Can Gemini 3.5 Flash Run Locally in Ollama?
Gemini 3.5 Flash does not run locally in Ollama, LM Studio or MLX. What actually works on Mac and which local models fit instead.
Short answer: no. Gemini 3.5 Flash is a Google cloud/API model, not a local open-weight model. You cannot run it locally in Ollama, LM Studio or MLX on your Mac. I spent some time trying to find a workaround on my Mac Mini M4, and there is simply no way around it — Gemini stays in the cloud. If you see Gemini-style models in Ollama, check carefully whether they are Ollama cloud models or older/different Gemini listings. For fully local AI on Apple Silicon, use open-weight models such as Gemma, Qwen, Llama, Mistral or other models that are actually available for local runtimes.
Related Mac guides: Gemini 3.5 Flash on Mac, Ollama on Mac mini M4, LM Studio vs Ollama, Unified Memory on Mac, Gemma 3 on Mac, small local LLMs, Apple Intelligence vs local AI and Local Models.
Original graphic based on the official Google and Ollama documentation; checked on May 27, 2026. Sources are listed at the end of the article.
Why this question is confusing
The confusion makes sense: Gemini is Google’s cloud model family, Gemma is Google’s open-weight family, Ollama is best known for local models but now also offers cloud models, and provider aliases such as google/gemini-3.5-flash appear in routers and benchmark tools.
That can make it look as if Gemini 3.5 Flash might run locally on a Mac. It does not.
For Mac users, the important question is not “Can I type something Gemini-like into a local tool?” The useful question is: where does inference actually run, and do my files leave the Mac?
What Gemini 3.5 Flash actually is
Gemini 3.5 Flash is a stable Google model for the Gemini API and Google’s own product ecosystem. The official model ID is gemini-3.5-flash.
According to Google’s model page, Gemini 3.5 Flash supports text, image, video, audio and PDF input, and returns text output. It has an input context window of 1,048,576 tokens and an output limit of 65,536 tokens.
It also supports features such as thinking, function calling, code execution, File Search, URL context, Search Grounding, Maps Grounding, Batch API, caching, Flex inference and Priority inference. It does not support audio generation, computer use, image generation or the Live API.
Important for Mac users: those capabilities come from Google’s cloud/API infrastructure. Apple Silicon does not accelerate Gemini 3.5 Flash locally because the inference is not running on your Mac.
Does Gemini 3.5 Flash run in Ollama?
No, not locally. You cannot start Gemini 3.5 Flash as a local model on your Mac with a command such as:
ollama run gemini-3.5-flashThere are no official Gemini 3.5 Flash weights for Ollama, no GGUF file and no MLX version.
If you see Gemini-style entries around Ollama or model routers, distinguish three cases:
- Is it a different model?
- Is it a preview/provider/cloud entry?
- Is the request processed locally or sent to a cloud service?
For local privacy, only the last point really matters.
Rule of thumb: an Ollama command does not automatically mean local inference. With cloud models, Ollama can act as a local interface while the actual inference runs in the cloud.
Ollama local vs Ollama Cloud
Ollama can run local models. Ollama also documents Cloud Models, which are offloaded to Ollama’s cloud and require an Ollama account. That is useful when your Mac does not have enough memory for a larger model, but it is not the same thing as local inference.
| Mode | Where inference runs | Internet needed? | Do data leave the Mac? | Example |
|---|---|---|---|---|
| Local Ollama model | On your Mac | No, after download | No, if no tools/cloud are active | Gemma, Qwen, Llama, Mistral |
| Ollama Cloud Model | Ollama Cloud | Yes | Yes | Cloud-hosted models |
| Gemini API | Google Cloud | Yes | Yes | gemini-3.5-flash |
If your goal is “my files never leave the Mac”, use local models and disable cloud features for sensitive work:
# For Ollama started from the terminal or shell
export OLLAMA_NO_CLOUD=1For the clearer persistent setup, use Ollama’s server configuration:
{
"disable_ollama_cloud": true
}Ollama documents this in ~/.ollama/server.json. Restart Ollama afterwards; the logs should show Ollama cloud disabled: true. Then test whether your workflow still works without internet. That is the practical check that matters.
Does Gemini 3.5 Flash run in LM Studio or MLX?
