DeepSeek LLM 67B (V1)

Independent researcher (togethercomputer/MoA issue #41) 公开的研究与报告生成案例，来源为 公开代码库，复核于 2026-06-27T05:40:00Z。 Model Atlas 将它标记为 A 类证据，因为它同时具备具体使用者、具体任务、公开原始证据和可访问产物。

任务：这是一个围绕研究分析和报告生成的真实任务，公开材料可以回溯到具体使用者和具体产物。 原始资料写作：A researcher configured a Mixture of Agents (MoA) pipeline using deepseek-llm-67b-chat as one of five intermediate-layer reference models alongside WizardLM-2-8x22B, Mixtral-8x7B-Instruct, Qwen2-72B-Instruct, and Llama-…

公开产物：公开材料提供公开代码、README 或项目配置，可用于核验任务结果、项目形态和模型绑定关系。 原始资料写作：The MoA configuration including deepseek-llm-67b-chat as an intermediate model did not outperform the single-model (no MoA) baseline on GSM8K. Both settings achieved equally on math reasoning, suggesting that for this s…

模型作用：DeepSeek LLM 67B Chat 在该案例中承担研究分析和报告生成相关的生成、分析、编排或实现角色。 原始资料写作：DeepSeek LLM 67B Chat contributed as one of five diverse intermediate reasoning models in the MoA ensemble. Its inclusion provided another perspective in the aggregation step, though the experiment showed diminishing re…

A 类理由：有具体使用者、具体任务、公开原始证据和可访问产物，可公开核验。

风险边界：当前判断基于公开材料；若产物下线、仓库变更或模型参与比例仅来自作者自述，需要在引用前重新复核。 原始资料写作：Research experiment, not production deployment; MoA is a specific ensemble technique; single model results not individually reported for deepseek-llm-67b-chat in isolation.

原始记录：Researcher uses DeepSeek LLM 67B Chat as intermediate layer in Mixture of Agents for GSM8K math reasoning

Shopify (Shopify/reasonableai) 公开的真实任务执行案例，来源为 公开代码库，复核于 2026-06-27T05:40:00Z。 Model Atlas 将它标记为 A 类证据，因为它同时具备具体使用者、具体任务、公开原始证据和可访问产物。

任务：这是一个围绕真实任务执行的真实任务，公开材料可以回溯到具体使用者和具体产物。 原始资料写作：Shopify's ReasonableAI team benchmarked deepseek-llm:67b-chat (via Ollama) alongside mistral:latest, mixtral:latest, and llama2:13b on query classification prompts for customer support routing. Each model was run 5 time…

公开产物：公开材料提供公开代码、README 或项目配置，可用于核验任务结果、项目形态和模型绑定关系。 原始资料写作：All four models returned the same and consistent classification results across 5 runs with 0.0 temperature. Mistral achieved the best overall performance on the classification task, but DeepSeek LLM 67B Chat demonstrate…

模型作用：DeepSeek LLM 67B Chat 在该案例中承担真实任务执行相关的生成、分析、编排或实现角色。 原始资料写作：DeepSeek LLM 67B Chat provided deterministic, consistent query classification outputs across multiple runs, validating its suitability as a candidate for production customer support routing at Shopify. The evaluation sh…

A 类理由：有具体使用者、具体任务、公开原始证据和可访问产物，可公开核验。

风险边界：当前判断基于公开材料；若产物下线、仓库变更或模型参与比例仅来自作者自述，需要在引用前重新复核。 原始资料写作：Benchmarking-only (not confirmed production deployment); evaluation was internal to Shopify ReasonableAI team; specific classification accuracy scores not publicly disclosed in the issue.

原始记录：Shopify ReasonableAI benchmarks DeepSeek LLM 67B Chat for query classification in customer support

the-crypt-keeper (Can AI Code project) 公开的真实任务执行案例，来源为 公开代码库，复核于 2026-06-27T00:35:00Z。 Model Atlas 将它标记为 A 类证据，因为它同时具备具体使用者、具体任务、公开原始证据和可访问产物。

任务：这是一个围绕真实任务执行的真实任务，公开材料可以回溯到具体使用者和具体产物。 原始资料写作：The Can AI Code project (600+ stars), a self-evaluating interview framework for AI coders, evaluated deepseek-ai/deepseek-llm-67b-base for code generation capabilities across multiple programming languages and difficult…

公开产物：公开材料提供公开代码、README 或项目配置，可用于核验任务结果、项目形态和模型绑定关系。 原始资料写作：The evaluation was completed (issue #119 closed), producing code generation benchmark results for deepseek-llm-67b-base. The model was evaluated alongside other LLMs including DeepSeek Coder variants, CodeLlama, and Mis…

模型作用：DeepSeek LLM 67B Base 在该案例中承担真实任务执行相关的生成、分析、编排或实现角色。 原始资料写作：DeepSeek LLM 67B Base was the base model under evaluation for its code generation capabilities, tested through the project's automated self-evaluation interview system that scores models on coding tasks.

