StartLux-Decision-v1-0.8B
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。
基本情報を収録・詳細は順次追加
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗DISCOVER & COMPARE
AIモデルを探す 37
StartLux-Decision-v1-0.8B-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。
基本情報を収録・詳細は順次追加
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1-0.8B-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。
基本情報を収録・詳細は順次追加
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1-0.8B-Q8_0-GGUF
startlux-modelsStartLux-Decision-v1-0.8B 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. At this size Q4_K_M changes noticeably more answers (93.1% the same), so Q8_0 is the better choice. `-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).
翻訳待ち・原文を表示
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1.1-0.8B-Instant
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。
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1.1-0.8B-Instant-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。
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1.1-27B-AutoThink
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。
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1.1-27B-AutoThink-GGUF
startlux-modelsFormats: BF16 · **GGUF** · MLX 8-bit · MLX 4-bit · Code: StartLuxLabs/StartLux-Decision · Paper: arXiv 2610.17309 Decision Index 0.3, public subset, as of 11 October 2026: the StartLux-Decision Instant models against other decision models of each size. Figure 1 of the technical report . The DecisionPivot column is the mean chance-corrected accuracy over the seven layers of the benchmark's scorer on its 7,800 core items, from the report's measurements: the GGUF files on llama.cpp (release b11549), the BF16 weights on vLLM. For an AutoThink model the rows therefore also compare two engines. The Q8_0 file scored 2.7 points above BF16 (95% interval +1.3 to +4.1), but as the two runs used different engines, the difference does not isolate the format. Q8_0 is the recommended file; Q4_K_M lost up to 3.8 points across the sizes.
翻訳待ち・原文を表示
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1.1-27B-Instant
startlux-modelsStartLux-Decision-v1.1-27B-Instant is a 27B decision model. You give it a state (text or JSON, with up to 8 images) and typed questions about it: pick one of several options (`choice`), yes or no (`noul`), or a level on a scale of 2 to 10 (`score`). It returns a probability for every option of every question from one forward pass, without generating text. The request and response format is compatible with the System One `/v1/systemone` API. Formats: **BF16** · GGUF · MLX 8-bit · MLX 4-bit · Code: StartLuxLabs/StartLux-Decision · Paper: arXiv 2610.17309 Family: 0.8B Instant · 2B Instant · 4B Instant · 4B AutoThink · 9B Instant · 9B AutoThink · **27B Instant** · 27B AutoThink
翻訳待ち・原文を表示
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1.1-27B-Instant-GGUF
startlux-modelsFormats: BF16 · **GGUF** · Code: StartLuxLabs/StartLux-Decision · Paper: arXiv 2610.17309 Decision Index 0.3, public subset, as of 11 October 2026: the StartLux-Decision Instant models against other decision models of each size. Figure 1 of the technical report . The DecisionPivot column is the mean chance-corrected accuracy over the seven layers of the benchmark's scorer on its 7,800 core items, from the report's measurements: the GGUF files on llama.cpp (release b11549), the BF16 weights on vLLM. Q8_0 is the recommended file; Q4_K_M lost up to 3.8 points across the sizes.
翻訳待ち・原文を表示
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1.1-2B-Instant
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。
基本情報を収録・詳細は順次追加
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1.1-2B-Instant-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。
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1.1-4B-AutoThink
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。
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1.1-4B-AutoThink-GGUF
startlux-modelsStartLux-Decision-v1.1-4B-AutoThink as GGUF files for llama.cpp, in Q8_0 (8-bit) and Q4_K_M (4-bit). StartLux-Decision-v1.1-4B-AutoThink is a 4B decision model that thinks only where its one-pass answer is uncertain. Given a state (text or JSON) and typed questions about it (pick an option, yes or no, or a level on a scale of 2 to 10), it reads a probability for every option from the option letters in one pass; where the top probability is below 0.90 it writes a thought of at most 4,096 tokens and reads the answer again, and the default answer is 0.25 × the first read-out + 0.75 × the second. Requests and responses use the TypeSafe `/v1/systemone` format. Formats: BF16 · **GGUF** · MLX 8-bit · MLX 4-bit · Code: StartLuxLabs/StartLux-Decision · Paper: arXiv 2610.17309 Decision Index 0.3, public subset, as of 11 October 2026: the StartLux-Decision Instant models against other decision models of each size. Figure 1 of the technical report .
翻訳待ち・原文を表示
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1.1-4B-Instant
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。
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1.1-4B-Instant-GGUF
startlux-modelsFormats: BF16 · **GGUF** · MLX 8-bit · MLX 4-bit · Code: StartLuxLabs/StartLux-Decision · Paper: arXiv 2610.17309 Decision Index 0.3, public subset, as of 11 October 2026: the StartLux-Decision Instant models against other decision models of each size. Figure 1 of the technical report . The DecisionPivot column is the mean chance-corrected accuracy over the seven layers of the benchmark's scorer on its 7,800 core items, from the report's measurements: the GGUF files on llama.cpp (release b11549), the BF16 weights on vLLM. Q8_0 is the recommended file; Q4_K_M lost up to 3.8 points across the sizes.
