TU
Tsinghua University
Language model · China ·May 2021

CogView

Language Open (Restricted)
4B
Parameters

About CogView

CogView is an AI model developed by Tsinghua University, in the language category, released in 2021, made available as an open-weights model with 4B params.

On this page you'll find CogView's full specifications. Review provider pricing and benchmark scores below, or compare CogView head-to-head with other language models.

→ More models by Tsinghua University → All language models → AI benchmarks leaderboard

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Run CogView locally — what to buy

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Sized to what CogView actually needs (~8k context at Q4), not to the biggest GPU: Good = cheapest that runs it, Better = best value, Best = most headroom. Speed is a hardware estimate; anything past ~120 tok/s is shown as instant.

Best
Intel Arc B580 12GB
Consumer GPU · ~$249
~120 tok/s
Q4 · fits full context · up to 8k ctx
Runs with: ExLlamaV2, KoboldCpp, LM Studio
See full estimate →

Software support

·ExLlamaV2 ·KoboldCpp ·LM Studio ·MLX ·Ollama ·SGLang ·TensorRT-LLM ·llama.cpp ·vLLM ?KTransformers ?text-generation-webui

✓ measured · · compatible · — not supported. Informational only — speed is hardware-based.

Consumer GPU
72–120+ tok/s
32 options →
Apple
43.5–120+ tok/s
18 options →
Datacenter GPU
120+ tok/s
13 options →

Community

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Frequently asked questions

What is CogView? ▶

CogView is an AI model developed by Tsinghua University, in the language category, released in 2021. It is tracked on GenAIList with its specifications, benchmark scores and provider pricing.

Who created CogView? ▶

CogView was developed by Tsinghua University and released in 2021.

Is CogView open source or proprietary? ▶

CogView ships as an open-weights model: you can download and self-host the weights, though the licence may place some restrictions on use.

How much does CogView cost? ▶

Pricing for CogView depends on the provider. See the providers table on this page for the latest API rates.

How does CogView perform on benchmarks? ▶

Benchmark scores for CogView are listed on this page as they are published. You can compare it head-to-head with other models on the GenAIList compare tool.

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