Qwen 2.5 72B Turbo vs Codestral
Compare Qwen 2.5 72B Turbo 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 2.5 72B Turbo | Codestral |
|---|---|---|
| Category | Open Source | Code |
| Parameters | 72B | 22B |
| Context Window | 128K | 256K |
| Input Price | $0.04/1M tokens | $0.03/1M tokens |
| Output Price | $0.08/1M tokens | $0.05/1M tokens |
| Latency | ~300ms | ~200ms |
Choose Qwen 2.5 72B Turbo when:
- ✓ Pan-India apps
- ✓ Multilingual Q&A
- ✓ Content generation
Strong Asian languages, Good reasoning, Fast inference
Choose Codestral when:
- ✓ API integration code
- ✓ SDK generation
- ✓ Code review
256K context for code, Strong code generation, Good APIs
Verdict: Qwen 2.5 72B Turbo vs Codestral
For cost efficiency, Codestral wins at $0.03/1M input tokens. For speed, Codestral is faster at ~200ms. Qwen 2.5 72B Turbo excels at Pan-India apps 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 2.5 72B Turbo costs $0.04/1M input tokens and $0.08/1M output tokens. Codestral costs $0.03 input and $0.05 output. Codestral is 1.3x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Qwen 2.5 72B Turbo has a 128K context window with ~300ms latency. Codestral offers 256K context at ~200ms. Codestral has the larger context window.
Best For
Qwen 2.5 72B Turbo (Open Source) is optimized for: Pan-India apps, Multilingual Q&A, Content generation. 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 2.5 72B Turbo
response_a = client.chat.completions.create(
model="qwen-2-5-72b-turbo",
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 2.5 72B Turbo or Codestral?
Qwen 2.5 72B Turbo (Open Source, 72B) offers Strong Asian languages. Codestral (Code, 22B) offers 256K context for code. Choose Qwen 2.5 72B Turbo for Pan-India apps or Codestral for API integration code.
How much does Qwen 2.5 72B Turbo cost vs Codestral?
Qwen 2.5 72B Turbo: $0.04/1M input, $0.08/1M 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 2.5 72B Turbo 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.