A 类理由：有具体使用者、具体任务、公开原始证据和可访问产物，可公开核验。

风险边界：当前判断基于公开材料；若产物下线、仓库变更或模型参与比例仅来自作者自述，需要在引用前重新复核。 原始资料写作：The evaluation results are stored in ndjson files in the results directory. The model was the subject of evaluation rather than being deployed in production.

原始记录：Can AI Code: DeepSeek LLM 67B Base Code Generation Evaluation

ThingsIBuild (TheX-23) 公开的研究与报告生成案例，来源为 公开代码库，复核于 2026-06-27T00:35:00Z。 Model Atlas 将它标记为 A 类证据，因为它同时具备具体使用者、具体任务、公开原始证据和可访问产物。

任务：这是一个围绕研究分析和报告生成的真实任务，公开材料可以回溯到具体使用者和具体产物。 原始资料写作：The Multilingual AI Assistant project integrated DeepSeek LLM 67B alongside Mistral, DeepSeek Coder 33B, GPT-o1, and Mixtral 8X7B as one of its core language models for multilingual text processing across 21+ languages,…

公开产物：公开材料提供公开代码、README 或项目配置，可用于核验任务结果、项目形态和模型绑定关系。 原始资料写作：A working multilingual AI assistant application supporting 21+ languages with multiple LLM backend options, including DeepSeek LLM 67B for general-purpose multilingual text understanding and generation. The project incl…

模型作用：DeepSeek LLM 67B 在该案例中承担研究分析和报告生成相关的生成、分析、编排或实现角色。 原始资料写作：DeepSeek LLM 67B served as one of several LLM backends for the assistant's multilingual text processing capabilities, leveraging the model's strong Chinese and English bilingual training for cross-language tasks.

A 类理由：有具体使用者、具体任务、公开原始证据和可访问产物，可公开核验。

风险边界：当前判断基于公开材料；若产物下线、仓库变更或模型参与比例仅来自作者自述，需要在引用前重新复核。 原始资料写作：Small open-source project (1 star, 2 forks). The model was added as an option but the project's overall adoption is minimal.

原始记录：Multilingual AI Assistant with DeepSeek LLM 67B for Cross-Language Support

Juexiao Zhou, Bin Zhang, Xiuying Chen et al. (King Abdullah University of Science and Technology / Southern University of Science and Technology) 公开的研究与报告生成案例，来源为 公开代码库，复核于 2026-06-26T18:17:12.971643+00:00。 Model Atlas 将它标记为 A 类证据，因为它同时具备具体使用者、具体任务、公开原始证据和可访问产物。

任务：这是一个围绕研究分析和报告生成的真实任务，公开材料可以回溯到具体使用者和具体产物。 原始资料写作：AutoBA is an autonomous AI agent for conventional multi-omic bioinformatics analysis (WGS, RNA-seq, scRNA-seq, ChIP-seq, spatial transcriptomics). DeepSeek LLM 67B Chat is one of the explicitly supported LLM backends (c…

公开产物：公开材料提供公开代码、README 或项目配置，可用于核验任务结果、项目形态和模型绑定关系。 原始资料写作：The agent generates complete, step-by-step bioinformatics analysis plans and executes them locally. Validated by expert bioinformaticians across whole genome sequencing, RNA-seq, single-cell RNA-seq, ChIP-seq, and spati…

模型作用：DeepSeek LLM 67B (V1) 在该案例中承担研究分析和报告生成相关的生成、分析、编排或实现角色。 原始资料写作：DeepSeek LLM 67B Chat serves as the reasoning backbone for the AutoBA agent, enabling it to understand bioinformatics data variations, autonomously design analysis pipelines, and generate executable step-by-step plans. …

A 类理由：有具体使用者、具体任务、公开原始证据和可访问产物，可公开核验。

风险边界：当前判断基于公开材料；若产物下线、仓库变更或模型参与比例仅来自作者自述，需要在引用前重新复核。 原始资料写作：AutoBA supports multiple LLM backends (GPT-4, deepseek-coder, etc.); deepseek-llm-67b-chat is one of several supported options rather than the sole model. No published ablation comparing deepseek-llm-67b-chat against ot…

原始记录：AutoBA: Automated Multi-Omic Bioinformatics Analysis Agent Powered by DeepSeek LLM 67B Chat