Janus-Pro 1B
DeepSeek's tiny unified multimodal model: one 1.5B-parameter checkpoint that both understands and generates images.
About
Janus-Pro-1B is DeepSeek's entry-level unified multimodal model, notable for doing two jobs with one set of weights: it both understands images and generates them. The trick is decoupled visual encoding, a SigLIP-L encoder for understanding tasks and a LlamaGen vector-quantized tokenizer for generation, routed through a shared autoregressive transformer built on a 1.5B-parameter DeepSeek LLM backbone. That makes it one of the smallest models anywhere that can look at a picture and also draw one.
DeepSeek's reported scores put the 1B model at 0.73 on GenEval and 82.6 on DPG-Bench for generation quality, within reach of DALL-E 3 on the latter despite the size gap, though the 7B sibling is visibly better. It runs in about 4 GB of VRAM, so a mid-range consumer GPU is enough. The code is MIT and the weights carry DeepSeek's model license with commercial use permitted. Expect research-grade output rather than production polish at this scale.
Specs
Context window
Pricing
Free quota
API access
Weights
Released
Benchmarks
- GenEval: 0.73; DPG-Bench: 82.63 (provider figures via third-party guide; DALL-E 3 at 0.67/83.50, Janus-Pro-7B at 0.80/84.19)
- No published understanding-benchmark headlines for the 1B variant in sources checked
Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.
Use cases
Trust score — 7/10
Scored 7/10 (verified tier, metrics-v1). Evidence: January 27, 2025 release, unified understanding+generation design, 4096 sequence length and deepseek-ai/Janus-Pro-1B weights confirmed via the official deepseek-ai/Janus GitHub repo and third-party setup guides; GenEval/DPG-Bench figures attributed to DeepSeek. Strengths: unique unified multimodal capability at 1.5B params, commercial-use-friendly terms, runs on consumer GPUs. Docked for: (1) headline generation scores are provider figures without independent replication found; (2) the 1B variant's understanding benchmarks are unpublished and image quality lags the 7B sibling clearly. License: MIT (code); DeepSeek Model License (weights, commercial use permitted).
How the trust score is built
Full methodology →- Adoption · stars/downloads, log-scaled vs peers
- 7.0/10
- Maintenance · recency, releases, issue load
- 6.0/10
- Openness · license + docs
- 7.0/10
- Manual review · sanity read + red-flag check
- 7.0/10
- · DeepSeek; released 2025-01-27
- · Unified understanding+generation; 1.5B actual params
- · Generation scores provider-reported via third-party guide