Model ID
thinkingmachines/Inkling-Small
Capabilities
Inkling Small
Inkling Small is a multimodal Mixture-of-Experts model with 276B total parameters and 12B active parameters, designed for conversational, coding, retrieval, and agentic applications. It features a 42-layer decoder-only architecture with 32 attention heads, 256 routed experts activating 6 per token, and 2 shared experts. Supporting text, image, and audio inputs, it uses hybrid local and global attention with a 1M-token context window and a 512-token sliding window, while supporting BF16 and NVFP4 numerics.
About this model
Inkling Small is a multimodal Mixture-of-Experts model with 276B total parameters and 12B active parameters, designed for conversational, coding, retrieval, and agentic applications. It features a 42-layer decoder-only architecture with 32 attention heads, 256 routed experts activating 6 per token, and 2 shared experts. Supporting text, image, and audio inputs, it uses hybrid local and global attention with a 1M-token context window and a 512-token sliding window, while supporting BF16 and NVFP4 numerics.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (thinkingmachines/Inkling-Small). Released under Apache 2.0. Further reading: Blog
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Hardware
B200
1,440 GB
Engine
vLLM
SGLang
Deployment code
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Requires vllm/vllm-openai:nightly or any standard vLLM image v0.26.0+ to support this model configuration.
Performance under load
Tokens/s (total)
Benchmarks measured by Vultr on B200 · vLLM. Throughput and latency vary with concurrency, input length and engine configuration, so treat these as a comparison baseline, not a service guarantee.
NVIDIA HGX B200
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