WizardLM 2 8x22B vs Cohere Embed v4
Compare WizardLM 2 8x22B and Cohere Embed v4: 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 | WizardLM 2 8x22B | Cohere Embed v4 |
|---|---|---|
| Category | Open Source | Embedding |
| Parameters | 176B (22B active) | ~400M |
| Context Window | 65K | 128K |
| Input Price | $0.04/1M tokens | $0.001/1M tokens |
| Output Price | $0.08/1M tokens | N/A/1M tokens |
| Latency | ~350ms | ~15ms |
Choose WizardLM 2 8x22B when:
- ✓ Complex instructions
- ✓ Math tasks
- ✓ Structured output
Strong instruction following, Good math, MoE efficient
Choose Cohere Embed v4 when:
- ✓ Long document RAG
- ✓ Multimodal search
- ✓ Large knowledge bases
128K context, Multimodal embedding, Matryoshka
Verdict: WizardLM 2 8x22B vs Cohere Embed v4
For cost efficiency, Cohere Embed v4 wins at $0.001/1M input tokens. For speed, Cohere Embed v4 is faster at ~15ms. WizardLM 2 8x22B excels at Complex instructions while Cohere Embed v4 is better for Long document RAG. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.
Detailed Analysis
Pricing Comparison
WizardLM 2 8x22B costs $0.04/1M input tokens and $0.08/1M output tokens. Cohere Embed v4 costs $0.001 input and N/A output. Cohere Embed v4 is 40.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
WizardLM 2 8x22B has a 65K context window with ~350ms latency. Cohere Embed v4 offers 128K context at ~15ms. Cohere Embed v4 has the larger context window.
Best For
WizardLM 2 8x22B (Open Source) is optimized for: Complex instructions, Math tasks, Structured output. Cohere Embed v4 (Embedding) works best for: Long document RAG, Multimodal search, Large knowledge bases.
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 WizardLM 2 8x22B
response_a = client.chat.completions.create(
model="wizardlm-2-8x22b",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use Cohere Embed v4
response_b = client.chat.completions.create(
model="embed-v4",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, WizardLM 2 8x22B or Cohere Embed v4?
WizardLM 2 8x22B (Open Source, 176B (22B active)) offers Strong instruction following. Cohere Embed v4 (Embedding, ~400M) offers 128K context. Choose WizardLM 2 8x22B for Complex instructions or Cohere Embed v4 for Long document RAG.
How much does WizardLM 2 8x22B cost vs Cohere Embed v4?
WizardLM 2 8x22B: $0.04/1M input, $0.08/1M output. Cohere Embed v4: $0.001/1M input, N/A/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 WizardLM 2 8x22B and Cohere Embed v4 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.