o4-mini vs Llama 3.2 90B Vision
Compare o4-mini and Llama 3.2 90B Vision: 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 | o4-mini | Llama 3.2 90B Vision |
|---|---|---|
| Category | Reasoning | Vision |
| Parameters | ~200B | 90B |
| Context Window | 200K | 128K |
| Input Price | $0.03/1M tokens | $0.06/1M tokens |
| Output Price | $0.12/1M tokens | $0.10/1M tokens |
| Latency | ~800ms | ~500ms |
Choose o4-mini when:
- ✓ Kundali scoring
- ✓ Compatibility analysis
- ✓ Decision systems
Fast reasoning, Cost-efficient, 200K context
Choose Llama 3.2 90B Vision when:
- ✓ Chart image analysis
- ✓ Document scanning
- ✓ Visual Q&A
Vision + language, Open weights, Good reasoning
Verdict: o4-mini vs Llama 3.2 90B Vision
For cost efficiency, o4-mini wins at $0.03/1M input tokens. For speed, Llama 3.2 90B Vision is faster at ~500ms. o4-mini excels at Kundali scoring while Llama 3.2 90B Vision is better for Chart image analysis. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.
Detailed Analysis
Pricing Comparison
o4-mini costs $0.03/1M input tokens and $0.12/1M output tokens. Llama 3.2 90B Vision costs $0.06 input and $0.10 output. o4-mini is 2.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
o4-mini has a 200K context window with ~800ms latency. Llama 3.2 90B Vision offers 128K context at ~500ms. o4-mini has the larger context window.
Best For
o4-mini (Reasoning) is optimized for: Kundali scoring, Compatibility analysis, Decision systems. Llama 3.2 90B Vision (Vision) works best for: Chart image analysis, Document scanning, Visual Q&A.
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 o4-mini
response_a = client.chat.completions.create(
model="o4-mini",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use Llama 3.2 90B Vision
response_b = client.chat.completions.create(
model="llama-3-2-90b-vision",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, o4-mini or Llama 3.2 90B Vision?
o4-mini (Reasoning, ~200B) offers Fast reasoning. Llama 3.2 90B Vision (Vision, 90B) offers Vision + language. Choose o4-mini for Kundali scoring or Llama 3.2 90B Vision for Chart image analysis.
How much does o4-mini cost vs Llama 3.2 90B Vision?
o4-mini: $0.03/1M input, $0.12/1M output. Llama 3.2 90B Vision: $0.06/1M input, $0.10/1M 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 o4-mini and Llama 3.2 90B Vision 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.