IQuestLab/IQuest-Q1
text-generation model by IQuestLab
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Model card & documentation
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IQuest-Q1 Developed by IQuest Introduction · Performance · Quick Start · Deployment · Limitations · Contact Us IQuest-Q1 is a Mixture-of-Experts (MoE) model developed by IQuest for agentic coding, reasoning, and multi-step tool use. It comprises approximately 320B total parameters, with an estimated 15B parameters activated per token. Training pipeline of IQuest-Q1. IQuest-Q1 Post-Training Pipeline. IQuest-Q1 performance across benchmarks. DeepSeek-V4-Flash/Pro refer to the official 0731/0813 releases, respectively. Humanity's Last Exam is reported without tools. IQuest-CLIBench is our in-house benchmark for CLI user experience. For reproducibility, we recommend using a temperature of 1.0, top-p of 0.95, and top-k of 20, with Claude Code 2.1.140 or Codex 0.142 as the respective harness. For each model, we report the publicly reported score; otherwise, we evaluate the model using the corresponding benchmark setup: (1) Harness: For agentic coding tasks, we use mini-SWE-agent for DeepSWE v1.1, and Claude Code for other tasks. For Agents' Last…
Read the full model card ↗ · Preview checked 2026-11-14T21:29:12.431Z
Inside the original model card — Document outline
- Introduction
- Model Specifications
- Performance
- Benchmark Notes
- Quick Start
- Deployment
- SGLang
- vLLM
- Tool Use and Agent Integration
- Claude Code
- Codex CLI
- Limitations
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Model overview
IQuestLab/IQuest-Q1 is a text-generation model repository published by IQuestLab on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-generation
- Library
- transformers
- Recent downloads (30 days)
- 1,047
- Cumulative likes
- 136
- Hugging Face trending score
- 51
- Reported safetensors parameters
- 320,318,615,552
- Architecture
- IQuestQ1ForCausalLM
- License
- other
- Access
- Not gated by Hugging Face
- Created
- 2026-09-28T06:37:48.000Z
- Last modified
- 2026-09-29T09:37:47.000Z
Compatibility and lineage
Reported languages: en, zh
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-06T06:38:55.388Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.