LLM Reference

WizardLM 70B

Released
2023-04-28
Last refreshed
2026-05-19
Status
Researched 16d ago

WizardLM 70B has model metadata, but missing tracked provider pricing keeps it from being a default production pick.

Use it for

  • Teams evaluating general LLM work
  • Workloads that can use a 4k context window

Do not use it for

  • Cost-sensitive launches that need sourced token pricing
  • Vision or document-understanding workloads
  • Strict JSON or tool-calling flows
Specifications
Family
WizardLM
Released
2023-04-28
Context
4k
Parameters
70B
Architecture
Decoder Only
Specialization
general
Training
finetuned
Created by

Advancing Language Model Capabilities

N/A
Founded N/A
Website
Pricing

No tracked provider token pricing is available yet.

About

WizardLM 70B is an advanced large language model utilizing the transformer architecture with an impressive 70 billion parameters. It is adept at following complex instructions and managing multi-turn conversations with detailed and polite responses. Known for its capabilities in text and code generation, as well as solving mathematical problems, the model often surpasses some proprietary LLMs on specific benchmarks. Offered in various quantized formats like GGML and GGUF, WizardLM 70B is optimized for diverse hardware and performance requirements. Although the training data isn't publicly accessible, its open-source nature, coupled with availability on platforms such as Hugging Face, makes it a valuable resource for research and development. Specialized versions like WizardCoder and WizardMath focus on coding and mathematical tasks, respectively.

WizardLM 70B is a model in the WizardLM family. The structured metadata tracks a 4k-token context window. No headline benchmark score is tracked for WizardLM 70B yet.

Top use-case fit

No primary decision-task fit is mapped for this model yet.

Provider price ladder

No tracked provider token pricing is available for this model yet.

Capabilities

No model capability flags are currently sourced.

Benchmark peer barsfor Coding

No task-mapped benchmark peers are available for this model yet.

Migration checks

No linked migration route is available for this model yet.

Rankings & picks(4)