IQuestLab/IQuest-Q1 · Hugging Face

Source: https://huggingface.co/IQuestLab/IQuest-Q1 Developed byIQuest

Introduction·Performance·Quick Start·Deployment·Limitations·Contact Us

https://huggingface.co/IQuestLab/IQuest-Q1#introductionIntroduction

IQuest-Q1is a Mixture-of-Experts (MoE) model developed byIQuestfor agentic coding, reasoning, and multi-step tool use. It comprises approximately320B total parameters, with an estimated15B parameters activated per token.

Training pipeline of IQuest-Q1.

IQuest-Q1 Post-Training Pipeline.

https://huggingface.co/IQuestLab/IQuest-Q1#model-specificationsModel Specifications

PropertyIQuest-Q1Total Parameters320BActivated Parameters15BTransformer layers88Hidden dimension3,072Attention Heads (Q/KV)48/8Head Dimension128Hybrid Attention Pattern3 SWA + 1 FASliding Window Size4,096Partial RoPE Dimensions32Experts (Total/Activated)256/8MTP Layers2 Independent (Training) / 1 Recursive x8 (Inference)MTP Sliding Window Size512 (Inference)Context length524,288

https://huggingface.co/IQuestLab/IQuest-Q1#performancePerformance

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.

https://huggingface.co/IQuestLab/IQuest-Q1#benchmark-notesBenchmark Notes

For reproducibility, we recommend using a temperature of 1.0, top-p of 0.95, and top-k of 20, with Claude Code2\.1\.140or Codex0\.142as 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 Exam, we evaluate our model using Claude Code2\.1\.258. Because our models currently do not have multimodal capability, we replace multimodal content inputs in the agent conversation with placeholders during tokenization. (2) Runtime: We set six-hour limits for CyberGym, eight hours for Terminal-Bench 2.1.

https://huggingface.co/IQuestLab/IQuest-Q1#quick-startQuick Start

Start a server as described inDeployment, install the client withpip install openai, and then call the OpenAI-compatible API:

from openai import OpenAI

client = OpenAI(base_url="http://127.0.0.1:8000/v1", api_key="sk-iquest")
response = client.chat.completions.create(
    model="IQuest-Q1",
    messages=[
        {"role": "user", "content": "Hello! Can you briefly introduce yourself?"},
    ],
    temperature=1.0,
    top_p=0.95,
)
print(response.choices[0].message.content)

https://huggingface.co/IQuestLab/IQuest-Q1#deploymentDeployment

For production deployment, we recommend usingSGLangorvLLM.

https://huggingface.co/IQuestLab/IQuest-Q1#sglangSGLang

Use our prebuilt imageiquestlabworkspace/sglang-iquest-q1:cu130:

docker pull iquestlabworkspace/sglang-iquest-q1:cu130

# without MTP
MODEL_ROOT="$(hf download IQuestLab/IQuest-Q1 --quiet)" && \
python -u -m sglang.launch_server \
  --model-path "$MODEL_ROOT" \
  --served-model-name IQuest-Q1 \
  --tp-size 8 \
  --dtype bfloat16 \
  --attention-backend fa3 \
  --mem-fraction-static 0.85 \
  --disable-prefill-cuda-graph \
  --enable-metrics \
  --tool-call-parser iquest_q1 \
  --reasoning-parser iquest_q1 \
  --enable-torch-compile \
  --load-format fastsafetensors \
  --speculative-use-rejection-sampling

# with recursive MTP
MODEL_ROOT="$(hf download IQuestLab/IQuest-Q1 --quiet)" && \
python -u -m sglang.launch_server \
    --model-path "$MODEL_ROOT" \
    --served-model-name IQuest-Q1 \
    --tp-size 8 \
    --dtype bfloat16 \
    --attention-backend fa3 \
    --mem-fraction-static 0.85 \
    --disable-prefill-cuda-graph \
    --enable-metrics \
    --tool-call-parser iquest_q1 \
    --reasoning-parser iquest_q1 \
    --speculative-algorithm EAGLE \
    --speculative-num-steps 5 \
    --speculative-eagle-topk 1 \
    --speculative-num-draft-tokens 6 \
    --speculative-draft-model-path "$MODEL_ROOT/mtp" \
    --enable-torch-compile \
    --load-format fastsafetensors \
    --speculative-use-rejection-sampling \
    --speculative-draft-attention-backend fa3

https://huggingface.co/IQuestLab/IQuest-Q1#vllmvLLM

Use our imageiquestlabworkspace/vllm-iquest-q1:cu130:

docker pull iquestlabworkspace/vllm-iquest-q1:cu130

# without MTP
MODEL_ROOT="$(hf download IQuestLab/IQuest-Q1 --quiet)" && \
vllm serve "$MODEL_ROOT" \
  --served-model-name IQuest-Q1 \
  --tensor-parallel-size 8 \
  --reasoning-parser iquest_q1 \
  --enable-auto-tool-choice \
  --tool-call-parser iquest_q1

# with recursive MTP
MODEL_ROOT="$(hf download IQuestLab/IQuest-Q1 --quiet)" && \
vllm serve "$MODEL_ROOT" \
  --served-model-name IQuest-Q1 \
  --tensor-parallel-size 8 \
  --reasoning-parser iquest_q1 \
  --enable-auto-tool-choice \
  --tool-call-parser iquest_q1 \
  --enable-prefix-caching \
  --speculative-config '{
    "method": "eagle",
    "model": "'"$MODEL_ROOT"'/mtp",
    "num_speculative_tokens": 5,
    "draft_sample_method": "probabilistic",
    "rejection_sample_method": "standard",
    "enforce_eager": false
  }'

https://huggingface.co/IQuestLab/IQuest-Q1#tool-use-and-agent-integrationTool Use and Agent Integration

Use a gateway that supports tool calling viaAnthropic MessagesforClaude CodeandOpenAI ResponsesforCodex.

https://huggingface.co/IQuestLab/IQuest-Q1#claude-codeClaude Code

We recommend version2\.1\.140and the IQuest-Q1[1m] client-side setting does not change 512K context limit.

export ANTHROPIC_MODEL="IQuest-Q1[1m]"
export ANTHROPIC_DEFAULT_SONNET_MODEL="IQuest-Q1[1m]"
export ANTHROPIC_DEFAULT_OPUS_MODEL="IQuest-Q1[1m]"
export ANTHROPIC_DEFAULT_HAIKU_MODEL="IQuest-Q1[1m]"
export CLAUDE_CODE_SUBAGENT_MODEL="IQuest-Q1[1m]"
export CLAUDE_CODE_MAX_OUTPUT_TOKENS="131072"
export CLAUDE_AUTOCOMPACT_PCT_OVERRIDE="80"
export CLAUDE_CODE_AUTO_COMPACT_WINDOW="524288"
export API_TIMEOUT_MS="3000000"
export CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC="1"
export CLAUDE_CODE_DISABLE_EXPERIMENTAL_BETAS="1"
export ANTHROPIC_BASE_URL="http://example-iquest-q1-link"
export ANTHROPIC_AUTH_TOKEN="sk-iquest-q1"
claude --model IQuest-Q1

https://huggingface.co/IQuestLab/IQuest-Q1#codex-cliCodex CLI

We recommend version0\.142\.0.

export OPENAI_API_KEY="sk-iquest-q1"
export MODEL_ID="IQuest-Q1"
# Add /v1 if required by your gateway's Responses endpoint.
export BASE_URL="http://example-iquest-q1-link"

(
  set -eu
  CONFIG_DIR="${HOME}/.codex"
  mkdir -p -- "$CONFIG_DIR"
  CONFIG_DIR="$(cd -- "$CONFIG_DIR" && pwd -P)"
  # Back up existing files before replacing them.
  BACKUP_SUFFIX="$(date +%Y%m%d-%H%M%S)-$$"
  for FILE in config.toml model_catalog.json; do
    if [ -f "$CONFIG_DIR/$FILE" ]; then
      cp -p -- "$CONFIG_DIR/$FILE" "$CONFIG_DIR/$FILE.bak.$BACKUP_SUFFIX"
    fi
  done
  # This configuration disables approval prompts and sandboxing.
  cat > "$CONFIG_DIR/config.toml" <<EOF
model = "$MODEL_ID"
model_provider = "iquest"
approval_policy = "never"
sandbox_mode = "danger-full-access"
web_search = "disabled"
model_reasoning_summary = "detailed"
model_supports_reasoning_summaries = true
model_context_window = 524288
model_auto_compact_token_limit = 419430
model_auto_compact_token_limit_scope = "total"
tool_output_token_limit = 32768
model_catalog_json = "$CONFIG_DIR/model_catalog.json"
[model_providers.iquest]
name = "iquest"
base_url = "${BASE_URL%/}"
wire_api = "responses"
env_key = "OPENAI_API_KEY"
supports_websockets = false
request_max_retries = 20
stream_max_retries = 20
stream_idle_timeout_ms = 600000
[model_providers.iquest.http_headers]
max-output-tokens = "131072"
EOF
  # The gateway must support the reasoning options and max-output-tokens header.
  cat > "$CONFIG_DIR/model_catalog.json" <<EOF
{
  "models": [
    {
      "slug": "$MODEL_ID",
      "display_name": "$MODEL_ID",
      "description": "IQuest-Q1 served through an API gateway.",
      "context_window": 524288,
      "input_modalities": ["text"],
      "base_instructions": "",
      "supported_reasoning_levels": [],
      "supports_reasoning_summaries": true,
      "supports_parallel_tool_calls": false,
      "shell_type": "default",
      "tool_mode": "default",
      "truncation_policy": {
        "mode": "tokens",
        "limit": 10000
      },
      "visibility": "list",
      "supported_in_api": true,
      "priority": 1,
      "support_verbosity": false,
      "experimental_supported_tools": []
    }
  ]
}
EOF
  codex --model "$MODEL_ID"
)

https://huggingface.co/IQuestLab/IQuest-Q1#limitationsLimitations

• **Text-only input.**This checkpoint has no native image, audio, or video input capability.
• **Output reliability.**Generated explanations and code can be incorrect. Review code changes and verify them with task-appropriate tests.
• **Tool integration.**Tool calls use the IQuest-specific format in the chat template. Structured tool execution and reasoning extraction require compatible serving parsers and an agent harness.
• **Challenges in Real-World CLI Tasks.**Real-world CLI tasks often require iterative debugging and verification. IQuest-Q1 may overlook constraints, repeat failed attempts, or leave issues unresolved, necessitating human oversight.
• **Ongoing development.**IQuest-Q1 remains at an early stage, with substantial limitations in its capabilities and reliability. Much work remains, and we still have a long way to go.

https://huggingface.co/IQuestLab/IQuest-Q1#contact-usContact Us

For technical questions, feedback, or collaboration inquiries, please email us at[email protected].

IQuest