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Show HN: First Claude Code client for Ollama local models
Just to clarify the background a bit. This project wasn’t planned as a big standalone release at first. On January 16, Ollama added support for an Anthropic-compatible API, and I was curious how far this could be pushed in practice. I decided to try plugging local Ollama models directly into a Claude Code-style workflow and see if it would actually work end to end.
Here is the release note from Ollama that made this possible: https://ollama.com/blog/claude https://ollama.com/blog/claude
Technically, what I do is pretty straightforward:
- Detect which local models are available in Ollama.
- When internet access is unavailable, the client automatically switches to Ollama-backed local models instead of remote ones.
- From the user’s perspective, it is the same Claude Code flow, just backed by local inference.
In practice, the best-performing model so far has been qwen3-coder:30b. I also tested glm-4.7-flash, which was released very recently, but it struggles with reliably following tool-calling instructions, so it is not usable for this workflow yet.
- mchiang 8mo agohey, thanks for sharing. I had to go to the Twitter feed to find the GitHub link: https://github.com/21st-dev/1code https://github.com/21st-dev/1code
- dang 8mo agoThanks for catching that. I've changed the URL at the top to that from https://twitter.com/serafimcloud/status/2014266928853110862 https://twitter.com/serafimcloud/status/2014266928853110862 now.
- dosinga 8mo agothis is cool. not sure it is the first claude code style coding agent that runs against Ollama models though. goose, opencode and others have been able to do that a while no?
- eli 8mo agoThere are already various proxies to translate between OpenAI-style models (local or otherwise) and an Anthropic endpoint that Claude Code can talk to. Is the advantage here just one less piece of infrastructure to worry about?
- g4cg54g54 8mo agosiderailing here - but got one that _actually_ works? in particular i´d like to call claude-models - in openai-schema hosted by a reseller - with some proxy that offers anthropic format to my claude --- but it seems like nothing gets to fully line things up (double-translated tool names for example) reseller is abacus.ai - tried BerriAI/litellm, musistudio/claude-code-router, ziozzang/claude2openai-proxy, 1rgs/claude-code-proxy, fuergaosi233/claude-code-proxy,
- kristopolous 8mo agoWhat probably needs to exist is something like `llsed`. The invocation would be like this llsed --host 0.0.0.0 --port 8080 --map_file claude_to_openai.json --server https://openrouter.ai/api Where the json has something like { tag: ... from: ..., to: ..., params: ..., pre: ..., post: ...} So if one call is two, you can call multiple in the pre or post or rearrange things accordingly. This sounds like the proper separation of concerns here... probably The pre/post should probably be json-rpc that get lazy loaded. Writing that now. Let's do this: https://github.com/day50-dev/llsed https://github.com/day50-dev/llsed
- eli 8mo agoSome unsolicited advice: Streaming support is tricky. I'd strip the streaming out when you proxy until everything else is solid.
- kristopolous 8mo agoCool. Sounds good. Thanks. I'll do it. This will be a bit challenging I'm sure but I agree, litellm and friends do too many things and take too long to get simple asks from I've been pitching this suite I'm building as "GNU coreutils for the LLM era" It's not sticking and nobody is hyped by it. I don't know if I should keep going or if this is my same old pattern cropping up again of things I really really like but just kinda me
- 8mo ago
- oceanplexian 8mo agoThe Anthropic API was already supported by llama.cpp (The project Ollama ripped off and typically lags in features by 3-6 months), which already works perfectly fine with Claude Code by setting a simple environment variable.
- xd1936 8mo agoAnd they reference that announcement and related information in the second line.
- gcr 8mo agoWhich announcement are you looking at? I see no references to llama-cpp in either Ollama's blog post or this project's github page.
- davely 8mo agoPoint of clarification: llama.cpp is MIT-licensed. Using it downstream (commercially or otherwise) is exactly what that license allows, so calling it a rip-off is misleading.
- d0100 8mo agoDoes this UI work with Open Code?
- smissingham 8mo ago[dead]
- horacemorace 8mo agoI was trying to get Claude code to work with llama.cpp but could never figure out anything functional. It always insisted on a phone home login for first time setup. In cline I’m getting better results with glm-4.7-flash than with qwen3-coder:30b
- g4cg54g54 8mo ago~/.claude.json with {"hasCompletedOnboarding":true} is the key, then ANTHROPIC_BASE_URL and ANTHROPIC_AUTH_TOKEN work as expected
- d4rkp4ttern 8mo agoCurious what llama-server flags you used. On my M1 Max 64GB MacBook I tried it in Claude Code (which has a 25K system message) and I get 3 tps. But with Qwen3-30B-A3B I get 20 tps in CC.
- dsrtslnd23 8mo agoWhat hardware are you running the 30b model on? I guess it needs at least 24GB VRAM for decent inference speeds.
- ryandrake 8mo agoI'd like to know this, too. I'm just getting started getting my feet wet with ollama and local models using just CPU, and it's obviously terribly slow (even 24 cores, 128GB DRAM. It's hard to gauge how much GPU money I'd need to plonk down to get acceptable performance for coding workflows.
- storystarling 8mo agoI tried to build a similar local stack recently to save on API costs. In practice I found the hardware savings are a bit of a mirage for coding workflows. The local models hallucinate just enough that you end up spending more in lost time debugging than you would have paid for Sonnet or Opus to get it right the first time.
- thtmnisamnstr 8mo agoThe general rule to follow is that you need as much VRAM as the model size. 30b models are usually around 19GB. So, most likely a GPU with 24GB of VRAM.
- 3836293648 8mo agoBut this also means tiny context windows. You can't fit gpt-oss:20b + more than a tiny file + instructions into 24GB
- blizdiddy 8mo agoGpt-oss is natively 4-bit, so you kinda can
- 3836293648 8mo ago
- d4rkp4ttern 8mo agoAs others said this was possible for months already with llama-cop’s support for Anthropic messages API. You just need to set the ANTHROPIC_BASE_URL. The specific llama-server settings/flags were a pain to figure out and required some hunting, so I collected them in this guide to using CC with local models: https://github.com/pchalasani/claude-code-tools/blob/main/docs/local-llm-setup.md https://github.com/pchalasani/claude-code-tools/blob/main/do... One tricky thing that took me a whole day to figure out is that using Claude Code in this setup was causing total network failures due to telemetry pings, so I had to set this env var to 1: CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC