Codestral vs Yi Large

Compare Codestral 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

All Mistral models All 01.AI models What is an LLM API? Python Quickstart What is inference?
Feature Codestral Yi Large
CategoryCodeOpen Source
Parameters22B300B
Context Window256K200K
Input Price$0.03/1M tokens$0.06/1M tokens
Output Price$0.05/1M tokens$0.12/1M tokens
Latency~200ms~450ms

Choose Codestral when:

  • ✓ API integration code
  • ✓ SDK generation
  • ✓ Code review
Key Strengths:

256K context for code, Strong code generation, Good APIs

Choose Yi Large when:

  • ✓ Long document analysis
  • ✓ Research
  • ✓ Complex tasks
Key Strengths:

200K context, Strong analysis, Good reasoning

Verdict: Codestral vs Yi Large

For cost efficiency, Codestral wins at $0.03/1M input tokens. For speed, Codestral is faster at ~200ms. Codestral excels at API integration code 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

Codestral costs $0.03/1M input tokens and $0.05/1M output tokens. Yi Large costs $0.06 input and $0.12 output. Codestral is 2.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Codestral has a 256K context window with ~200ms latency. Yi Large offers 200K context at ~450ms. Codestral has the larger context window.

Best For

Codestral (Code) is optimized for: API integration code, SDK generation, Code review. 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 Codestral
response_a = client.chat.completions.create(
    model="codestral",
    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"}]
)

Start Building with XALEN

200+ AI models. One API. Pay-as-you-go.

Get API Key Try in Playground

Frequently Asked Questions

Which is better, Codestral or Yi Large?

Codestral (Code, 22B) offers 256K context for code. Yi Large (Open Source, 300B) offers 200K context. Choose Codestral for API integration code or Yi Large for Long document analysis.

How much does Codestral cost vs Yi Large?

Codestral: $0.03/1M input, $0.05/1M 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 Codestral and Yi Large 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.