No. LM Studio and MLX also need model weights that can be loaded locally. Gemini 3.5 Flash is not an open-weight download, so neither LM Studio nor MLX can run it as a local Apple Silicon model.
LM Studio and MLX are good for local alternatives, not for Gemini 3.5 Flash itself.
What about google/gemini-3.5-flash?
google/gemini-3.5-flash is usually provider naming in routers, benchmark tools or multi-model platforms. It means: provider Google, model Gemini 3.5 Flash.
In Google’s own Gemini API, the model ID is:
gemini-3.5-flashThe google/ prefix does not make the model local and does not turn it into an Ollama model.
Local alternatives on the Mac
If what you really want is “Gemini quality, but local”, there is no 1:1 replacement. You need a local open-weight model that fits your Mac.
| Goal | Local direction | Note |
|---|---|---|
| Google-adjacent open-weight model | Gemma 3 | Not Gemini 3.5 Flash, but locally available |
| General chat | Qwen / Llama / Mistral class | Depends on size and quantization |
| Local coding | Qwen / DeepSeek / code-focused models | Quality depends heavily on model size, quantization and task |
| Local vision | Gemma 3 4B/12B/27B or vision models | Not every local model can read images |
| Transcription | Whisper | Different model family, very practical locally |
| Private documents | Local RAG + Ollama/LM Studio | Privacy benefit only with local-only setup |
As a rough Mac RAM guide (based on what I have seen on my own Mac Mini M4 with 32 GB):
- 8 GB: small models, 1B-4B, sometimes heavily quantized 7B.
- 16 GB: 7B/8B more comfortably, some 12B workflows.
- 24 GB: 12B/14B is more realistic, larger models carefully.
- 32 GB: 27B-class models become more realistic, but limit context.
- 48 GB+: larger local models and vision workflows become much more comfortable.
No guarantee: runtime, quantization, context length, KV cache, swap and open apps change real memory use.
Gemini 3.5 Flash vs local models
| Criterion | Gemini 3.5 Flash | Local Ollama model |
|---|---|---|
| Runs offline on Mac? | No | Yes, after download |
| Local Ollama? | No | Yes |
| Local LM Studio? | No | Yes, if compatible |
| Local MLX? | No | Yes, if available |
| Open weights? | No | Depending on model, yes |
| Context | 1,048,576 input tokens | Depends on model, RAM and runtime |
| Multimodal | Text/image/video/audio/PDF input, text output | Model-dependent |
| Privacy | Cloud processing | Local-only possible |
| Costs | API/token/grounding/caching costs | Hardware, power, storage and time |
| Advantage | Large context, tools, agents, Google ecosystem | Offline, control, private files |
| Trade-off | Cloud data flow, ongoing costs | Memory limits, smaller models, setup effort |
When Gemini 3.5 Flash is better
Gemini 3.5 Flash is useful when you need:
- very long context windows
- large PDFs, audio, video or image analysis
- function calling, code execution or File Search
- Search Grounding or Maps Grounding
- multi-step agent workflows
- API integration more than full offline privacy
- non-sensitive or explicitly approved data processing
When local AI is better
Local AI is the better default when:
- private files should not leave the Mac
- you need offline work
- you want no ongoing API token costs
- you want reproducible model/quantization tests
- you are building local RAG systems
- you process customer data, unpublished code, personal notes or confidential documents
A practical hybrid workflow for Mac users
The best Mac workflow is often hybrid.
Use local models for:
- private notes
- internal documents
- drafts
- code that must not go to the cloud
- transcription with Whisper
- local RAG search
Use Gemini 3.5 Flash for:
- very large context windows
- public or approved material
- API-based workflows
- agents
- tool calling
- multimodal analysis
- structured extraction
Rule of thumb: if the content must stay private, use local AI. If context, tools and agent capabilities matter more, use Gemini 3.5 Flash. That is exactly the workflow I follow — local models for everything private, and Gemini API only when I need the 1M context window or multimodal analysis.
Privacy and costs
Gemini 3.5 Flash is not “free no matter how much you use it”. Free-tier access may exist, but production usage needs cost control for input, output, thinking tokens, caching, storage and grounding. In the paid tier, Google’s pricing page lists Standard at $1.50 input and $9.00 output per 1M tokens; Batch and Flex are cheaper, Priority is more expensive. Search/Maps Grounding can add costs per individual search query.
