Mistral 7B Instruct v0.3: memory fit on every Jetson module.
Method v1.0 · dataset 2026-09-07 · verified 2026-09-07 · last updated September 2026
7.25 B parameters · 32 layers · 32,768-token max context. Hugging Face: mistralai/Mistral-7B-Instruct-v0.3.
Model facts
| Fact | Value | Note |
|---|---|---|
| Parameters | 7.248 B | |
| Layers | 32 | |
| Hidden size | 4096 | |
| Attention heads | 32 | |
| KV heads | 8 | |
| Head dimension | 128 | |
| Max context | 32,768 tokens | |
| dtype | bfloat16 | |
| Vocabulary | 32,768 |
Mistral AI · hf:mistralai/Mistral-7B-Instruct-v0.3 · config.json · verified 2026-09-07
“"num_attention_heads": 32, "num_key_value_heads": 8, "vocab_size": 32768”
Parameters source
- Hugging Face · hf:mistralai/Mistral-7B-Instruct-v0.3 · verified 2026-09-07 · model.safetensors.index.json · class A
“"total_size": 14496047104”
Published quantised artefacts
A file the publisher or a community mirror actually ships, used as the class-A weight figure when the requested quant matches. Any quant without a row here falls back to parameters × bytes-per-parameter (class D for block quants).
| Quant | Format | File | Size | Source |
|---|---|---|---|---|
| GGUF Q4_K_M / INT4 (AWQ, MLC q4f16) | GGUF Q4_K_M | Mistral-7B-Instruct-v0.3-Q4_K_M.gguf | 4.373 GB | bartowski (community GGUF) · hf:bartowski/Mistral-7B-Instruct-v0.3-GGUF · verified 2026-09-07 |
Jetson tokens/s measurements
Published or archived throughput numbers, not modelled. Class C (external measured benchmark).
No Jetson-measured tokens/s reported for this model yet.
Every module × every quantisation
Verdict and total memory at 4096-token context, 1 sequence, llama.cpp, headless. Q4 cells link to the static breakdown page; every other cell links to the live engine at that quantisation.
Notes
head_dim derived as hidden_size/num_attention_heads=4096/32=128 (no explicit head_dim field in config.json). params_b (7.25B) is higher than the nominal '7B' name due to the extended 32768-token vocabulary vs Mistral-7B-v0.1's 32000.
Method and data: Model Memory Fit methodology. Full registry: model-memory.json.
Change the context, concurrency or runtime.
The live engine covers any context length, sequence count, KV precision and runtime, with a permanent link.