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Ds4 Alternatives
Similar projects and alternatives to ds4
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AppSignal
Monitoring that respects your time & budget. APM, error tracking, and dashboards for modern web apps. Ten-minute setup, transparent flat pricing, and support from engineers who actually use the product.
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Redis
For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.
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zed
Code at the speed of thought – Zed is a high-performance, multiplayer code editor from the creators of Atom and Tree-sitter.
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kvrocks
Apache Kvrocks is a distributed key value NoSQL database that uses RocksDB as storage engine and is compatible with Redis protocol.
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omlx
LLM inference server with continuous batching & SSD caching for Apple Silicon — managed from the macOS menu bar
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SaaSHub
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colibri
Run frontier MoE models on hardware you already own — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦
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Strata
Qwen3.8-Flash-Next on any consumer hardware: one-click install for Windows / Linux. Strata inference engine, OpenAI/Anthropic API on localhost, optional image input. (by Niko1221)
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club-3090
Community recipes for serving LLMs on RTX 3090. Multi-engine (vLLM, llama.cpp, SGLang) and model-agnostic. Currently shipping Qwen3.6-27B configs for 1× and 2× cards.
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kilocode
Kilo is the all-in-one agentic engineering platform. Build, ship, and iterate faster with the most popular open source coding agent.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better ds4 alternative or higher similarity.
ds4 discussion
ds4 reviews and mentions
Posts with mentions or reviews of ds4.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2026-10-04.
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Run Qwen 3.8 Flash Next (125B) on consumer hardware (RTX 4090) at 100T/s
Dwarfstar already supports this, curious how it compares, but I use the q4 quant daily and it works really well.
https://github.com/antirez/ds4/blob/main/docs/MODELS.md#qwen...
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Run DeepSeek V4 on Your Own Hardware With DwarfStar, the Redis Creator's New Inference Engine
git clone https://github.com/antirez/ds4.git cd ds4 make # Metal on Apple Silicon ./download_model.sh ds4f-q2
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The Redis Guy Wrote a Local LLM Engine That Refuses to Be General. That's Why It Works.
git clone https://github.com/antirez/ds4 cd ds4 && ./download_model.sh ds4f-q2 make # macOS / Metal # make cuda-spark # Linux / DGX Spark ./ds4 # interactive CLI ./ds4-server --ctx 100000 # OpenAI + Anthropic style API
- From the creator of Redis; run LLM locally with ds4
- Directional steering is a runtime activation edit for DS4
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Pirate Face Rescues LLM Models from Deletion
Speaking to the "uncensored model" angle: there's little reason to distribute abliterated weights anyway. Instead of orthogonalising the weights that write back to the residual stream, you can just orthogonalise the activations themselves. It's equivalent.
Orthogonalising activations at runtime is computationally cheap. Just distribute the refusal vectors (few thousand floats per layer), then run against the stock weights. Antirez's DS4 already supports this: https://github.com/antirez/ds4/blob/8db1d1d155cb0400a86a86b9...
Abliterated weights are just a bad habit we've gotten into. It's also deeply suboptimal from a precision point of view to take a model that's already been QATed and distributed in pre-quantised form (DeepSeek V4, Kimi K2.5 or K3...), modify its weights, and re-quantise it.
- Dwarf Star Support for Qwen3.8 Flash Next
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Dwarf Star Support for DeepSeek 4.1 Flash on MBPro 128GB
Antirez just landed a commit[1] to the github repo for DwarfStar that adds support for his heavily quantized variant of DeepSeek V4.1 Flash.
He claims it runs with SSD streaming on a macbook pro M5-Max 128 GB laptop. The code was just checked in literally hours ago, so take YMMV quite literally.
[1] https://github.com/antirez/ds4/commit/bd66c402070042bf0a79ad6ece8242de4c93680c
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How accurate have Ed Zitron's AI skeptic predictions been?
Something Cherny said in early December last year is clearly not relevant anymore.
By late December he said: "100% of my contributions to Claude Code were written by Claude Code"[1]. That's production software shipping to millions of people.
Antirez's Dwarfstar is also mostly AI written:
> This software is developed with strong assistance from GPT 5.5, 5.6, Claude Fable and with humans leading the ideas, testing, and debugging. We say this openly because it shaped how the project was built. If you are not happy with AI-developed code, this software is not for you. [2]
I'm actually pretty shocked anyone would claim otherwise. In January 2026, sure, but the world has changed since then. Many, many places are doing 100% AI code now, and yes for production code. https://www.businessinsider.com/ai-writing-all-startup-code-...
[1] https://x.com/bcherny/status/2004897269674639461
[2] https://github.com/antirez/ds4
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Apple Caught Off Guard by AI Demand for Mac Mini and Mac Studio
I agree about getting the Ultra if you're interested in AI (LLM) inference speed. I'm a little perplexed as to why there isn't a RAM option in between 96GB and 256GB, though. For instance, I believe Deepseek v4 flash runs a lot faster on (https://github.com/antirez/ds4) with 128GB than 96. I assume the higher SKUs have low enough sales that Apple doesn't want to be manufacturing too many different RAM configs as that would eat into their margins. (I say this as someone interested in AI hardware in general, even the 96GB is out of my price range).
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Stats
Basic ds4 repo stats
48
53
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5 months ago
antirez/ds4 is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of ds4 is C.
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