Mistral 7B

What this model is

The architecture is dense. Every parameter is part of the active path, so memory and speed scale with the full model rather than a smaller expert subset.

Memory and quantization

Decimal GB, rounded from the Ollama tag page. Runtime memory still needs KV cache and overhead.

Estimate formula: published weight files + 1.0737 GB per 8K tokens × context / 8K + 1.5 GB runtime overhead. Sizes are decimal GB, not GiB. At 8K context, the smallest listed build is about 7.0 GB before OS and application reserve.

Conservative FP16 estimate from the standard Mistral GQA configuration; not a runtime measurement.

KV method source: https://ollama.com/library/mistral

Speed heuristic

Speed depends on quantization, backend, and hardware; no single measured value is reported

Active path: 7.2B parameters. This is a relative speed signal only; it is not a tokens/sec benchmark.

Runtimes

• Ollama
• llama.cpp

ollama run mistral:7b

License restrictions

Apache 2.0 permits commercial use and modification; retain notices and comply with the patent and termination terms.

This is a plain-language summary, not legal advice. Read the linked license before commercial deployment or redistribution.

Known issues

• An older model; newer models may perform better on some tasks

Sources

• https://ollama.com/library/mistral
• https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3

This page is an independent compatibility guide, not official documentation. Verify the primary source before downloading or deploying a model.

Check a specific machine