Mistral Small 3 vs CodeGemma 7B

Compare Mistral Small 3 and CodeGemma 7B: pricing, performance, context window, latency, and best use cases. Side-by-side comparison on XALEN.

Updated 2026-05-21 · By Abhishek Raj · Our methodology

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Feature Mistral Small 3 CodeGemma 7B
CategoryCompactCode
Parameters24B7B
Context Window32K8K
Input Price$0.02/1M tokens$0.008/1M tokens
Output Price$0.04/1M tokens$0.015/1M tokens
Latency~150ms~60ms

Choose Mistral Small 3 when:

  • ✓ Content classification
  • ✓ Intent detection
  • ✓ Preprocessing
Key Strengths:

Very fast, Low cost, Good classification

Choose CodeGemma 7B when:

  • ✓ Code completion
  • ✓ Simple generation
  • ✓ Editor plugins
Key Strengths:

Compact, Fast code completion, Open weights

Verdict: Mistral Small 3 vs CodeGemma 7B

For cost efficiency, CodeGemma 7B wins at $0.008/1M input tokens. For speed, Mistral Small 3 is faster at ~150ms. Mistral Small 3 excels at Content classification while CodeGemma 7B is better for Code completion. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.

Detailed Analysis

Pricing Comparison

Mistral Small 3 costs $0.02/1M input tokens and $0.04/1M output tokens. CodeGemma 7B costs $0.008 input and $0.015 output. CodeGemma 7B is 2.5x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Mistral Small 3 has a 32K context window with ~150ms latency. CodeGemma 7B offers 8K context at ~60ms. Mistral Small 3 has the larger context window.

Best For

Mistral Small 3 (Compact) is optimized for: Content classification, Intent detection, Preprocessing. CodeGemma 7B (Code) works best for: Code completion, Simple generation, Editor plugins.

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 Mistral Small 3
response_a = client.chat.completions.create(
    model="mistral-small-3",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use CodeGemma 7B
response_b = client.chat.completions.create(
    model="codegemma-7b",
    messages=[{"role": "user", "content": "Your question here"}]
)

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Frequently Asked Questions

Which is better, Mistral Small 3 or CodeGemma 7B?

Mistral Small 3 (Compact, 24B) offers Very fast. CodeGemma 7B (Code, 7B) offers Compact. Choose Mistral Small 3 for Content classification or CodeGemma 7B for Code completion.

How much does Mistral Small 3 cost vs CodeGemma 7B?

Mistral Small 3: $0.02/1M input, $0.04/1M output. CodeGemma 7B: $0.008/1M input, $0.015/1M 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 Mistral Small 3 and CodeGemma 7B 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.