PaddleOCR-VL-1.5 vs Ministral-3-3B-Base-2512
Benchmark Performance
Available Benchmarks
Technical Differences
Side-by-Side Facts
| Field | PaddleOCR-VL-1.5 | Ministral-3-3B-Base-2512 |
|---|---|---|
| Developer | Baidu | Mistral AI |
| Family | Paddleocr VL 1 5 | Ministral 3 3b Base 2512 |
| Model | PaddleOCR-VL-1.5 | Ministral-3-3B-Base-2512 |
| Version | PaddleOCR-VL-1.5 | Ministral-3-3B-Base-2512 |
| Lifecycle | active | active |
| Released | 2026-01-29 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 131,072 | 262,144 |
| Total parameters | 958,588,736 | 4,251,743,232 |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | apache-2.0 |
| Open weights | Yes | Yes |
| API available | Unknown | Unknown |
| Self-hostable | Yes | Yes |
| Provider access | Unknown | Unknown |
| Capabilities | chat, generation | generation |
13 comparable fields · 7 material differences · Pair passes the primary-source comparison gate
PaddleOCR-VL-1.5 Capabilities
Ministral-3-3B-Base-2512 Capabilities
Internal Comparison Graph
Related Comparisons
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|---|---|---|---|
Ministral-3-3B-Base-2512Mistral AI | vs | Ministral-3-3B-Reasoning-2512Mistral AI | family variantsimage, text |
Ministral-3-3B-Base-2512Mistral AI | vs | Ministral-3-3B-Instruct-2512Mistral AI | family variantsimage, text |
Ministral-3-3B-Base-2512Mistral AI | vs | Ministral-3-8B-Base-2512Mistral AI | family variantsimage, text |
PaddleOCR-VL-1.5Baidu | vs |  GLM-OCRZ.ai | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs |  Phi-4-multimodal-instructMicrosoft | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs | Ministral-3-3B-Instruct-2512Mistral AI | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs | Ministral-3-8B-Instruct-2512Mistral AI | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs |  Molmo2-8BAi2 | cross-developer peersimage, text |
| vs | Ministral-3-3B-Base-2512Mistral AI | cross-developer peersimage, text | |
Phi-4-multimodal-instructMicrosoft | vs | Ministral-3-3B-Base-2512Mistral AI | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs | Ministral-3-14B-Base-2512Mistral AI | cross-developer peersimage, text |
| vs | Ministral-3-3B-Base-2512Mistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
PaddleOCR-VL-1.5 vs Ministral-3-3B-Base-2512 FAQs
Is PaddleOCR-VL-1.5 or Ministral-3-3B-Base-2512 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both PaddleOCR-VL-1.5 and Ministral-3-3B-Base-2512, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, PaddleOCR-VL-1.5 or Ministral-3-3B-Base-2512?+
Neither model has a directly sourced input price in this comparison. Neither model has a directly sourced output price in this comparison.
Which has a larger context window, PaddleOCR-VL-1.5 or Ministral-3-3B-Base-2512?+
Ministral-3-3B-Base-2512 has the larger sourced context window. PaddleOCR-VL-1.5 supports 131,072 and Ministral-3-3B-Base-2512 supports 262,144.
Which performs better in benchmarks, PaddleOCR-VL-1.5 or Ministral-3-3B-Base-2512?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can PaddleOCR-VL-1.5 or Ministral-3-3B-Base-2512 be self-hosted?+
Both models have the same recorded self-hosting status: supported. PaddleOCR-VL-1.5 is open weight; Ministral-3-3B-Base-2512 is open weight.
Can PaddleOCR-VL-1.5 and Ministral-3-3B-Base-2512 understand images?+
PaddleOCR-VL-1.5 is documented with image input; Ministral-3-3B-Base-2512 is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, PaddleOCR-VL-1.5 or Ministral-3-3B-Base-2512?+
Neither has a larger sourced maximum output. PaddleOCR-VL-1.5 is — and Ministral-3-3B-Base-2512 is —.
Do PaddleOCR-VL-1.5 and Ministral-3-3B-Base-2512 support reasoning and tool use?+
PaddleOCR-VL-1.5: image input. Ministral-3-3B-Base-2512: image input. Feature support does not establish relative quality.
Which is available from more inference providers, PaddleOCR-VL-1.5 or Ministral-3-3B-Base-2512?+
PaddleOCR-VL-1.5 has 0 sourced provider routes; Ministral-3-3B-Base-2512 has 0, a tie.
Which offers better value, PaddleOCR-VL-1.5 or Ministral-3-3B-Base-2512?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.