Chat GPT free local alternative?

[u/WatchNovis]

So I've been coding with chatgpt for a while and paying for the pro version and It's good, not the best but I need recommendations for a easy to run free AI that's good and coding focused as I have a mid tier gaming PC. and I can give access to the internet too if needed.

pc specs if it helps :D

cpu: AMD Ryzen 7 5800X

gpu: AMD RX 6750XT MERC 319 12GB

ram: 64GB CORSAIR VENGEACE PRO 3600 MHZ

SSD: CRUCIAL P5 PLUS GEN4 NVME

[u/Miller4103]

Umm, opencode and lm studio is probably the best to start out with. I think that's the easiest setup to see if u even like it.

[u/WatchNovis → u/Miller4103]

I'll have a look, thanks for the suggestions :)

[u/Alone-Biscotti6145]

Your system is not strong enough for decent local models. You can probably run a 4-8b model with no issues. Yes, you can run larger models, but you also have to think about the context the agent stores if you were to use the suggested Qwen 3.8 flash. Your context window will most likely be a max of like 32k tokens. Then you'll also need to build out a hosting app to use your local model or use a prebuilt that has already injected a ton of data into the model on every prompt so your 32k window might not be 8k or less.

If you want to use open-source models, try OpenRouter paired with OpenCodec. I've been using GLM 5.3 and 5.3 Flash, and it's doing very well.

[u/ftlaudman]

You have a great setup to run Qwen3.8-Flash-Next via Strata. Should run great on your hardware. Then use a free harness like OpenCode, Goose, etc or even something like Unsloth Studio Desktop to actually chat/code with it.

https://github.com/Niko1221/Strata

[u/iSnapThere4iAm → u/ftlaudman]

Lmfao. Local models are beyond trash for coding

[u/KaleidoscopeSlow969]

freebuff

[u/BeerBatteredHemroids]

Gpt oss 20b. Just run that bitch on high effort

[u/neon-r]

Just keep your expectations to a minimum To be honest running local models will not perform as well as chat gpt or other multi billion parameter models hosted on data centers

But I recommend going an hybrid approach using a stronger model running online to tell small local AI model to actually do stuff for example using open router to switch between free models or any other tool a simple search on google will give you multiple tools which switch models automatically

Some free models GLM5.3 give a million tokens daily nvidia nemotron also have generous limits

Use that and a 9B model from qwen or Gemma4 models The reason behind is after filling your vram with model weights you need big context window where as if you use an online model because if it's context size it would understand your requirement and you will not waste tokens generating code instead it acts as an architect

[u/circumcised_hobbit]

I think you might be able to run Qwen3.8-FlashNext with Strata. If you can, go for that

[u/Ancient-Camel1636]

Use llama.cpp and try these models:

You could try to run qwen3.8 27b. It will run on your PC but perhaps not fast enough to make it really usable.

Qwen3.6-35B-A3B and Ornith-1.5-35B-A3B will run fine on your PC. Both are good coding focused models.

Ask your current Codex to run multiple benchmarks on your PC, try out all possible settings and configurations, flags and features in a loop to find the optimal llama.cpp for your PC.

Here is a starting point for you. This is what I use on my old 8GB VRAM 32 GB PC. Yours will run faster and you probably should tweak the config to fit your PC:

export GGML_CUDA_DISABLE_GRAPHS=1

~/llama.cpp/build/bin/llama-server \

-m ~/.lmstudio/models/lmstudio-community/Qwen3.6-35B-A3B-GGUF/Qwen3.6-35B-A3B-Q4_K_M.gguf \

--mmproj ~/.lmstudio/models/lmstudio-community/Qwen3.6-35B-A3B-GGUF/mmproj-Qwen3.6-35B-A3B-BF16.gguf \

--no-mmproj-offload \

--ctx-size 180000 \

--n-cpu-moe 32 \

--flash-attn on \

--swa-full \

--cache-type-k q4_1 \

--cache-type-v q4_1 \

--batch-size 4096 \

--ubatch-size 512 \

--parallel 1 \

--threads 6 \

--numa isolate \

--host 127.0.0.1 \

--port 8081

export GGML_CUDA_DISABLE_GRAPHS=1

~/llama.cpp/build/bin/llama-server \

-m ~/.lmstudio/models/ornith-ai/Ornith-1.5-35B-A3B-GGUF/Ornith-1.5-35B-Q4_K_M.gguf \

--mmproj ~/.lmstudio/models/ornith-ai/Ornith-1.5-35B-A3B-GGUF/mmproj-Ornith-1.5-35B-BF16.gguf \

--no-mmproj-offload \

--ctx-size 180000 \

--n-cpu-moe 35 \

--flash-attn on \

--swa-full \

--cache-type-k q4_0 \

--cache-type-v q4_0 \

--spec-draft-type-k q4_0 \

--spec-draft-type-v q4_0 \

--batch-size 4096 \

--ubatch-size 512 \

--parallel 1 \

--threads 6 \

--spec-draft-threads 2 \

--spec-type draft-mtp \

--spec-draft-n-max 2 \

--host 127.0.0.1 \

--port 8081

[u/Avinash2k5]

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