Mistral 7B on NVIDIA GeForce RTX 5090 · 32GB VRAM

✅ Runs comfortably — Mistral 7B @ Q8_0
Mistral 7B 7B at Q8_0 needs ~8.7 GB (weights 7.2 GB + KV 1.0 GB + overhead 512 MB @ 8K ctx) of your 28.8 GB usable VRAM — plenty of headroom. Expect ~90–150 tok/s (very fast).
context @ Q8_0: comfortable to 32K
quantneedsspeed
✓ Q8_08.7 GB~90–150 tok/s (very fast)
✓ Q6_K7.0 GB~110–190 tok/s (very fast)
✓ Q5_K_M6.3 GB~130–210 tok/s (very fast)
✓ Q4_K_M5.6 GB~140–240 tok/s (very fast)
$runlocal install mistral:7b
⚠ NVIDIA support is best-effort in v0.1 — verify before relying on it.
runlocal verdict card
download card share on x share on reddit drop it in your model-drop post
Mistral 7B: Runs comfortably
for your own README — links back here

Same model, other machines: Apple M1 · Apple M1 Pro · Apple M2 · Apple M3 Pro · Apple M2 Pro · Apple M4 Pro

Also runs on a NVIDIA GeForce RTX 5090: DeepSeek-R1 (distill) · Qwen2.5 · Qwen3 · Llama 3.1 · Gemma 3

Best models for a NVIDIA GeForce RTX 5090 · 32GB VRAM →

Architecturally similar

These share Mistral 7B's KV-cache geometry — they size memory the same way, so here's how they fit on a NVIDIA GeForce RTX 5090 · 32GB VRAM too:

modelsharesverdict here
Qwen2.5-Coder 8kv/128hd ✅ Runs (tight)
Llama 3.2 8kv/128hd ✅ Runs comfortably
Llama 3.3 8kv/128hd ✅ Runs (tight)
Mistral Small 3 8kv/128hd ✅ Runs (tight)
Mistral Nemo 8kv/128hd ✅ Runs comfortably
Codestral 8kv/128hd ✅ Runs (tight)
Llama 3.2 Vision 8kv/128hd ✅ Runs comfortably
Mixtral 8x7B 8kv/128hd ✅ Runs (tight)

…and 7 more — see the Mistral 7B page.

Check any combo yourself: open the checker →