GLM vs Gemma

Head-to-Head Performance Audit

GLM

GLM

Z.AI

Z AI coding model scoring 94.6% of Claude Opus on SWE-Bench

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Gemma

Gemma

Google DeepMind

Google's lightweight open model family powered by Gemini technology

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Intelligence Fingerprint

GLM-5.1 (Reasoning)

GLM-5.1 (Reasoning) by Z AI. Optimized for high intelligence.

Gemma 4 31B (Reasoning)

Gemma 4 31B (Reasoning) by Google. Optimized for efficiency.

Competitive Edge

GLM Verdict

Key Strengths

  • 94.6% of Claude coding performance
  • 28% improvement in single update
  • Open-source options
  • Competitive pricing

Limitations

  • China-based service
  • Smaller community
  • Less general capability

Gemma Verdict

Key Strengths

  • Apache 2.0 license (commercial use)
  • #3 Open Model on Arena AI
  • Phone-to-Workstation scalability
  • Native Gemini 3 research inside

Limitations

  • Smaller context than proprietary Gemini
  • Resource heavy for 31B on mobile

Where to Choose Which?

Select GLM for:

  • Coding tasks
  • Chinese developers
  • Budget-conscious teams
  • SWE-Bench style problems

Select Gemma for:

  • Open-source developers
  • Local RAG implementations
  • Edge device AI
  • Academic research

Frequently Asked Questions

Is GLM better than Gemma?
Based on our benchmark analysis, Gemma scores higher on average across key metrics (SWE-Bench, GPQA Diamond, ARC-AGI-2) with a composite average of 65.3% vs 61.0%. However, GLM may still be the better choice depending on your specific use case and budget.
Which is better for coding, GLM or Gemma?
GLM scores 77.8% on SWE-Bench Verified compared to Gemma's 72.1%. SWE-Bench measures real-world GitHub issue resolution, making it the most reliable coding benchmark. GLM is the stronger choice for developers.
How does GLM pricing compare to Gemma?
GLM starts at Free (freemium) while Gemma starts at Free (open-source). Gemma offers a completely free tier.
When should I choose GLM over Gemma?
Choose GLM when you need Coding tasks or Chinese developers. Choose Gemma when your priority is Open-source developers or Local RAG implementations. Both tools serve different strengths depending on your workflow.
GLM vs Gemma | AI Performance Comparison 2026 | RQR Benchmarks