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Alibaba / Qwen Intermediate

Qwen1.5-110B-Chat

Qwen1.5-110B-Chat is Qwen's April 2024 110B chat checkpoint with 32K context, multilingual support and substantial multi-GPU deployment requirements.

Language Models (LLMs)Text Open Source
In plain English

What is this model and why does it matter?

Qwen1.5-110B-Chat is the largest Qwen1.5 chat checkpoint, released in April 2024 with 32K context and very high self-hosting requirements.

Historical large-model researchCompatibility testingLarge self-hosted chatBenchmarking
Model overview

Qwen1.5-110B-Chat: features, use cases and important details

Qwen1.5-110B-Chat is the largest dense chat checkpoint released in the Qwen1.5 series. Qwen announced the 110B model on April 25, 2024 and described it as its first model in the series above 100 billion parameters.

Capabilities and context

The model follows the same Qwen1.5 architecture family and supports a 32K context window. Qwen evaluated the generation across multilingual, chat and reasoning tasks and positioned the 110B release as a performance step up from Qwen1.5-72B-Chat.

Deployment reality

The exact model ID is Qwen/Qwen1.5-110B-Chat. Because of its scale, practical self-hosting requires substantial accelerator memory and commonly a distributed inference setup. The model is distributed under the Tongyi Qianwen License.

Should you use it now?

For historical benchmarking or an existing deployment that depends on this exact checkpoint, it remains a useful reference. For new projects, the Qwen1.5 generation is old and newer Qwen releases should be evaluated first. A newer architecture can often provide better capability, context and serving efficiency without the operational cost of a 110B legacy checkpoint.

Get started

How to use this model

  1. Download the exact 110B chat checkpoint.
  2. Plan a multi-GPU or distributed inference environment.
  3. Use the official Qwen chat template.
  4. Measure throughput, memory and output quality on your workload.
  5. Compare against newer Qwen models before choosing it for a new deployment.
Copy and try

Example prompts

  • Analyze these competing architecture proposals in depth.
  • Create a multilingual executive summary from this document.
  • Review this codebase migration plan and identify missing risks.
Capabilities

What it can do

  • Large-scale instruction following
  • Multilingual text
  • 32K context
  • Reasoning
  • Long-form generation
Best for

Practical use cases

  • Research
  • Historical benchmarking
  • Existing compatibility deployments
  • Large self-hosted assistants
Pricing

What does it cost?

Downloadable Qwen1.5 checkpoint; no current provider per-token price is assigned to this specific open-weight checkpoint.

Simple summaryWeights are downloadable under the Tongyi Qianwen License, but serving a 110B model typically requires large multi-GPU infrastructure.

What stands out

  • Largest Qwen1.5 dense chat checkpoint
  • 32K context
  • Strong historical benchmark performance

Things to consider

  • Extremely demanding hardware requirements
  • Older generation
  • Custom license
Limitations

Important restrictions and trade-offs

  • Very expensive to self-host
  • Newer Qwen generations are more relevant for new projects
  • Can still hallucinate or make reasoning mistakes
SimplifyAITools verdict

Our editorial take

A notable historical Qwen release, but its 110B scale and age make it a niche choice today outside research and compatibility work.

References

Primary sources

  1. Open source 1 ↗
  2. Open source 2 ↗
  3. Open source 3 ↗
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