MiniCPM5-2B

Headlines · 3

1. 7d
   CamThink AI benchmarks small models on agent tasks

   CamThink AI evaluated six language models with 4 billion parameters or fewer on its own AI agent task set, according to a Reddit post from /u/KienShen. The models were Qwen3.5-4B, Spark-X2.6, LFM3-1.7B, LFM2.5-2.6B, Gemma 4 E2B and MiniCPM5-2B, but the submitted text provides no individual scores, methodology or full results. CamThink AI argues that the intelligence density of small models is improving rapidly, though that trend is a vendor claim.

   r/LocalLLaMA · 🔥 0
2. Nov 3
   LFM3-1.7B quantization report finds 3.6 GB lossless VRAM footprint

   A report shared on r/LocalLLaMA says LFM3-1.7B can run in 3.6 GB of VRAM with lossless quantization and 2.2 GB with modest degradation. It also cites LiquidAI's own benchmarks as placing LFM3-1.7B above MiniCPM5-2B, while claiming twice the context and roughly half the VRAM footprint for the quasi-lossless quantization.

   r/LocalLLaMA · 🔥 0
3. Oct 20
   Developer introduces source-available RK3588 NPU inference runtime

   Developer happyme531 introduced open_rknpu2_lm_infer, a local LLM inference engine for the Rockchip RK3588 NPU that runs without Rockchip's proprietary userspace inference libraries. Its host code is written in Rust and its NPU operators in C++. The project supports Qwen3.5-4B image input, optional MTP speculative decoding, an OpenAI-compatible API, streaming, tool calling and prefix caching. In a developer-published comparison, the engine with MTP1 recorded 10.61 tokens per second for decoding after 512 tokens, compared with 5.54 tokens per second for RKLLM 1.3.1. The report does not specify the test board, RAM configuration or driver versions and invites comparisons across boards and configurations.

   r/LocalLLaMA · 🔥 0

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