PaddleOCR-VL-1.5 vs Gemma 4 12B
Benchmark Performance
Available Benchmarks
Technical Differences
Side-by-Side Facts
| Field | PaddleOCR-VL-1.5 | Gemma 4 12B |
|---|---|---|
| Developer | Baidu | Google DeepMind |
| Family | Paddleocr VL 1 5 | Gemma 4 |
| Model | PaddleOCR-VL-1.5 | Gemma 4 12B |
| Version | PaddleOCR-VL-1.5 | Gemma 4 12B |
| Lifecycle | active | active |
| Released | 2026-01-29 | 2026-05-23 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Image, Video, Audio |
| Output modalities | Text | Text |
| Context window | 131,072 | 262,144 |
| Total parameters | 958,588,736 | 12,000,000,000 |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | apache-2.0 |
| Open weights | Yes | Yes |
| API available | Unknown | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Unknown | Together Ai (Standard) |
| Capabilities | chat, generation | chat, generation, reasoning, structured_outputs, tools |
14 comparable fields · 9 material differences · Pair passes the primary-source comparison gate
PaddleOCR-VL-1.5 Capabilities
Gemma 4 12B Capabilities
Internal Comparison Graph
Related Comparisons
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|---|---|---|---|
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Gemma 4 12BGoogle DeepMind | vs |  Muse Spark 1.2Meta | cross-developer peersaudio, image, text, video |
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Seed 1.8ByteDance Seed | vs | Gemma 4 12BGoogle DeepMind | cross-developer peersimage, text |
Gemma 4 12BGoogle DeepMind | vs |  Ministral-3-14B-Reasoning-2512Mistral AI | cross-developer peersimage, text |
Gemma 4 12BGoogle DeepMind | vs | Ministral-3-14B-Instruct-2512Mistral AI | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs |  GLM-OCRZ.ai | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs | cross-developer peersimage, text | |
PaddleOCR-VL-1.5Baidu | vs | Ministral-3-3B-Instruct-2512Mistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
PaddleOCR-VL-1.5 vs Gemma 4 12B FAQs
Is PaddleOCR-VL-1.5 or Gemma 4 12B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both PaddleOCR-VL-1.5 and Gemma 4 12B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, PaddleOCR-VL-1.5 or Gemma 4 12B?+
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 Gemma 4 12B?+
Gemma 4 12B has the larger sourced context window. PaddleOCR-VL-1.5 supports 131,072 and Gemma 4 12B supports 262,144.
Which performs better in benchmarks, PaddleOCR-VL-1.5 or Gemma 4 12B?+
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 Gemma 4 12B be self-hosted?+
Both models have the same recorded self-hosting status: supported. PaddleOCR-VL-1.5 is open weight; Gemma 4 12B is open weight.
Can PaddleOCR-VL-1.5 and Gemma 4 12B understand images?+
PaddleOCR-VL-1.5 is documented with image input; Gemma 4 12B is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, PaddleOCR-VL-1.5 or Gemma 4 12B?+
Neither has a larger sourced maximum output. PaddleOCR-VL-1.5 is — and Gemma 4 12B is —.
Do PaddleOCR-VL-1.5 and Gemma 4 12B support reasoning and tool use?+
PaddleOCR-VL-1.5: image input. Gemma 4 12B: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, PaddleOCR-VL-1.5 or Gemma 4 12B?+
PaddleOCR-VL-1.5 has 0 sourced provider routes; Gemma 4 12B has 1, so Gemma 4 12B has broader tracked availability.
Which offers better value, PaddleOCR-VL-1.5 or Gemma 4 12B?+
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.