Text Embedding 3 Large vs Llama 3.3 70B
Compare Text Embedding 3 Large and Llama 3.3 70B: 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 | Text Embedding 3 Large | Llama 3.3 70B |
|---|---|---|
| Category | Embedding | Open Source |
| Parameters | ~500M | 70B |
| Context Window | 8K | 128K |
| Input Price | $0.002/1M tokens | $0.04/1M tokens |
| Output Price | N/A/1M tokens | $0.06/1M tokens |
| Latency | ~20ms | ~300ms |
Choose Text Embedding 3 Large when:
- ✓ Semantic search
- ✓ Knowledge retrieval
- ✓ Similarity matching
3072 dimensions, Superior semantic quality, Matryoshka support
Choose Llama 3.3 70B when:
- ✓ General Q&A
- ✓ Hindi chatbots
- ✓ Content generation
Proven reliability, Good Hindi/Tamil, 128K context
Verdict: Text Embedding 3 Large vs Llama 3.3 70B
For cost efficiency, Text Embedding 3 Large wins at $0.002/1M input tokens. For speed, Text Embedding 3 Large is faster at ~20ms. Text Embedding 3 Large excels at Semantic search while Llama 3.3 70B is better for General Q&A. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.
Detailed Analysis
Pricing Comparison
Text Embedding 3 Large costs $0.002/1M input tokens and N/A/1M output tokens. Llama 3.3 70B costs $0.04 input and $0.06 output. Text Embedding 3 Large is 20.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Text Embedding 3 Large has a 8K context window with ~20ms latency. Llama 3.3 70B offers 128K context at ~300ms. Llama 3.3 70B has the larger context window.
Best For
Text Embedding 3 Large (Embedding) is optimized for: Semantic search, Knowledge retrieval, Similarity matching. Llama 3.3 70B (Open Source) works best for: General Q&A, Hindi chatbots, Content generation.
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 Text Embedding 3 Large
response_a = client.chat.completions.create(
model="text-embedding-3-large",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use Llama 3.3 70B
response_b = client.chat.completions.create(
model="llama-3-3-70b",
messages=[{"role": "user", "content": "Your question here"}]
)
Frequently Asked Questions
Which is better, Text Embedding 3 Large or Llama 3.3 70B?
Text Embedding 3 Large (Embedding, ~500M) offers 3072 dimensions. Llama 3.3 70B (Open Source, 70B) offers Proven reliability. Choose Text Embedding 3 Large for Semantic search or Llama 3.3 70B for General Q&A.
How much does Text Embedding 3 Large cost vs Llama 3.3 70B?
Text Embedding 3 Large: $0.002/1M input, N/A/1M output. Llama 3.3 70B: $0.04/1M input, $0.06/1M 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 Text Embedding 3 Large and Llama 3.3 70B 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.