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AI Tool Comparison

Cerebras Inference vs Gemma 3

A side-by-side breakdown to help you pick the right tool for your workflow.

Cerebras Inference logo

Cerebras Inference

Run Llama 70B at 1,800 tokens per second — 20x faster than GPU alternatives. The only inference provider where speed itself is the competitive moat.

Models
freemium
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Gemma 3 logo

Gemma 3

Superseded by Gemma 4 (April 2026) — Gemini-3-derived reasoning and agentic capability in five open sizes from 2B to 31B, running on phones, laptops, or servers with a 256K context window.

Models
free
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Bottom Line

Cerebras Inference edges ahead on rating (4.7 vs 4.5), but the right pick still comes down to which workflow you're running.

Choose Cerebras Inference if…

Coding

Choose Gemma 3 if…

Models

AttributeCerebras InferenceGemma 3
CategoryModelsModels
Pricingfreemiumfree
Pricing DetailFree tier available / Pay-per-tokenFree and open-weight (Apache 2.0) — now on Gemma 4
Rating4.74.5

Key Features

Cerebras Inference

  • 1,800+ tokens/second on Llama 3.1 70B — fastest available
  • Wafer-scale chip architecture eliminates inter-chip communication overhead
  • Supports Llama 3.1, 3.3, DeepSeek R1, and Qwen models
  • OpenAI-compatible API with streaming support
  • Free tier for prototyping with no credit card required
  • Real-time performance suitable for voice and interactive applications

Gemma 3

  • Open weights
  • Multilingual and multimodal
  • Multiple sizes
  • Runs on single GPU

Pros

Cerebras Inference

  • Fastest inference in the industry by a wide margin
  • Free tier is genuinely useful, not just a trial
  • OpenAI-compatible — drops into existing code immediately

Gemma 3

  • High quality and open
  • Good documentation
  • Flexible sizes

Cons

Cerebras Inference

  • Model selection is limited to a curated set, not the full open-source catalog
  • Purpose-built hardware means no custom model fine-tuning support
  • Very high throughput can mask context window limitations

Gemma 3

  • Self-hosting expertise needed
  • Behind frontier closed models

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