Qwen 3 235B vs Codestral
Compare Qwen 3 235B and Codestral: 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 | Codestral |
|---|---|---|
| Category | Open Source | Code |
| Parameters | 235B (22B active) | 22B |
| Context Window | 128K | 256K |
| Input Price | $0.06/1M tokens | $0.03/1M tokens |
| Output Price | $0.10/1M tokens | $0.05/1M tokens |
| Latency | ~350ms | ~200ms |
Choose Qwen 3 235B when:
- ✓ Pan-India multilingual
- ✓ Regional chatbots
- ✓ Translation
Exceptional Asian languages, Strong Hindi/Bengali/Tamil, MoE efficiency
Choose Codestral when:
- ✓ API integration code
- ✓ SDK generation
- ✓ Code review
256K context for code, Strong code generation, Good APIs
Verdict: Qwen 3 235B vs Codestral
For cost efficiency, Codestral wins at $0.03/1M input tokens. For speed, Codestral is faster at ~200ms. Qwen 3 235B excels at Pan-India multilingual while Codestral is better for API integration code. 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. Codestral costs $0.03 input and $0.05 output. Codestral is 2.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Qwen 3 235B has a 128K context window with ~350ms latency. Codestral offers 256K context at ~200ms. Codestral has the larger context window.
Best For
Qwen 3 235B (Open Source) is optimized for: Pan-India multilingual, Regional chatbots, Translation. Codestral (Code) works best for: API integration code, SDK generation, Code review.
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 Codestral
response_b = client.chat.completions.create(
model="codestral",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Qwen 3 235B or Codestral?
Qwen 3 235B (Open Source, 235B (22B active)) offers Exceptional Asian languages. Codestral (Code, 22B) offers 256K context for code. Choose Qwen 3 235B for Pan-India multilingual or Codestral for API integration code.
How much does Qwen 3 235B cost vs Codestral?
Qwen 3 235B: $0.06/1M input, $0.10/1M output. Codestral: $0.03/1M input, $0.05/1M 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 Codestral 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.