Gemma

Gemma Review 2026: Pricing, Benchmarks & Alternatives

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Google DeepMind

Google's lightweight open model family powered by Gemini technology

Category

chatbots

Starting At

Open Source

API

Available

Updated

2026-04-02

Open-source developersLocal RAG implementationsEdge device AIAcademic research

Model Variants

16 variants · Select to compare specs

Capability Fingerprint

Gemma 4 31B (Reasoning)

Speed

balanced

Intelligence

medium

Context

128k

Pricing

$0.00 / 1M tokens

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

Benchmarks

8 metrics
Swe Bench Verified
38.7%
Gpqa Diamond
85.7%
Hle
22.7%
Arc A G I2
59.9%
Human Eval
43.4%
Mmlu
39.2%
Terminal Bench
36.4%
Speed
35.1%

Our Verdict

Gemma 4 is Google's leading open-weights model family. The 4.3 Beta model ranks high locally on the Arena AI leaderboard, offering frontier reasoning and coding capabilities under an Apache 2.0 license.

Who should use Gemma: This tool excels for Open-source developers, Local RAG implementations, Edge device AI. Being open-source means no vendor lock-in and full control over your data. The #3 Open Model globally (Arena AI) pricing positions itcompetitively in the market.

Benchmark Analysis

Based on 8+ independent benchmarks, here's how Gemma performs:

SWE-Bench
38.7%
Real-world coding tasks
ARC-AGI-2
59.9%
Abstract reasoning
GPQA Diamond
85.7%
Expert-level QA

Note: Benchmarks are verified against official vendor claims and independent testing. Scores last updated 2026-04-02. See our methodology for details.

Company Overview

Google DeepMind was founded in 2024 and is based in Mountain View, CA.Gemma is released under an open-source license, which means anyone can inspect the code, modify it, or deploy it privately without licensing fees.

Should you use Gemma?

Use it if:
  • Open-source developers
  • Local RAG implementations
  • Edge device AI
Avoid if:
  • Smaller context than proprietary Gemini
  • Resource heavy for 31B on mobile

Key Advantages

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

Known Constraints

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

Head-to-Head Comparisons

See how Gemma stacks up against its closest competitors with detailed benchmark analysis, pricing breakdowns, and expert verdicts.

Benchmark Comparison

Real performance data from independent testing

Metric
GemmaThis
Gemini
Claude
ChatGPT
SiteSiteSiteSite
SWE-Bench (Coding)
72.1%
80.6%
87.6%
80.1%
Terminal Success (Agents)
58.4%
68.5%
69.4%
75.1%
Unit Logic (HumanEval)
88.2%
94.1%
94.5%
92.4%
GPQA Diamond (Science)
94.3%
94.2%
94.4%
MATH (Reasoning)
82.5%
96.2%
95.8%
93.8%
MMLU (Knowledge)
84.5%
92.6%
91.5%
88.2%
Code Arena (ELO)
1861
1650
1678
Chat Arena (ELO)
1421
1455
1583
1457
Context
256K tokens
1M tokens
1M tokens
1M tokens
Price
Open SourceFreemiumFreemiumFreemium
Best For
CodingReasoningAgenticValue
CodingReasoningAgenticValue
CodingReasoningAgentic
CodingReasoningAgentic
Gemma:#3 Open Model globally (Arena AI)
Gemini:#1 on ARC-AGI-2 (77.1%)
Claude:#1 on SWE-Bench Verified (87.6%)
ChatGPT:Best for agentic tasks (75.1% Terminal-Bench)
Data from March 2026 independent benchmarksFull comparison

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