翻訳待ち・原文を表示
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1.1-9B-AutoThink
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。
基本情報を収録・詳細は順次追加
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1.1-9B-AutoThink-GGUF
startlux-modelsStartLux-Decision-v1.1-9B-AutoThink as GGUF files for llama.cpp, in Q8_0 (8-bit) and Q4_K_M (4-bit). StartLux-Decision-v1.1-9B-AutoThink is a 9B decision model that thinks only where its one-pass answer is uncertain. Given a state (text or JSON) and typed questions about it (pick an option, yes or no, or a level on a scale of 2 to 10), it reads a probability for every option from the option letters in one pass; where the top probability is below 0.90 it writes a thought of at most 4,096 tokens and reads the answer again, and the default answer is 0.25 × the first read-out + 0.75 × the second. Requests and responses use the TypeSafe `/v1/systemone` format. Formats: BF16 · **GGUF** · MLX 8-bit · MLX 4-bit · Code: StartLuxLabs/StartLux-Decision · Paper: arXiv 2610.17309 Decision Index 0.3, public subset, as of 11 October 2026: the StartLux-Decision Instant models against other decision models of each size. Figure 1 of the technical report .
翻訳待ち・原文を表示
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1.1-9B-Instant
startlux-modelsStartLux-Decision-v1.1-9B-Instant is a 9B decision model. You give it a state (text or JSON, with up to 8 images) and typed questions about it: pick one of several options (`choice`), yes or no (`noul`), or a level on a scale of 2 to 10 (`score`). It returns a probability for every option of every question from one forward pass, without generating text. The request and response format is compatible with the System One `/v1/systemone` API. Formats: **BF16** · GGUF · MLX 8-bit · MLX 4-bit · Code: StartLuxLabs/StartLux-Decision · Paper: arXiv 2610.17309 Family: 0.8B Instant · 2B Instant · 4B Instant · 4B AutoThink · **9B Instant** · 9B AutoThink · 27B Instant · 27B AutoThink
翻訳待ち・原文を表示
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1.1-9B-Instant-GGUF
startlux-modelsStartLux-Decision-v1.1-9B-Instant as GGUF files for llama.cpp, in Q8_0 (8-bit) and Q4_K_M (4-bit). StartLux-Decision-v1.1-9B-Instant is a 9B decision model. Given a state (text or JSON) and typed questions about it (pick an option, yes or no, or a level on a scale of 2 to 10), it returns a probability for every option of every question from one forward pass, without generating text. Requests and responses use the TypeSafe `/v1/systemone` format. Formats: BF16 · **GGUF** · MLX 8-bit · MLX 4-bit · Code: StartLuxLabs/StartLux-Decision · Paper: arXiv 2610.17309 Decision Index 0.3, public subset, as of 11 October 2026: the StartLux-Decision Instant models against other decision models of each size. Figure 1 of the technical report .
翻訳待ち・原文を表示
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1-27B
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。
基本情報を収録・詳細は順次追加
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1-27B-BF16-GGUF
startlux-modelsStartLux-Decision-v1-27B in BF16 (16-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).
翻訳待ち・原文を表示
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1-27B-Q4_K_M-GGUF
startlux-modelsStartLux-Decision-v1-27B 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).
翻訳待ち・原文を表示
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗StartLux-Decision-v1-27B-Q8_0-GGUF
startlux-modelsStartLux-Decision-v1-27B 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).
翻訳待ち・原文を表示
入力 未確認→ 出力 未確認
料金未確認マルチモーダル・チャネル料金は個別に確認
詳細を見る ↗該当するモデルがありません
提供元・分類・入出力の条件を変更してください。新しいモデルを随時追加しています。
COST EXPLORER
モデル選びに、費用の視点も。
月間トークン数を調整してAPI費用を比較。
1 M = 100万トークン・米ドル
同一チャネルの基本テキスト料金を比較
同一チャネルの基本テキスト料金を比較
収集済みの比較可能な100万トークン当たり米ドル料金です。キャッシュ割引、段階料金、追加推論出力、税金は含みません。最新料金は出典で確認してください。
MODEL HANDBOOK
モデルを理解して選ぶ
API料金はどう比較しますか？+
入力・出力・キャッシュ料金を分け、同じ用途と使用量で総費用を比較します。画像・音声・動画は枚数、時間、解像度で課金される場合があります。
オープンウェイトは無料で商用利用できますか？+
必ずしもそうではありません。バージョンごとのライセンス、商用制限、ポリシーを確認してください。自前運用には計算資源と保守費用も必要です。
ランキング1位が最適ですか？+
順位はテスト、バージョン、評価方法によります。実際の業務データで精度、遅延、安定性、費用を比較してください。