A user on LocalLLaMA surfaced a practical problem on April 13th: when running llama-server with certain models — particularly those trained with explicit reasoning or "thinking" steps baked into their output — there's no obvious configuration flag to suppress that internal monologue. The models, increasingly built around chain-of-thought architectures, want to show their work. The question is whether operators running inference servers actually want that verbosity in production, or whether they need clean, direct outputs without the cognitive scaffolding. The post scored modestly, suggesting either a niche audience or a problem that hasn't yet reached critical mass — possibly both.
If confirmed as a genuine gap in llama-server's configuration options, here is what this means. Developers building applications on top of locally-hosted models — customer-facing tools, pipelines where token efficiency matters, anything with latency constraints — need control over output structure. A reasoning model that insists on narrating its thought process burns tokens, increases response time, and can break downstream parsing logic that expects clean text. The second-order effect is strategic: as more capable thinking models get quantised and deployed locally through tools like llama.cpp, the gap between raw model capability and production-ready inference tooling becomes a real friction point. Someone has to solve this, either through model-level prompt engineering, server-side filtering, or an explicit configuration parameter — and right now it's not obvious which layer owns the problem.
Watch for a response from the llama.cpp maintainers or a community-contributed workaround that clarifies whether this is a known limitation, a planned feature, or simply a configuration step that isn't well documented yet.
<!-- SC_OFF --><div class="md"><p>I build context/harness optimization tooling, so provider-side serialization quirks actually matter to me. If you're optimizing over prompts, you
<!-- SC_OFF --><div class="md"><p>I am running <code>unsloth/gemma-4-26B-A4B-it-GGUF/gemma-4-26B-A4B-it-UD-Q4_K_XL.gguf</code> with llama-server (with reasoning enabled). </p>
<!-- SC_OFF --><div class="md"><p>Even the trick of editing the reply with the tag <think> or <|think|> doesn't do anything for me. On some models I used to be able to
<!-- SC_OFF --><div class="md"><blockquote> <p>Wait, I need to be careful about the "no_think" tag in the system prompt. The system prompt says <code>/no_think</code>.
<!-- SC_OFF --><div class="md"><p>I run ollama in combination with LibreChat using docker compose. Have been using gemma3 for quite some time. Now switched to gemma4 only to
<!-- SC_OFF --><div class="md"><p>I can't get my model to think. According to the <a href="https://huggingface.co/google/gemma-4-31B">documentation</a>, thinking should be
<!-- SC_OFF --><div class="md"><p>In my testing, i have only seen improvements in response on specific “misguided attention” questions for models below 10b.</p> <p>Example: Gemma
<!-- SC_OFF --><div class="md"><p>Heyo everyone,</p> <p>I'm running an OpenWebUI instance with an Ollama backend on a 1x RTX4090 (24GB) & 13900K (64GB) rig.</p> <p>I've been
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