local-ai

memra

memra is a Rust + CUDA inference engine for serving GGUF models on NVIDIA GPUs. It is optimized for Blackwell (sm_120a), with a separately gated Hopper/H100

From the repo · “Rust + CUDA inference engine for NVIDIA RTX PRO 6000 Blackwell and RTX 5090. Serves safetensors and GGUF over an OpenAI-compatible API, with per-device tuned defaults and speculative decode gated byte-identical to plain decode. Hosted instance: inference.tiyuvta.ai”

4 stars+2★ this week1 forksRustUpdated 10/6/2026100% free · open source
What it does

Memra is a Rust + CUDA inference engine that serves GGUF models on NVIDIA GPUs, optimized for Blackwell and Hopper/H100 architectures.

When to use it
  • •You need to deploy GGUF models on NVIDIA GPUs for high-performance inference.
  • •Your startup requires a customized inference engine for specific GPU architectures.
  • •You want to leverage Rust and CUDA for building a high-speed AI application.
Ready-to-paste prompt
cargo run --release -- -m path/to/model.gguf -i path/to/input.data
Heads up: Ensure you have the CUDA toolkit installed and configured properly on your system, as memra relies on it for GPU acceleration.
Saves to your device
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Claude Code
mkdir -p ~/.claude/skills/memra && curl -fsSL https://workflowstacks.com/api/skills/memra/claude-skill -o ~/.claude/skills/memra/SKILL.md
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18
top-level files
9
folders
1322.5M
source size
Other
license
Key files
AGENTS.md
README.md
File tree
.cargo/
.github/
agent-knowledge/
crates/
deploy/
docs/
probe/
research/
tools/
.gitattributes
.gitignore
.ignore
AGENTS.md
ARCHITECTURE-H100.md
ARCHITECTURE.md
ASR-MODALITY-PLAN.md
bench_vllm.py
Cargo.lock
Cargo.toml
CITATION.cff
CONTRIBUTING.md
LICENSE
README.md
rust-toolchain.toml
Quick Actions
Details
Creator
avifenesh
Language
Rust
Category
local-ai
Published
7/5/2026

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