MM-Vet
Harbor: pendingMM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities
- Samples
- N/A
- Released
- 2023
- Scores
- 43
MM-Vet v2
MM-Vet v2: A Challenging Benchmark to Evaluate Large Multimodal Models for Integrated Capabilities
How to run
ltb · mm-vet-v2
$ npm i -g lettokenburn-cli$ ltb bench info mm-vet-v2
External harness. No Harbor adapter has been generated for this benchmark yet. `ltb bench info` prints the known links.
Runs happen on your machine with your own subscription; only the score summary is pushed. CLI docs
Scores
13 sourced entries| Harness | Source | Confidence | Link | |||
|---|---|---|---|---|---|---|
| Gemini 2.0 Flash Experimental | 77.1 | N/A | Independent | medium | N/A | paperswithcode.com |
| InternVL2-Llama3-76B | 68.4 | N/A | Independent | medium | N/A | paperswithcode.com |
| Gemini 1.5 Pro | 66.9 | N/A | Independent | medium | Mar 8, 2024 | arxiv.org |
| GPT-4o-mini | 66.8 | N/A | Independent | medium | Mar 15, 2023 | arxiv.org |
| InternVL2-40B | 63.8 | N/A | Independent | medium | N/A | paperswithcode.com |
| Gemini Pro Vision | 57.2 | N/A | Independent | medium | Dec 19, 2023 | arxiv.org |
| Qwen-VL-Max | 55.8 | N/A | Independent | medium | Aug 24, 2023 | arxiv.org |
| InternVL-Chat-V1-5 | 51.5 | N/A | Independent | medium | Apr 25, 2024 | arxiv.org |
| LLaVA-NeXT-34B | 50.9 | N/A | Independent | medium | N/A | paperswithcode.com |
| InternVL-Chat-V1-2 | 45.5 | N/A | Independent | medium | N/A | paperswithcode.com |
| CogVLM-Chat | 45.1 | N/A | Independent | medium | Nov 6, 2023 | arxiv.org |
| LLaVA-v1.5-13B | 33.2 | N/A | Independent | medium | Oct 5, 2023 | arxiv.org |
| LLaVA-v1.5-7B | 28.3 | N/A | Independent | medium | Oct 5, 2023 | arxiv.org |
Every number links to where it was published. Low-confidence rows are muted and need per-cell verification.
Reproduced by the community
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MM-Vet v2: A Challenging Benchmark to Evaluate Large Multimodal Models for Integrated Capabilities