest open-source quality
Verdict: Vedika Vision vs Llama 3.1 405B
For cost efficiency, Llama 3.1 405B wins at $0.08/1M input tokens. For speed, Vedika Vision is faster at ~500ms. Vedika Vision excels at Chart image analysis while Llama 3.1 405B is better for Premium tasks. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.
Detailed Analysis
Pricing Comparison
Vedika Vision costs $0.08/1M input tokens and $0.12/1M output tokens. Llama 3.1 405B 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
Vedika Vision has a 32K context window with ~500ms latency. Llama 3.1 405B offers 128K context at ~600ms. Llama 3.1 405B has the larger context window.
Best For
Vedika Vision (Vision) is optimized for: Chart image analysis, Temple photo description, Vastu photo analysis. Llama 3.1 405B (Open Source) works best for: Premium tasks, Research, Fine-tuning base.
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 Vedika Vision
response_a = client.chat.completions.create(
model="vedika-vision",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use Llama 3.1 405B
response_b = client.chat.completions.create(
model="llama-3-1-405b",
messages=[{"role": "user", "content": "Your question here"}]
)
Frequently Asked Questions
Which is better, Vedika Vision or Llama 3.1 405B?
Vedika Vision (Vision, 26B) offers Chart image analysis. Llama 3.1 405B (Open Source, 405B) offers Largest open model. Choose Vedika Vision for Chart image analysis or Llama 3.1 405B for Premium tasks.
How much does Vedika Vision cost vs Llama 3.1 405B?
Vedika Vision: $0.08/1M input, $0.12/1M output. Llama 3.1 405B: $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 Vedika Vision and Llama 3.1 405B 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.