Head-to-Head Model Comparison

Gemma 3 vs Gemma 2

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale

Cambia e Confronta Qualsiasi Modello

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Gemma 3Profile

Gemma 2Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Google

Gemma 3

IA Multimodale Nativa

Gemma 3 di Google è un modello di IA progettato per la comprensione multimodale nativa di testo e immagini e l’analisi visiva dei documenti, con finestra di contesto da 131K, velocità di 105 token/s, indice di intelligenza di 68/100 e tarif

Intelligence Index68 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

131.1K tokens

SWE-bench Verified:

N/A

Google

Gemma 2

Modello Base a Pesi Aperti

Gemma 2 di Google è un modello di IA progettato per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, con finestra di contesto da 8K, velocità di 110 token/s, indice di intelligenza di 58/100 e tariffa

Intelligence Index58 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

8.2K tokens

SWE-bench Verified:

N/A

Differenze Chiave a Colpo d’Occhio

Both models cost the same under this workload — choose on capability, not price.
Gemma 3 has a larger context window (131K vs 8K tokens).
Gemma 2 is faster at 110 tok/s vs 105 tok/s.

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Feature	Gemma 3	Gemma 2
Intelligence Index Composite reasoning & knowledge score (0-100)	68	58
Provider	Google	Google
Input Price Cost per million input tokens	$0.00 / 1M	$0.00 / 1M
Output Price Cost per million output tokens	$0.00 / 1M	$0.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.00 / 1M	$0.00 / 1M
Context Window Maximum input + output tokens	131.1K tokens~197 A4 pages of text	8.2K tokens~12 A4 pages of text
Max Output Tokens Per single request	16K	4K
Throughput Speed Tokens generated per second	105 tok/s	110 tok/s
SWE-bench Verified Real-world software engineering	N/A	N/A
GPQA Diamond Graduate-level reasoning	61%	N/A

Chi vince in ogni categoria?

At-a-glance decision framework

Coding

Evaluations ongoing

Cost

Tied

Identical monthly runtime cost

Speed

Gemma 2

+5% faster generation

Context

Gemma 3

131.1K tokens window

Punteggi Benchmark Verificati

Official evaluation metrics verified by independent third-party research labs.

Gemma 3Gemma 2

GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

61%vsN/A

MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

78%vs68.5%

LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1335ptsvs1250pts

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

105 tok/s vs110 tok/s

Latenza e Tempo di Risposta

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better

Gemma 30.32s

Gemma 20.30s

Est. End-to-End Response (500 tokens)TTFT + generation time

Gemma 35.08s

Gemma 24.85s

Simulatore Interattivo dei Costi Token

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% cached

0% (Cold)50%90% (Warm)

Gemma 3 Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

Gemma 2 Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

These models cost the same under this workload — no savings either way.Break-even

Gemma 3 · Strengths & Key Advantages

Finestra di contesto da 131K con capacità massima di output fino a 16K token (GPQA Diamond 61% · MMLU-Pro 78%)
Throughput elevato di 105 token/secondo con latenza al primo token (TTFT) di soli 320 ms
Pesi aperti (1B / 4B / 12B / 27B) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama

Considerations & Trade-offs

Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

Gemma 2 · Strengths & Key Advantages

Finestra di contesto da 8K con capacità massima di output fino a 4K token (MMLU-Pro 68.5% · Arena Elo 1250)
Throughput elevato di 110 token/secondo con latenza al primo token (TTFT) di soli 300 ms
Pesi aperti (2B / 9B / 27B) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama

Considerations & Trade-offs

Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

Metric	Gemma 3	Gemma 2
Cost per Task Estimated USD to finish one task	$0.00	$0.00
Output Tokens / Task Tokens generated per task	5K	3K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Feature	Gemma 3	Gemma 2
Official API Model ID (SDK)	models/gemma-3	models/gemma-2
API Protocol	Google Gemini API (generateContent) + OpenAI-Compatible SDK	Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date	2025-03	2024-06
Knowledge Cutoff	December 2024	May 2024
Architecture	Native multimodal open transformer with expanded context	Dense transformer with sliding window attention and soft-capping
Parameters	1B / 4B / 12B / 27B	2B / 9B / 27B
Enterprise Rate Limits (RPM / TPM)	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)	Free across full context window (only KV-cache VRAM scales)	Free across full context window (only KV-cache VRAM scales)
Prompt Cache Policy & TTL	Automatic prefix KV-caching in vLLM / SGLang (0 cost)	Automatic prefix KV-caching in vLLM / SGLang (0 cost)
Computer Use / GUI Agent	Supported (Screen coordinate grounding, browser & desktop GUI action loops)	API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
MCP & Parallel Tool Calling	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & Sandbox	Built-in Google Search Grounding + Managed Python Code Execution Sandbox	Built-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning Support	Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)	Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Token Billing	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)	Text BPE (~4 chars/token)
Quantization & Min GPU VRAM	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 2 GB VRAM (4-bit Quantized) · 4 GB VRAM (Native BF16)	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 2 GB VRAM (4-bit Quantized) · 4 GB VRAM (Native BF16)
Safety & Frontier Classification	Google DeepMind Frontier Safety Framework Verified	Google DeepMind Frontier Safety Framework Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalities	text, vision	text
Output Modalities	text	text

Gemma 3 vs Gemma 2: Risposte Rapide (FAQ)

Which is more intelligent, Gemma 3 or Gemma 2?

Gemma 3 is more intelligent. It scores 68 compared with 58 on the composite Intelligence Index.

Which model is faster?

Gemma 2 is faster, generating 110 tokens per second compared with 105 tokens per second.

Which model has lower latency?

Gemma 2 has lower latency, with a time to first token of 0.30s compared with 0.32s.

Which model has a larger context window?

Gemma 3 has a larger context window, supporting 131.1K tokens compared with 8.2K tokens.

Verdetto

Sia Gemma 3 (Ideale per la comprensione multimodale nativa di testo e immagini e l’analisi visiva dei documenti, sistemi RAG aziendali e integrazioni API scalabili.) sia Gemma 2 (Ideale per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Gemma 3 guida nei benchmark di ragionamento e programmazione, Gemma 2 garantisce una generazione più rapida e Gemma 3 offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Gemma 3 o Gemma 2?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Gemma 3. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra Gemma 3 e Gemma 2?+

Gemma 3 costa $0.00 / $0.00 per milione di token di input/output, mentre Gemma 2 costa $0.00 / $0.00. Nel costo combinato, Gemma 3 risulta più economico.

Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+

Gemma 3 supporta 131.1K token di contesto contro 8.2K token di Gemma 2, mentre Gemma 2 offre una velocità di generazione superiore.

AI Terminology & Guide

Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

Gemma 3 vs Gemma 2

Cambia e Confronta Qualsiasi Modello

Gemma 3

Gemma 2

Chi vince in ogni categoria?

Punteggi Benchmark Verificati

Latenza e Tempo di Risposta

Simulatore Interattivo dei Costi Token

Gemma 3 · Strengths & Key Advantages

Considerations & Trade-offs

Gemma 2 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Specifiche Tecniche

Gemma 3 vs Gemma 2: Risposte Rapide (FAQ)

Verdetto

Domande Frequenti (FAQ)

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