Gemma 3 27B
Google's largest Gemma 3. Reads images, writes well, and handles many languages. It needs a 24 GB card to run with room for context.
ollama run gemma3:27bNeeds about 19 GB of graphics memory, or unified memory on a Mac. First time? Install Ollama, then paste that into a terminal.
Download17 GB
Memory to runAbout 19 GB
Read per token17 GB
LicenseGemma Terms of Use
Context128K tokens
ReleasedMarch 2025
Good for
- Image understanding with a smarter model
- Polished writing and translation
- Long documents
Not the best pick for
- Speed: as a dense 27B it is slower than the MoE models of similar size
63 GPUs and Macs
What runs Gemma 3 27B
Estimated speed on each card at the smallest memory size that fits it, from memory bandwidth. As a dense model it reads all its weights for every token, so memory bandwidth sets the speed.
Runs great 14 cards
- H200141 GB · ~160 tok/s
- H10080 GB · ~110 tok/s
- RTX 509032 GB · ~58 tok/s
- RTX Pro 6000 Blackwell96 GB · ~58 tok/s
- A10040 GB · ~50 tok/s
- RTX Pro 5000 Blackwell48 GB · ~43 tok/s
- Instinct MI10032 GB · ~40 tok/s
- Instinct MI5032 GB · ~33 tok/s
- RTX 3090 Ti24 GB · ~33 tok/s
- RTX 409024 GB · ~33 tok/s
- RTX 6000 Ada48 GB · ~31 tok/s
- RX 7900 XTX24 GB · ~31 tok/s
- RTX 309024 GB · ~30 tok/s
- A3024 GB · ~30 tok/s
Usable 32 cards
- Tesla V10032 GB · ~29 tok/s
- RTX 5090 Laptop24 GB · ~29 tok/s
- RTX Pro 4500 Blackwell32 GB · ~29 tok/s
- L40S48 GB · ~28 tok/s
- Radeon Pro W790048 GB · ~28 tok/s
- Apple M3 Ultra96 GB · ~26 tok/s
- RX 7900 XT20 GB · ~26 tok/s
- Apple M1 Ultra64 GB · ~26 tok/s
- Apple M2 Ultra64 GB · ~26 tok/s
- RTX A500024 GB · ~25 tok/s
- RTX A550024 GB · ~25 tok/s
- RTX A600048 GB · ~25 tok/s
- A4048 GB · ~23 tok/s
- Titan RTX24 GB · ~22 tok/s
- Quadro RTX 600024 GB · ~22 tok/s
- Quadro RTX 800048 GB · ~22 tok/s
- RTX Pro 4000 Blackwell24 GB · ~22 tok/s
- RTX A450020 GB · ~21 tok/s
- Radeon AI Pro R970032 GB · ~21 tok/s
- A1024 GB · ~19 tok/s
- RTX 5000 Ada32 GB · ~19 tok/s
- Radeon Pro W780032 GB · ~19 tok/s
- Apple M4 Max36 GB · ~18 tok/s
- Radeon Pro W680032 GB · ~17 tok/s
- Apple M5 Max36 GB · ~15 tok/s
- Arc Pro B6024 GB · ~15 tok/s
- RTX 4500 Ada24 GB · ~14 tok/s
- Apple M1 Max32 GB · ~13 tok/s
- Apple M2 Max32 GB · ~13 tok/s
- Apple M3 Max36 GB · ~13 tok/s
- RTX 4000 Ada20 GB · ~12 tok/s
- Tesla P4024 GB · ~11 tok/s
Slow 17 cards
- Apple M5 Pro48 GB · ~10 tok/s
- L424 GB · ~10 tok/s
- Tesla M4024 GB · ~9 tok/s
- Apple M4 Pro48 GB · ~9 tok/s
- NVIDIA DGX Spark128 GB · ~9 tok/s
- Ryzen AI Max+ 395 (Radeon 8060S)64 GB · ~8 tok/s
- Ryzen AI Max 390 (Radeon 8050S)32 GB · ~8 tok/s
- Jetson AGX Orin32 GB · ~7 tok/s
- Apple M1 Pro32 GB · ~6 tok/s
- Apple M2 Pro32 GB · ~6 tok/s
- Apple M532 GB · ~5 tok/s
- Apple M3 Pro36 GB · ~5 tok/s
- Intel Arc 140V32 GB · ~4 tok/s
- Snapdragon X Elite (Adreno X1-85)32 GB · ~4 tok/s
- Apple M432 GB · ~4 tok/s
- Radeon 890M32 GB · ~4 tok/s
- Radeon 780M32 GB · ~3 tok/s
Cheapest build from our list that runs it well: Used workstation + 2× Tesla P100, from $750 used, at about 24 tok/s. See the builds.
Learn
Read more about Gemma 3 27B
- Context length and the KV cache: why long chats use more VRAMWhy a model that fits can still run out of memory on a long document, how to work out the KV cache size, and three ways to shrink it.
- Open model licenses explained: Apache 2.0, Llama and Gemma termsWhat the licenses on popular open models mean in practice for personal, business and product use. Apache 2.0, the Llama community license and Gemma terms.
- Qwen3 vs Gemma 3: which local model should you run?Qwen3 and Gemma 3 compared for local use. Reasoning, images, writing, licenses, memory and estimated speeds on 12 and 24 GB cards.
- The best GPU for local AI under $1,000What to buy for local AI under $1,000 now that a used RTX 3090 costs more, how Tesla P100s and the RTX 3060 compare to new 16 GB cards and the RTX A4500, and what to buy for each kind of use.
- The best local LLM for 24 GB of VRAM (RTX 3090, 4090, 7900 XTX)What to run on a 24 GB card, the community's favorite size for local AI. Picks for speed, smarts, images and code, with estimated speeds.
- The best local LLM for a Mac with 64 GB, 96 GB or 128 GB+What to run on a Mac Studio or MacBook Pro with 64 GB or more of unified memory, from Qwen3 30B-A3B to Llama 3.3 70B and gpt-oss 120B, with estimated speeds.
- The best local LLM for writing, by how much memory you haveWhich open models write best for drafts, editing, emails and fiction on 8 GB to 48 GB+, plus the settings and prompts that make local writing sound less generic.
- The best local model for translationWhich open models translate best on your own hardware, by memory size, plus prompts that get natural results and where local translation still falls short.
- The best local vision model for reading images and screenshotsHow to run a local model that reads images, screenshots, charts and documents. Why Gemma 3 is the pick, which size to run, and what it can and can't do.
- The RTX 5090 for local AI: what 32 GB and 1.8 TB/s get youHow fast the RTX 5090 runs local LLMs, what fits in 32 GB, what doesn't, the power you need, and when a used 3090 or two is the smarter buy.
- Uncensored local models: what abliterated means, and the tradeoffsWhy local models refuse some requests, what abliterated and uncensored fine-tunes change, what it costs in quality, and how to cut needless refusals without one.
Compare
Other models
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- Gemma 3 12BAbout 10 GB · Reads images as well as text
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- Qwen3 30B-A3BAbout 21 GB · 30B smarts at small-model speed
- Qwen3 32BAbout 22 GB · Strong coding and long answers
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- gpt-oss 120BAbout 67 GB · OpenAI's largest open model
- Qwen3 235B-A22BAbout 144 GB · Alibaba's flagship open model, for multi-GPU rigs
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