Mistral vs Llama vs Gemma: Choosing Overseas Open Weights for Local Deployment
Compare Mistral 7B, Llama 3.3 70B, and Gemma 3 27B by parameters, licences, ecosystem, hardware and local deployment.
Mistral vs Llama vs Gemma: Choosing Overseas Open Weights for Local Deployment
This page maps mistral-vs-llama-gemma using facts verified from HuggingFace metadata and official repository configuration, sampled in November 2026. It separates local open weights from EXAIV cloud IDs and does not invent benchmarks, prices, or converted repositories.
Verified facts
A HuggingFace repository proves that weights or a model card exists; it does not prove that EXAIV serves the model. Download counts are public 30-day community signals, not quality scores. Licences must be read per repository. Config fields prove architecture, not every capability or request payload.
Deployment reality
Choose a runtime that matches the format, measure memory on your own hardware, and keep the model ID, file name, licence, token counts and latency in a run log. Community GGUF files need a named publisher, a stated conversion source and a clear quantization label. The local deployment angle here is intentional: none of these repositories should be called an EXAIV cloud model unless the live catalog lists the ID.
Availability boundary
The safest wording is local open weights, official model card, and measured behaviour on your machine. Availability and prices follow /models and /pricing. A licence tag such as apache-2.0, gemma, llama3.3 or other is a starting point for review, not legal advice.
Situation
| Situation | Pick |
|---|---|
| Small local card | See the live model card and choose by hardware and licence |
| Highest instruction capacity | See the live model card and choose by hardware and licence |
| Image-text input | See the live model card and choose by hardware and licence |
| Permissive Apache licence | See the live model card and choose by hardware and licence |
| Community GGUF ecosystem | See the live model card and choose by hardware and licence |
FAQ
Are these models callable on EXAIV?
Can I use community GGUF?
Are downloads benchmark scores?
Where do I check licences?
Where do I check EXAIV availability?
Where do I check price?
Related reading
- Claude family overview — callable IDs
- GPT family overview — ID families
- Open overseas weights — local weights
- Mistral vs Llama vs Gemma — selection
- pricing — live credit packs
Sources
Parameter, download and licence data sampled in November 2026 and subject to change.
Local selection checklist
Start with memory and context length, then read the licence and input format in each model card, and measure all three on the same prompt set. Never use a weight name as a cloud ID and never treat downloads as a quality score. Price and availability follow the live pages.
For production, compare the same task set on all three models and record peak memory, time to first token, sustained tokens per second, output validity, and licence status. The winning model is the one that fits the whole constraint, not the one with the largest parameter count. Keep a rollback file and verify the live catalog before describing any model as callable through EXAIV.