Mistral Large 4 1T A52B
Mistral Large 4 1T A52B is an open-weights language model from Mistral, released September 30, 2026. It has 1T parameters (mixture-of-experts, 52B active). The context window is 1M tokens.
Check it against your own PC →
Can you run Mistral Large 4 1T A52B locally?
Even with 32 GB of VRAM and 32 GB of RAM it is too large to run at a usable speed on a single consumer GPU. Estimates assume 32 GB of DDR5 RAM, a 16K context and llama.cpp-style GGUF quantization. Enter your exact hardware in the live app.
| GPU memory | Verdict | Best quant | VRAM | RAM | tok/s |
|---|---|---|---|---|---|
| 6 GB VRAM | Too large | – | – | – | – |
| 8 GB VRAM | Too large | – | – | – | – |
| 12 GB VRAM | Too large | – | – | – | – |
| 16 GB VRAM | Too large | – | – | – | – |
| 24 GB VRAM | Too large | – | – | – | – |
| 32 GB VRAM | Too large | – | – | – | – |
Ready-made quantizations on Hugging Face: unsloth/Mistral-Large-4-1T-A52B-GGUF · ggml-org/Mistral-Large-4-1T-A52B-GGUF · orcarouter/Mistral-Large-4-1T-A52B-GGUF · DevQuasar/mistralai.Mistral-Large-4-1T-A52B-GGUF · bertholomus/Mistral-Large-4-1T-A52B-EXL3-2.5bpw · mistralai/Mistral-Large-4-1T-A52B-NVFP4
Benchmark results
Epoch AI has not published results for Mistral Large 4 1T A52B yet. New models are usually evaluated within days to weeks.
Links
Hugging Face: mistralai/Mistral-Large-4-1T-A52B
More from Mistral
Mistral Large 4 · Mistral Large 4 Preview · Leanstral 1.5 · Mistral Medium 3.5 · Mistral Small 4 · Devstral Small 2 · Devstral 2 · Ministral 3 3B