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mindlab-research
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Model Details
Model Provider
mindlab-research
Model Tree
zai-org/GLM-5.2
Input Modalities
Output Modalities
Supported Functionality
| Field | Value |
|---|---|
| Model name | Macaron-V1-Coding-Venti |
| Organization | MindLab Research |
| Release family | Macaron-V1 |
| Base model | GLM-5.2 |
| Source specialist | Macaron-V1-Venti L2 Coding LoRA |
| Checkpoint type | BF16 merged checkpoint |
| Runtime architecture | GLM-5.2 weights with coding LoRA update merged into the base |
| Primary domains | Coding, terminal workflows, software-engineering agents |
| Context length | 1M |
| License | MIT |
The coding-specialist release reports the coding and terminal slices from the Macaron-V1 evaluation suite.
| Benchmark | Macaron V1 | GLM 5.2 | GPT 5.5 | Claude Opus 4.8 | Gemini 3.1 Pro | Qwen 3.7 Max | Minimax M3 |
|---|---|---|---|---|---|---|---|
| SWE Verified | 85.6 | 80.4 | 82.9 | 88.6 | 80.6 | 80.4 | 80.5 |
| TerminalBench 2.1 | 87.6 | 82.7 | 83.4 | 78.9 | 70.7 | 73.5 | 66.0 |
| DeepSWE | 58.4 | 54.9 | 70.0 | 58.0 | 10.0 | 18.0 | 20.0 |
| SWE Atlas QnA | 49.5 | 48.9 | 45.4 | 57.3 | 13.5 | 22.6 | 37.9 |
Higher is better for all scores shown in the table.
The coding benchmark table is mirrored in evaluation/coding_benchmark_summary.yaml for reproducibility and downstream parsing.
The full benchmark methodology will be released with the technical report.
This repository contains a merged checkpoint. Load it as a standard GLM-5.2-compatible causal language model; no PEFT adapter attachment or MoL router is required.
python
import torchfrom transformers import AutoModelForCausalLM, AutoTokenizerrepo_id = "mindlab-research/Macaron-V1-Coding-Venti"tokenizer = AutoTokenizer.from_pretrained(repo_id,trust_remote_code=True,)model = AutoModelForCausalLM.from_pretrained(repo_id,torch_dtype=torch.bfloat16,device_map="auto",trust_remote_code=True,)model.eval()
For production serving, use the same GLM-5.2-compatible serving stack you would use for a merged BF16 checkpoint. The full Macaron routed system, including Chat, Agent, Coding, and GenUI specialists, remains available through Macaron-V1-Venti and the Mixture of LoRA (MoL) serving harness.
Macaron Artifacts is the companion local WebUI and plugin bundle for viewing Macaron sessions and generated artifacts. It supports Claude Code, Codex, and Kimi Code, and can run against Macaron or another Anthropic-compatible endpoint.
Install it as a plugin in the agent runtime you use:
text
# Claude Code/plugin marketplace add https://github.com/MindLab-Research/macaron-artifacts/plugin install macaron@macaron
bash
# Codexcodex plugin marketplace add https://github.com/MindLab-Research/macaron-artifactscodex plugin add macaron@macaron
text
# Kimi Code/plugins install https://github.com/MindLab-Research/macaron-artifacts/reload
This repository is released under the MIT License. Users should also respect any requirements inherited from the GLM-5.2 base model and from dependencies used by their serving stack.
bibtex
@misc{mindlab2026macaronv1,author = {{Mind Lab}},title = {Introducing Macaron-V1},year = {2026},howpublished = {Mind Lab: A Lab for Experiential Intelligence},note = {https://macaron.im/mindlab/research/introducing-macaron-v1}}