Privacy also needs precision:
- Free Tier content may be used by Google to improve products, according to Google’s pricing/data notes.
- Paid Tier usage is not used for product improvement by default according to Google’s pricing page.
- Abuse monitoring can still involve prompts, context and outputs for a limited period.
- Ollama says it does not see prompts or data for locally run models. For cloud-hosted models, Ollama processes prompts and responses to provide the service, and says it does not store, log or train on that content.
- For sensitive data, local AI or a clear enterprise/compliance workflow remains the safer default.
Common mistakes
- Trying to install Gemini 3.5 Flash in Ollama. Correction: it is not locally available.
- Confusing Ollama Cloud with local inference. Correction: cloud model means cloud processing.
- Treating Gemma and Gemini as the same thing. Correction: Gemma is open-weight; Gemini 3.5 Flash is cloud/API.
- Using
google/gemini-3.5-flashas the official Google API model ID. Correction: in the Gemini API, usegemini-3.5-flash. - Expecting 1M context locally. Correction: local models are limited by RAM, KV cache and runtime.
- Describing local AI as automatically 100% private. Correction: only with local-only setup, no cloud tools and no exposed server.
- Treating Gemini 3.5 Flash as an Ollama replacement. Correction: it is better viewed as part of a hybrid workflow.
FAQ
Can I run Gemini 3.5 Flash locally on my Mac?
No. Gemini 3.5 Flash is not a local open-weight model. It runs through Google’s cloud/API infrastructure.
Does ollama run gemini-3.5-flash work?
No, not as an official local model. If you see Gemini-style Ollama entries, check whether they are cloud models, preview models or third-party/provider listings.
Is Ollama always local?
No. Ollama is known for local models, but it also supports Cloud Models. For sensitive work, configure local-only usage.
What is the best local alternative?
There is no direct 1:1 alternative. For Google-adjacent local workflows, Gemma 3 is the obvious starting point. For other tasks, Qwen, Llama, Mistral, DeepSeek or specialized models may fit better.
Is Gemma 3 the same as Gemini 3.5 Flash?
No. Gemma is Google’s open-weight model family. Gemini 3.5 Flash is a proprietary cloud/API model.
When should I still use Gemini 3.5 Flash?
Use it when you need 1M context, multimodal input, tool calling, code execution, File Search, Search Grounding or cloud agents, and the cloud data flow is acceptable.
Sources and status
Status: checked on May 27, 2026. Model names, prices, limits, availability and supported features can change.
Frequently Asked Questions
Can I run Gemini 3.5 Flash locally in Ollama on my Mac?
No. Gemini 3.5 Flash is a Google-hosted API model. There is no Ollama tag, no LM Studio preset, and no MLX checkpoint for any Gemini 3.5 variant. If you want a local model on a Mac, you need an open-weight alternative like Qwen3, Llama 3.3, Mistral, Gemma, or DeepSeek.
Is there a community port of Gemini 3.5 Flash for Ollama?
No reliable community port exists. Google has not released weights for Gemini 3.5, and reverse-engineering a production API into local weights is not a real workflow. Be skeptical of any 'gemini-3.5-flash' tag on Ollama — it is either a distractor, a rebrand of a different model, or a wrapper around the Google API.
What is the closest local model to Gemini 3.5 Flash on Mac?
On Apple Silicon with 16–24 GB RAM, Qwen3 14B (Q4), Gemma 3 12B or Mistral Small 3.1 are possible local alternatives. With 32 GB, larger Qwen or reasoning models become practical. Llama 3.3 is a 70B model, and there is no local 'DeepSeek V3 small' model.
Can I use the Gemini API from my Mac without sending data to Google?
No. Any call to Gemini routes to Google's infrastructure. For privacy-sensitive work you must run a local model and not call any cloud API. The ai-on-mac.com privacy guide covers how to set up Ollama, LM Studio, or MLX with a no-telemetry config and a local-only model.
Will Gemini 3.5 Flash become available locally in the future?
Google has not announced open-weight releases for the Gemini 3.5 family. Gemma 3 is Google's open-weight line, but Gemma is a separate model family, not a port of Gemini. If you need a Gemini-class local model today, plan around an open-weight substitute, not a future Gemini release.