Gemma 4 31B — Specifications
Compilado por Mustafa Ihsan de la documentación publicada por el proveedor · Última actualización
| Desarrollador | |
|---|---|
| Tipo | LLM (multimodal) |
| Modalidad | Texto, imagen → texto |
| Parámetros | 30,7B |
| Ventana de contexto | 256K |
| Licencia | Apache 2.0 |
| Pesos abiertos | Sí |
| Lanzado | 2026-03 |
| Precio de entrada | $0.20 /1M |
| Precio de salida | $0.40 /1M |
| Proveedores de API | DeepInfra, OpenRouter (hosted); Gemini API (free tier only); Ollama (local) |
Ejecútelo localmente
| VRAM (4 bits) | ~17.5 GB |
|---|
Benchmarks
| Google-reported | MMLU Pro 85.2%; GPQA Diamond 84.3%; LiveCodeBench v6 80.0%; AIME 2026 (no tools) 89.2%; MMMU Pro 76.9%. |
|---|
What is Gemma 4 31B?
Gemma 4 31B is the largest dense model in Google DeepMind’s open Gemma 4 family, released on 31 March 2026 under the Apache 2.0 licence. Its model card lists 30.7 billion parameters, text and image input, a 256K-token context window, configurable thinking modes and support for over 140 languages. Google reports 85.2% on MMLU Pro, 84.3% on GPQA Diamond and 80.0% on LiveCodeBench v6, against 67.6%, 42.4% and 29.1% for Gemma 3 27B without thinking.
Google estimates about 17.5 GB of memory to load it at 4-bit (Q4_0). That covers the weights only: the context window (KV cache) and supporting software need more on top. Ollama’s gemma4:31b-it-q4_K_M build is a 20 GB download, which will not fit in a 16 GB card’s memory but fits a 24 GB GPU with some room for context. Check a setup with the Calculadora de VRAM y nuestra guía sobre running Gemma 4 in Ollama.
Google’s Gemini API serves gemma-4-31b-it on its free tier only, with no paid tier. Hosted, DeepInfra charges $0.20 per million input tokens and $0.40 output, the price stored in this entry. It succeeds Gemma 3 27B. If speed matters more than peak quality, the mixture-of-experts Gemma 4 26B A4B needs less memory and, according to Google, runs almost as fast as a 4B model.
Gemma 4 31B pricing: API cost per 1M tokens
| Entrada (por cada millón de tokens) | $0.200 |
|---|---|
| Salida (por cada millón de tokens) | $0.400 |
| Relación salida/entrada | 2× |
| Combinada (4:1 entrada:salida) | $0.240 por 1 millón de tokens |
What Gemma 4 31B costs per month
Gasto mensual real con una mezcla entrada:salida de 4:1, es decir, la proporción que realmente genera una carga de trabajo típica de chat o RAG.
| Carga de trabajo | Tokens/mes | Coste mensual |
|---|---|---|
| Proyecto secundario | 1 millón de tokens de entrada / 0,25 millones de tokens de salida | $0.30 |
| Pequeño equipo | 20 millones de tokens de entrada / 5 millones de tokens de salida | $6.00 |
| Producción | 200 millones de tokens de entrada / 50 millones de tokens de salida | $60 |
Calcule sus propios números en la Calculadora de costos de API de IA.
Cheaper alternatives to Gemma 4 31B
| Modelo | Dólares por millón combinados | Usted ahorra |
|---|---|---|
| Llama 3.1 8B abierta | $0.0240 | 90% cheaper |
| Mistral NeMo 12B abierta | $0.0292 | 88% más barato |
| Gemma 3 4B abierta | $0.0600 | un 75 % más económico |
¿Autoalojarlo o pagar por la API?
Gemma 4 31B is open-weight, so you can run it yourself. It needs ~17.5 GB of VRAM at 4-bit. Self-hosting only beats the API once your volume is high enough to keep that hardware busy — the calculadora de autohospedaje frente a API calcula el punto de equilibrio para su volumen de tokens.
Preguntas frecuentes
How much does Gemma 4 31B cost per 1M tokens?
Gemma 4 31B costs $0.200 per 1M input tokens and $0.400 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $0.240 per 1M tokens.
How much does Gemma 4 31B cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $6.00 on Gemma 4 31B. A side project (1M in / 0.25M out) costs roughly $0.30.
What is a cheaper alternative to Gemma 4 31B?
Llama 3.1 8B is the strongest cheaper option in our database at $0.0240 per 1M blended — about 90% less than Gemma 4 31B. It is also open-weight, so self-hosting is an option.
Can I run Gemma 4 31B locally?
Yes. Gemma 4 31B is open-weight and needs about ~17.5 GB of VRAM at 4-bit quantisation.
Why does Gemma 4 31B charge more for output than input?
Output tokens are generated one at a time and cannot be batched the way a prompt can, so they cost the provider more to serve. Gemma 4 31B charges 2× more for output, which is why prompt-heavy workloads are far cheaper to run than generation-heavy ones.
Los precios corresponden a las tarifas oficiales publicadas para la API principal del modelo y se revisan periódicamente conforme los proveedores los actualicen. No incluyen descuentos por volumen, procesamiento por lotes ni entradas en caché. Compare todos los modelos uno al lado del otro en la Base de datos de modelos de IA o el Clasificación de modelos de lenguaje grande (LLM).