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Ds4 Alternatives
Similar projects and alternatives to ds4
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ollama
Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.
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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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plannotator
Annotate and review coding agent plans and code diffs visually, share with your team, send feedback to agents with one click.
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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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nono
Capability-based agent runtime with fine-grained policies . Brokering access directly within the agent's operating context, with zero setup and zero latency
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yzma
Go with your own intelligence - Go applications that directly integrate llama.cpp for local inference using hardware acceleration.
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 2026-06-05.
- Ask HN: What is your (AI) dev tech stack / workflow? (June 2026)
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Redis 8.8: New array data structure, rate limiter, performance improvements
The experimental SSD streaming branch https://github.com/antirez/ds4/tree/streaming - author's demo @ https://x.com/antirez/status/2062536214675067322 is great news for that project, allowing for SOTA inference (DeepSeek V4 Flash and Pro!) on RAM-limited machines. Now we need work on large-ish scale batching in order to recover tok/s under the SSD streaming scenario. It's not helpful when running normally (at least not on Apple Silicon) since thermal/power throttling is the constraint in that case, but SSD streaming is a whole other consideration.
- Nvidia RTX Spark
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Was my $48K GPU server worth it?
I have two of the M3s due testing of models at work and with exo I can run decent quantization with 1 millon tokens for memory and derailment tests.
Slow? Yes, but ... private. Unconditionally.
And recently with https://github.com/antirez/ds4 one can use just one system to a very, very decent speed and ttft for chat inference. Again, private.
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OpenAI Is Preparing to File for an IPO Soon
You only need about a mac w 96GB or 128gb to run deepseek v4flash with ds4(https://github.com/antirez/ds4). Works mostly well
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Notes + Local AI: Simpler Than You Think
I can point Claude or Qwen or DS4 at the notes folder and say "read my meeting notes from the last week, find follow-up items related to product issues, and create a Linear ticket for each one." First time I ran it, it made 20 tickets. A full week of calls where customers had mentioned things in passing, I'd written them down, and nothing had happened. One pass, done.
- Gemini 3.5: frontier intelligence with action
- antirez lanza DS4: corre DeepSeek v4 Flash local en Mac de 128 GB
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A Few Words on DS4
More information about DwarfStar 4 (DS4) in the readme: https://github.com/antirez/ds4
The code seems based on llama.cpp and GGML.
I don't fully understand why it is a standalone project. The readme discusses this: DwarfStar 4 is a small native inference engine specific for DeepSeek V4 Flash. It is intentionally narrow: ...
I think the only bigger difference in DeepSeek V4 vs other models is maybe the type of self-attention. And that leads to: KV cache is actually a first-class disk citizen.
But I still feel like those changes could have been implemented as part of some of the other local engines.
I also assume more models will come out, not just from DeepSeek but also from others, and they might share similar self-attention approaches, that would benefit from a similar KV cache implementation.
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Ask HN: Are we gonna back less powerful local LLMs
I think the trend is that top models are meant for companies. Small devs did our job of hyping and training and we can now either pay way more, or pay more and use not sota models, or give our data to access train chinese models in hopes they keep 6 months behind in the cold war and need still need some of our input, or invest around 5-10K for powerful local personal AI [0].
On the other hand I think that AI can really raise the bar of "average tech", and we devs are wired to think that better tech == more value... but this might not be the case in the many many many cases where existing average tech and velocity is already good enough and the real moat is the handshake, trust, marketing, etc etc
[0] https://github.com/antirez/ds4
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A note from our sponsor - SaaSHub
www.saashub.com | 9 Jun 2026
Stats
Basic ds4 repo stats
13
53
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about 1 month 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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