53 open-source models selected for local deployment. Each with its use case, the memory it needs and how to install it.
Source: Hugging Face and Ollama. Sizes checked on 6 October 2026.
53 models 8 categories 20 machines compared
Pick a model and a quantisation to see which machines it fits.
Pick a model, a quantisation and a context. The bars show which machines it fits.
Estimated memory needed
Weights = parameters × bits per weight ÷ 8 (Q4_0 4.5 · Q4_K_M 4.85 · Q8_0 8.5 · FP16 16). Cache = MB per token × context tokens. Runtime = 1.5 GB.
Measured with ollama ps on our GB10, real use comes in 1.4 to 1.6 GB below this figure: we would rather you have memory to spare than run short. From each machine we also take off the share the operating system keeps.
Estimated speed: –
From least to most memory. Open a machine for its spec sheet and where to buy it.
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Next step: Hardware selector ROI calculator Grants
53 models
Click a model for details
NVIDIA's world generation model. Understands physics. Great for game dev and simulation.
RTX 4060 Ti 16GB or RTX 4090
Strong Chinese-English bilingual video generation. Apache 2.0. Good motion and detail.
RTX 4090 or A100
Exceptional motion quality. Apache 2.0. Natural human movement and physics.
RTX 4090 or cloud
Industry standard for transcription. 99 languages. MIT license. Runs on any device.
Any device (809M params)
ollama pull whisper-large-v3-turbo Generates realistic speech, music, and sound effects from text. MIT license. Multilingual.
Any device with 4GB+ RAM
ollama pull bark Generate music from text descriptions. Great for content creators. Multiple styles.
Any device with 8GB+ RAM
ollama pull musicgen-large Clone any voice from 6-second sample. 17 languages including Spanish. Real-time on CPU.
Any device (runs on CPU)
ollama pull xtts-v2 Control voice via text description ('A warm female voice, clear, podcast style'). Apache 2.0.
Any device with 4GB+ RAM
ollama pull parler-tts Fine-tuned on PubMed. Medical QA, clinical text analysis. Apache 2.0. EU AI Act: high-risk category.
Jetson Orin Nano 8GB (Q4) or Mac Mini M4
ollama pull biomistral Trained on legal corpora. Understanding of legal concepts, statutes, case law. MIT license.
Jetson Orin Nano 8GB (Q4) or Mac Mini M4
ollama pull saullm Math reasoning at 7B. Solves complex problems step by step.
Jetson Orin Nano 8GB (Q4) or any device
ollama pull deepseek-math Best 7B for structured tasks: function calling, JSON output, tool use. Apache 2.0. Fast and reliable.
Jetson Orin Nano 8GB (Q4) or any device
ollama pull mistral:7b-instruct-v0.3 No models found
Select 2-3 models for a side-by-side comparison.
For jobs that need a bigger model than your machine holds, this is what the API costs. We only publish prices we have checked on each provider's official page.
| Model | Provider | Input | Output | Context |
|---|---|---|---|---|
| GPT-5 | OpenAI | $1.25 | $10.00 | 400K |
| GPT-5 Mini | OpenAI | $0.25 | $2.00 | 400K |
| Claude Sonnet 5 | Anthropic | $2.00 | $10.00 | 200K |
| Claude Haiku 4.5 | Anthropic | $1.00 | $5.00 | 200K |
Sources: OpenAI · Anthropic. To compare with what it costs locally, use the cost calculator.
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