DeepSeek-R1-0528 vs Step3-VL-10B
DeepSeek-R1-0528 and Step3-VL-10B are closely matched at 24.1 and 25.5 on the LLM Stats Score.
DeepSeek · StepFun · Updated for 2026
Which is better?
DeepSeek-R1-0528 and Step3-VL-10B are closely matched on the overall LLM Stats Score at 24.1 and 25.5.
In the 1 individual benchmarks reported for both models, Step3-VL-10B wins 1; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-R1-0528
- you want predictable pricing at $0.50/M input and $2.15/M output
Choose Step3-VL-10B
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you want the most recent training data — it shipped Jan 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
16 reported for DeepSeek-R1-0528 · 6 for Step3-VL-10B
DeepSeek-R1-0528 outperforms in 0 benchmarks, while Step3-VL-10B is better at 1 benchmark (AIME 2025).
Step3-VL-10B significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
DeepSeek-R1-0528 has 661.0B more parameters than Step3-VL-10B, making it 6610.0% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-R1-0528 specifies input context (163,840 tokens). Only DeepSeek-R1-0528 specifies output context (163,840 tokens).
Input capabilities
Documented input modalities across available providers
Step3-VL-10B supports multimodal inputs, whereas DeepSeek-R1-0528 does not.
Step3-VL-10B can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-R1-0528
Step3-VL-10B
License
Usage and distribution terms
DeepSeek-R1-0528 is licensed under MIT, while Step3-VL-10B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-R1-0528 was released on 2025-05-28, while Step3-VL-10B was released on 2026-01-15.
Step3-VL-10B is 8 months newer than DeepSeek-R1-0528.
May 28, 2025
1.3 years ago
Jan 15, 2026
8 months ago
7mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-R1-0528 and Step3-VL-10B side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-R1-0528 vs Step3-VL-10B.