WizardLM Team
17 models across 3 families · Latest: WizardCoder 33B (2024-01)
Advancing Language Model Capabilities
WizardLM Team's portfolio covers 17 active models across 3 current families, spanning classification and json / tool use. Open a model detail page to compare provider routes and sourced benchmarks.
Covers 2 workload areas across 17 active tracked models; last verified 2026-06-29.
Use it for
- Teams evaluating classification and json / tool use across this lab's releases
- Comparing model families before committing to a flagship
- Migration and pricing follow-ups across 17 tracked models
Do not use it for
- Choosing a hosting provider without opening a model page for price ladders
Active models
17
Current models from this lab, excluding deprecated ones
Active families
3
Current model families from this lab
Open catalog
17 open
7 open source / 10 open weights
Lowest output price
$0.300 /1M
Cheapest tracked output across active models, per 1M tokens
Latest dated release
2024-01-29
WizardCoder 33B
Freshness
2026-06-29
Researched 19d ago
Information
Release cadence
Showing 5 recent dated releases (full timeline below). Latest: WizardCoder 33B (2024-01-29).
Where this lab wins
- Classification: 2 tracked models with MMLU-class moderation/safety coverage.
- JSON/tool-use: 2 tracked models with BFCL / Nexus strict-JSON routing coverage.
Flagship quality / price signal
Flagship: WizardLM 70B (best sourced coding quality-per-dollar in this portfolio).
Quality-per-dollar unavailable for this flagship — benchmark coverage or output token pricing is still missing.
WizardLM Team is an AI research organization founded in N/A. Advancing Language Model Capabilities. WizardLM Team ships 3 model families totaling 17 models, with the most recent release WizardCoder 33B in 2024-01. Notable families include WizardCoder, WizardMath, and WizardLM. Use it as a stable reference for lab background, release coverage, and follow-up model pages as they are added. Researchers and evaluators can. View official API endpoints, benchmark performance, and coding/agent fit for every WizardLM Team model.
About
The WizardLM Team is dedicated to advancing large language models (LLMs) with a focus on enhancing their ability to follow complex instructions. Their core innovation lies in the ""AI Align AI"" (AAA) framework, which leverages multiple state-of-the-art LLMs to collaboratively train and refine one another. This approach, combined with techniques like Evol-Instruct and Reinforcement Learning for Instruction and Process Supervision (RLEIF), enables the creation of high-quality training data and the fine-tuning of models for superior performance in complex chat, multilingual capabilities, reasoning, and agent-based interactions. The team's WizardLM models undergo rigorous testing, demonstrating high performance across standardized benchmarks and real-world applications. Their fully AI-powered synthetic training system creates and curates training data, ensuring high quality and relevance. Weighted sampling ensures balanced representation across diverse content and use cases, preventing bias while maintaining comprehensive coverage. Progressive learning, where the model is trained incrementally with increasing complexity, further enhances performance and reduces training time. The models have shown significant improvements over existing open-source LLMs in areas like reasoning, creative generation, and technical analysis. Beyond the core models, the WizardLM Team has extended their innovations into specialized areas like code generation (WizardCoder) and mathematical problem-solving (WizardMath). These models consistently outperform other open-source LLMs on benchmark tests in these domains and even rival some closed-source models. The team continues to publish research and release updated model versions, showcasing a commitment to ongoing advancement in the field of LLM technology and pushing the boundaries of what's possible with AI-powered instruction following and synthetic data generation.
Featured models
| Model | Released | Context | Input price ($/1M) | Output price ($/1M) | License | Openness |
|---|---|---|---|---|---|---|
| WizardCoder 33B | 2024-01-29 | 16k | $0.20 | $1.00 | Apache 2.0 | Open source |
| WizardCoder Python 34B | 2024-01-29 | 100k | $0.8 | $0.8 | Apache 2.0 | Open source |
| Wizard Coder 15B | 2024-01-29 | 8k | - | - | Apache 2.0 | Open source |
Model families
Recent releases
- WizardCoder 33B- 2024-01-29
- WizardCoder Python 34B- 2024-01-29
- Wizard Coder 15B- 2024-01-29
- WizardCoder Python 13B- 2024-01-29
- WizardCoder Python 7B- 2024-01-29
FAQ
Who founded WizardLM Team and when?
WizardLM Team was founded in N/A and is associated with N/A.
What models has WizardLM Team released?
WizardLM Team ships 17 models across 3 families: WizardCoder, WizardMath, and WizardLM.
Is WizardLM Team's technology open source?
All tracked WizardLM Team models are open-weight or open-source.
Where is WizardLM Team headquartered?
WizardLM Team is headquartered in N/A.
What is WizardLM Team known for?
Advancing Language Model Capabilities. Its most prominent tracked family is WizardCoder.
How can I access WizardLM Team's models?
WizardLM Team's models are available via Baseten API, Microsoft Foundry, Replicate API, and Together AI.
Explore related pages
Last reviewed: 2026-06-29. Data sourced from public lab announcements and provider documentation.