Jina Embeddings v3 vs WizardLM 2 8x22B
Compare Jina Embeddings v3 and WizardLM 2 8x22B: 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 | Jina Embeddings v3 | WizardLM 2 8x22B |
|---|---|---|
| Category | Embedding | Open Source |
| Parameters | ~300M | 176B (22B active) |
| Context Window | 8K | 65K |
| Input Price | $0.002/1M tokens | $0.04/1M tokens |
| Output Price | N/A/1M tokens | $0.08/1M tokens |
| Latency | ~15ms | ~350ms |
Choose Jina Embeddings v3 when:
- ✓ Multilingual search
- ✓ Cross-language RAG
- ✓ Semantic matching
Strong multilingual, Good for RAG, Flexible dimensions
Choose WizardLM 2 8x22B when:
- ✓ Complex instructions
- ✓ Math tasks
- ✓ Structured output
Strong instruction following, Good math, MoE efficient
Verdict: Jina Embeddings v3 vs WizardLM 2 8x22B
For cost efficiency, Jina Embeddings v3 wins at $0.002/1M input tokens. For speed, Jina Embeddings v3 is faster at ~15ms. Jina Embeddings v3 excels at Multilingual search while WizardLM 2 8x22B is better for Complex instructions. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.
Detailed Analysis
Pricing Comparison
Jina Embeddings v3 costs $0.002/1M input tokens and N/A/1M output tokens. WizardLM 2 8x22B costs $0.04 input and $0.08 output. Jina Embeddings v3 is 20.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Jina Embeddings v3 has a 8K context window with ~15ms latency. WizardLM 2 8x22B offers 65K context at ~350ms. WizardLM 2 8x22B has the larger context window.
Best For
Jina Embeddings v3 (Embedding) is optimized for: Multilingual search, Cross-language RAG, Semantic matching. WizardLM 2 8x22B (Open Source) works best for: Complex instructions, Math tasks, Structured output.
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 Jina Embeddings v3
response_a = client.chat.completions.create(
model="jina-embeddings-v3",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use WizardLM 2 8x22B
response_b = client.chat.completions.create(
model="wizardlm-2-8x22b",
messages=[{"role": "user", "content": "Your question here"}]
)
Frequently Asked Questions
Which is better, Jina Embeddings v3 or WizardLM 2 8x22B?
Jina Embeddings v3 (Embedding, ~300M) offers Strong multilingual. WizardLM 2 8x22B (Open Source, 176B (22B active)) offers Strong instruction following. Choose Jina Embeddings v3 for Multilingual search or WizardLM 2 8x22B for Complex instructions.
How much does Jina Embeddings v3 cost vs WizardLM 2 8x22B?
Jina Embeddings v3: $0.002/1M input, N/A/1M output. WizardLM 2 8x22B: $0.04/1M input, $0.08/1M 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 Jina Embeddings v3 and WizardLM 2 8x22B 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.