Qwen 3 235B vs Yi Large
Compare Qwen 3 235B and Yi Large: 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 | Qwen 3 235B | Yi Large |
|---|---|---|
| Category | Open Source | Open Source |
| Parameters | 235B (22B active) | 300B |
| Context Window | 128K | 200K |
| Input Price | $0.06/1M tokens | $0.06/1M tokens |
| Output Price | $0.10/1M tokens | $0.12/1M tokens |
| Latency | ~350ms | ~450ms |
Choose Qwen 3 235B when:
- ✓ Pan-India multilingual
- ✓ Regional chatbots
- ✓ Translation
Exceptional Asian languages, Strong Hindi/Bengali/Tamil, MoE efficiency
Choose Yi Large when:
- ✓ Long document analysis
- ✓ Research
- ✓ Complex tasks
200K context, Strong analysis, Good reasoning
Verdict: Qwen 3 235B vs Yi Large
For cost efficiency, Yi Large wins at $0.06/1M input tokens. For speed, Qwen 3 235B is faster at ~350ms. Qwen 3 235B excels at Pan-India multilingual while Yi Large is better for Long document 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
Qwen 3 235B costs $0.06/1M input tokens and $0.10/1M output tokens. Yi Large costs $0.06 input and $0.12 output. Both models are similarly priced. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Qwen 3 235B has a 128K context window with ~350ms latency. Yi Large offers 200K context at ~450ms. Yi Large has the larger context window.
Best For
Qwen 3 235B (Open Source) is optimized for: Pan-India multilingual, Regional chatbots, Translation. Yi Large (Open Source) works best for: Long document analysis, Research, Complex tasks.
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 Qwen 3 235B
response_a = client.chat.completions.create(
model="qwen-3-235b",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use Yi Large
response_b = client.chat.completions.create(
model="yi-large",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Qwen 3 235B or Yi Large?
Qwen 3 235B (Open Source, 235B (22B active)) offers Exceptional Asian languages. Yi Large (Open Source, 300B) offers 200K context. Choose Qwen 3 235B for Pan-India multilingual or Yi Large for Long document analysis.
How much does Qwen 3 235B cost vs Yi Large?
Qwen 3 235B: $0.06/1M input, $0.10/1M output. Yi Large: $0.06/1M input, $0.12/1M 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 Qwen 3 235B and Yi Large by changing the model parameter. No code changes needed.
Related Comparisons
Last updated: 2026-05-21. Pricing and specifications may change. Check pricing page for latest rates.