Benchmarks1y ago
qwen2.5 - GAIA
GAIA score 4.7 from rft-2
View sourcekorea-deep-learning
Qwen2.5-VL-7B-TableRecog is a open-weight korea-deep-learning vision model.
Running this yourself: consumer gpu should be enough.
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Quality Score
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Arena ELO
7B
Parameters
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Context
This measures the amount of verifiable public evidence we have, not how capable the model is. A missing field means it has not been verified yet, not that its value is zero.
13 of 22 public signals
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28
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Nov 2025
Released
2/5 signals
2/4 signals
4/5 signals
3/4 signals
2/4 signals
Gaps we are still tracking
Benchmarks
3
Open Source
1
Recent launch, pricing, benchmark, and API signals linked to this model or its provider.
GAIA score 4.7 from rft-2
View sourceGAIA score 4.7 from rft-2
View sourceGAIA score 4.7 from rft-2
Qwen2.5-VL-7B-TableRecog is now available through local Ollama runtime. 32K context window listed. Qwen2.5 models are pretrained on Alibaba's latest large-scale dataset, encompassing up to 18 trillion tokens. The model supports up to 128K tokens and has multilingual support.
View sourceQwen2.5-VL-7B-TableRecog is now available through local Ollama runtime. 32K context window listed. Qwen2.5 models are pretrained on Alibaba's latest large-scale dataset, encompassing up to 18 trillion tokens. The model supports up to 128K tokens and has multilingual support.