StartLux-Decision-v1-2B
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StartLux-Decision-v1-2B-BF16-GGUF
startlux-models基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗StartLux-Decision-v1-2B-Q4_K_M-GGUF
startlux-models基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗StartLux-Decision-v1-2B-Q8_0-GGUF
startlux-models基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗StartLux-Decision-v1-35B-A3B
startlux-modelsStartLux-Decision-v1-35B-A3B answers typed questions about a state: pick one of several options, yes or no, or a rating on a scale. The state can be text, JSON or images, up to 262,144 tokens (256K). Every question comes back with a probability for each option. Requests and responses use the TypeSafe `/v1/systemone` format, so clients written for Jev work unchanged. It is a mixture of experts: about 35B parameters, of which about 3B are active for each token. It answers in half the time of StartLux-Decision-v1-27B, has the highest JevBench and Intern-Decision numbers of the family, and is 2.3 points below the 27B on Decision Index 0.2.1. JevBench public counts the correct answers on the 231 public items in the Intern-Decision bundle; Intern avg is the average accuracy over its seven suites; DI is the Decision Index under both editions, the public board's values for the other systems. A blank cell means the number is not published. StartLux-Decision latencies are for one H200, with the three questions answered in one forward pass. ¹ Intern-Decision's own measurement on an RTX 4090. ² The server time the TypeSafe API gateway reports for the same request, mean of 100, network left out as in ours; Intern-Decision reports 109.7 ms end to end.
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View details ↗StartLux-Decision-v1-4B
startlux-models基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗StartLux-Decision-v1-4B-BF16-GGUF
startlux-models基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗StartLux-Decision-v1-4B-Q4_K_M-GGUF
startlux-modelsStartLux-Decision-v1-4B in Q4_K_M (4-bit) as a GGUF file for llama.cpp. The decision server in this repository turns it into the same typed decisions, with a probability for every option, as the original model. "Same decision" is the share of the 231 public JevBench items on which the file picks the same answer as the original weights run through the `startlux_decision` package, with the same prompts, readout and temperatures. Q8_0 and Q4_K_M are llama.cpp's standard quantizations of BF16, without an importance matrix. `-ngl 99` puts every layer on the GPU (CUDA or Metal); leave it out on a CPU-only machine. llama.cpp has to be recent enough for this model (build b10454 or newer).
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View details ↗StartLux-Decision-v1-4B-Q8_0-GGUF
startlux-modelsStartLux-Decision-v1-4B in Q8_0 (8-bit) as a GGUF file for llama.cpp. The decision server in this repository turns it into the same typed decisions, with a probability for every option, as the original model. "Same decision" is the share of the 231 public JevBench items on which the file picks the same answer as the original weights run through the `startlux_decision` package, with the same prompts, readout and temperatures. Q8_0 and Q4_K_M are llama.cpp's standard quantizations of BF16, without an importance matrix. `-ngl 99` puts every layer on the GPU (CUDA or Metal); leave it out on a CPU-only machine. llama.cpp has to be recent enough for this model (build b10454 or newer).
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View details ↗StartLux-Decision-v1-9B
startlux-models基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗StartLux-Decision-v1-9B-BF16-GGUF
startlux-models基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗StartLux-Decision-v1-9B-Q4_K_M-GGUF
startlux-modelsStartLux-Decision-v1-9B in Q4_K_M (4-bit) as a GGUF file for llama.cpp. The decision server in this repository turns it into the same typed decisions, with a probability for every option, as the original model. "Same decision" is the share of the 231 public JevBench items on which the file picks the same answer as the original weights run through the `startlux_decision` package, with the same prompts, readout and temperatures. Q8_0 and Q4_K_M are llama.cpp's standard quantizations of BF16, without an importance matrix. `-ngl 99` puts every layer on the GPU (CUDA or Metal); leave it out on a CPU-only machine. llama.cpp has to be recent enough for this model (build b10454 or newer).
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View details ↗StartLux-Decision-v1-9B-Q8_0-GGUF
startlux-models"Same decision" is the share of the 231 public JevBench items on which the file picks the same answer as the original weights run through the `startlux_decision` package, with the same prompts, readout and temperatures. Q8_0 and Q4_K_M are llama.cpp's standard quantizations of BF16, without an importance matrix. `-ngl 99` puts every layer on the GPU (CUDA or Metal); leave it out on a CPU-only machine. llama.cpp has to be recent enough for this model (build b10454 or newer). Plain chat with a GGUF file does not give these decisions: the option-letter readout and the per-type temperatures live in `gguf_server.py`, not in the weights. The file holds the text decoder only.
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