Gemma 3 27B — Spezifikationen
Compiled by Mustafa Ihsan from the vendor’s published documentation · Last updated
| Entwickler | |
|---|---|
| Typ | LLM (multimodal) |
| Modality | Text, Bild → Text |
| Parameter | 27B |
| Kontextfenster | 128 K |
| Lizenz | Gemma (offen) |
| Offene Gewichte | Ja |
| Veröffentlicht | 2025 |
| Eingabepreis | $0.08 /1M |
| Ausgabepreis | $0.16 /1M |
| API-Anbieter | Google AI Studio, OpenRouter, Ollama |
Lokal ausführen
| VRAM (4-Bit) | ~16 GB |
|---|---|
| Mindest-GPU | RTX 4080 16 GB / RTX 4090 |
What is Gemma 3 27B?
Gemma 3 27B is the largest open model in Google’s Gemma 3 line — multimodal across text
and images, 128K context, 140+ languages — and the strongest single-GPU local model in its
class. It needs roughly 16 GB of VRAM at 4-bit, so an RTX 4080 16GB or an RTX 4090.
The phrase “single-GPU” is what makes it interesting. Above this size, open models tend to
jump straight to multi-GPU servers: 70B-class models want 40 GB, and the large
mixture-of-experts flagships want hundreds. Gemma 3 27B is close to the ceiling of what one
consumer card can hold while remaining genuinely capable, which makes it the practical
maximum for a workstation deployment. Teams that need on-premises inference for compliance
reasons, and can live with 27B-class quality rather than frontier quality, can serve it from
a single machine instead of a rack. The API price of $0.08 in / $0.16 out per million tokens
is low enough that self-hosting only pays at sustained volume — worth checking against the
Selbsthosting vs. API
Rechner before buying hardware.
Gemma 3 27B pricing: API cost per 1M tokens
| Eingabe (pro 1 Mio. Token) | $0.0800 |
|---|---|
| Ausgabe (pro 1 Mio. Token) | $0.160 |
| Verhältnis Output/Input | 2× |
| Gemischt (4:1 Input:Output) | $0.0960 pro 1 Mio. Tokens |
What Gemma 3 27B costs per month
Tatsächliche monatliche Ausgaben bei einem 4:1-Input-zu-Output-Mix – dem Verhältnis, das typische Chat- oder RAG-Arbeitslasten tatsächlich erzeugen.
| Workload | Tokens/Monat | Kosten pro Monat |
|---|---|---|
| Nebenprojekt | 1 Mio. Eingabe / 0,25 Mio. Ausgabe | $0.12 |
| Kleines Team | 20 Mio. Eingabe / 5 Mio. Ausgabe | $2.40 |
| Produktion | 200 Mio. Eingabe / 50 Mio. Ausgabe | $24 |
Stellen Sie Ihre eigenen Berechnungen im KI-API-Kostenrechner.
Cheaper alternatives to Gemma 3 27B
| Modell | Gewichteter Preis pro Million US-Dollar | Sie sparen |
|---|---|---|
| Phi-4 offenere | $0.0840 | 13% cheaper |
Selbst hosten oder die API nutzen?
Gemma 3 27B is open-weight, so you can run it yourself. It needs ~16 GB of VRAM at 4-bit (RTX 4080 16GB / RTX 4090). Self-hosting only beats the API once your volume is high enough to keep that hardware busy — the Selbsthosting vs. API-Rechner berechnet den Break-even-Punkt für Ihr Token-Volumen.
Häufig gestellte Fragen
How much does Gemma 3 27B cost per 1M tokens?
Gemma 3 27B costs $0.0800 per 1M input tokens and $0.160 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $0.0960 per 1M tokens.
How much does Gemma 3 27B cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $2.40 on Gemma 3 27B. A side project (1M in / 0.25M out) costs roughly $0.12.
What is a cheaper alternative to Gemma 3 27B?
Phi-4 is the strongest cheaper option in our database at $0.0840 per 1M blended — about 13% less than Gemma 3 27B. It is also open-weight, so self-hosting is an option.
Can I run Gemma 3 27B locally?
Yes. Gemma 3 27B is open-weight and needs about ~16 GB of VRAM at 4-bit quantisation (RTX 4080 16GB / RTX 4090).
Why does Gemma 3 27B 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 3 27B charges 2× more for output, which is why prompt-heavy workloads are far cheaper to run than generation-heavy ones.
Die Preise entsprechen den offiziell veröffentlichten Listenpreisen für die primäre API des jeweiligen Modells und werden regelmäßig aktualisiert, sobald Anbieter diese ändern. Volumen-, Batch- und Cached-Input-Rabatte sind nicht enthalten. Vergleichen Sie alle Modelle nebeneinander im Datenbank für KI-Modelle oder das LLM-Leaderboard.