Unverified50% confidenceFactExact time
Current open-source VLMs commonly range in size from 2B to over 70B, with 4B falling in the lightweight range.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
11/2/2026
First Seen
Valid until: 1/31/2027
Sources
Related Entities
Related Claims
UnverifiedThe context length of mainstream open-source multimodal models is typically between 4K and 32K tokens: LLaVA-1.5 is 4,096 tokens, Qwen-VL is 8,192 tokens, and InternVL2 extends to 32K.69% similarUnverifiedThe actual effective bits per weight (bpw) of mainstream quantization formats (such as AWQ, GPTQ, and GGUF K-Quants) is usually higher than 4; for example, INT4 AWQ with group_size=128 is about 4.5 bpw, and GGUF Q4_K_M is about 4.85 bpw.66% similarUnverifiedThe GGUF quantized version Q4_K_M of MiniCPM 2B has a model size of only 1.56G and can run smoothly on devices with 4G VRAM.64% similarUnverifiedOne B70 user running vLLM + GPT-Q INT4 quantization with MTP depth 4 achieved 84.6 tokens/s on a 27B model, but this only supports single-stream and uses different quantization, making direct comparison impossible.64% similarUnverifiedDeepSeek-V3 has a total of 685B parameters, and even after Q4 quantization its size still exceeds 400GB.64% similar
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