Qwen3 Coder 30B A3B Instruct NVFP4

Qwen 3

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released May 2025262K context≈ 196,608 words30B params

A code-focused model from the Qwen3 family, quantized to NVFP4 precision with a mixture-of-experts architecture that activates around 3 billion parameters out of 30 billion total. The reduced precision and selective parameter activation make it more efficient to run while preserving much of the full model's capability. It handles a very large context window of 262k tokens, useful for working across large codebases.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Reasoning & Logic

Moderate

Creative Writing

Qwen3 Coder 30B A3B Instruct NVFP4

Qwen 3

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released May 2025262K context≈ 196,608 words30B params

A code-focused model from the Qwen3 family, quantized to NVFP4 precision with a mixture-of-experts architecture that activates around 3 billion parameters out of 30 billion total. The reduced precision and selective parameter activation make it more efficient to run while preserving much of the full model's capability. It handles a very large context window of 262k tokens, useful for working across large codebases.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Reasoning & Logic

Moderate

Creative Writing

Glossary

ArchitectureThe underlying structural design of a neural network that defines how data flows through layers and components.Context WindowThe maximum number of tokens a model can process in a single conversation or prompt.NVFP4 PrecisionA low-precision numerical format that uses 4 bits per weight, developed by NVIDIA to compress models for efficient inference on consumer hardware.NVFP4 PrecisionA low-precision numerical format optimized by NVIDIA that uses fewer bits per number than standard formats, enabling efficient inference on NVIDIA GPUs while maintaining reasonable accuracy.Parameter ActivationThe process of selectively using only a subset of a model's total parameters during inference, reducing computational cost while maintaining performance.ParametersThe learned numerical values in a model — more parameters generally means more capacity but higher compute cost.PrecisionThe level of numerical detail a model uses to represent its internal values; higher precision means more accurate calculations but requires more memory.QuantizedA technique that reduces a model's size and memory usage by storing weights with lower precision (fewer bits), trading some accuracy for efficiency.Selective Parameter ActivationA technique where only a subset of a model's weights are used for each input, rather than activating all parameters, which reduces memory usage and speeds up inference.TokensThe basic units of text that a language model processes, typically representing words or word fragments.

Capabilities

Capabilities

Use Case Fit

Glossary