Model reference · open weights
Qianfan-VL is an open-weight language model from baidu. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Maker | baidu |
|---|---|
| Type | Language models |
| Task | Vision + text |
| Parameters (lead) | 3.7B |
| Runs with | transformers |
| Released | 2025-09-16 |
| Popularity | 199 downloads / month |
| Licence | Commercial licence needed |
About
Domain Capability Enhancement through Continuous Pre-training | 3B to 70B Parameter Scale | Document Understanding & OCR Enhancement | Chain-of-Thought Reasoning Support
Qianfan-VL is a series of general-purpose multimodal large language models enhanced for enterprise-level multimodal applications. The models offer deep optimization for high-frequency scenarios in industrial deployment while maintaining strong general capabilities.
| Model | Parameters | Context Length | CoT Support | Best For |
|---|---|---|---|---|
| Qianfan-VL-3B | 3B | 32k | ❌ | Edge deployment, real-time OCR |
| Qianfan-VL-8B | 8B | 32k | ✅ | Server-side general scenarios, fine-tuning |
| Qianfan-VL-70B | 70B | 32k | ✅ | Complex reasoning, data synthesis |
| Benchmark | Qianfan-VL-3B | Qianfan-VL-8B | Qianfan-VL-70B | InternVL-3-8B | InternVL-3-78B | Qwen2.5-VL-7B | Qwen2.5-VL-72B |
|---|---|---|---|---|---|---|---|
| A-Bench_VAL | 75.65 | 75.72 | 78.1 | 75.86 | 75.86 | 76.49 | 79.22 |
| CCBench | 66.86 | 70.39 | 80.98 | 77.84 | 70.78 | 57.65 | 73.73 |
| SEEDBench_IMG | 76.55 | 78.02 | 79.13 | 77.0 | 77.52 | 76.98 | 78.34 |
| SEEDBench2_Plus | 67.59 | 70.97 | 73.17 | 69.52 | 68.47 | 70.93 | 73.25 |
| MMVet | 48.17 | 53.21 | 67.34 | 80.28 | 78.9 | 70.64 | 75.69 |
| MMMU_VAL | 46.44 | 47.11 | 58.33 | 56.11 | 60.78 | 51.0 | 65.78 |
| ScienceQA_TEST | 95.19 | 97.62 | 98.76 | 97.97 | 97.17 | 85.47 | 92.51 |
| ScienceQA_VAL | 93.85 | 97.62 | 98.81 | 97.81 | 95.14 | 83.59 | 91.32 |
| MMT-Bench_VAL | 62.23 | 63.22 | 71.06 | 65.17 | 63.67 | 61.4 | 69.49 |
| MTVQA_TEST | 26.5 | 30.14 | 32.18 | 30.3 | 27.62 | 29.08 | 31.48 |
| BLINK | 49.97 | 56.81 | 59.44 | 55.87 | 51.87 | 54.55 | 63.02 |
| MMStar | 57.93 | 64.07 | 69.47 | 68.4 | 66.07 | 61.53 | 66.0 |
| RealWorldQA | 65.75 | 70.59 | 71.63 | 71.11 | 74.25 | 69.28 | 73.86 |
| Q-Bench1_VAL | 73.51 | 75.25 | 77.46 | 75.99 | 77.99 | 78.1 | 79.93 |
| POPE | 85.08 | 86.06 | 88.97 | 90.59 | 88.87 | 85.97 | 83.35 |
| RefCOCO (Avg) | 85.94 | 89.37 | 91.01 | 89.65 | 91.40 | 86.56 | 90.25 |
| Benchmark | Qianfan-VL-3B | Qianfan-VL-8B | Qianfan-VL-70B | InternVL-3-8B | InternVL-3-78B | Qwen2.5-VL-3B | Qwen2.5-VL-7B | Qwen2.5-VL-72B |
|---|---|---|---|---|---|---|---|---|
| OCRBench | 831 | 854 | 873 | 881 | 847 | 810 | 883 | 874 |
| AI2D_TEST | 81.38 | 85.07 | 87.23 | 85.07 | 83.55 | 77.07 | 80.472 | 83.84 |
| OCRVQA_TEST | 66.15 | 68.98 | 74.06 | 39.03 | 35.58 | 69.24 | 71.02 | 66.8 |
| TextVQA_VAL | 80.11 | 82.13 | 84.48 | 82.15 | 83.52 | 79.09 | 84.962 | 83.26 |
| DocVQA_VAL | 90.85 | 93.54 | 94.75 | 92.04 | 83.82 | 92.71 | **9 |
From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Once AxForge deploys qianfan-vl for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (qianfan-vl below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/chat/completions \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"qianfan-vl","messages":[{"role":"user","content":"Hello"}]}'
Create an account — your API key is available in the console. 5M tokens/month currently included with every new account at launch.