Ministral 3 (14B Base 2512) vs Qwen3 VL 4B Instruct
Ministral 3 (14B Base 2512) and Qwen3 VL 4B Instruct are closely matched at 3.6 and 10.8 on the LLM Stats Score.
Mistral AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Ministral 3 (14B Base 2512) and Qwen3 VL 4B Instruct are closely matched on the overall LLM Stats Score at 3.6 and 10.8.
In the 2 individual benchmarks reported for both models, Ministral 3 (14B Base 2512) wins 2; 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 Ministral 3 (14B Base 2512)
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you want the most recent training data — it shipped Dec 2025
Choose Qwen3 VL 4B Instruct
- you want predictable pricing at $0.10/M input and $0.60/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
6 reported for Ministral 3 (14B Base 2512) · 45 for Qwen3 VL 4B Instruct
Ministral 3 (14B Base 2512) outperforms in 2 benchmarks (MMLU, MMLU-Redux), while Qwen3 VL 4B Instruct is better at 0 benchmarks.
Ministral 3 (14B Base 2512) significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
Ministral 3 (14B Base 2512) has 10.0B more parameters than Qwen3 VL 4B Instruct, making it 250.0% larger.
Context Window
Maximum input and output token capacity
Only Qwen3 VL 4B Instruct specifies input context (262,144 tokens). Only Qwen3 VL 4B Instruct specifies output context (262,144 tokens).
Input capabilities
Documented input modalities across available providers
Both Ministral 3 (14B Base 2512) and Qwen3 VL 4B Instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Ministral 3 (14B Base 2512)
Qwen3 VL 4B Instruct
License
Usage and distribution terms
Both models are licensed under Apache 2.0.
Both models share the same licensing terms, providing consistent usage rights.
Apache 2.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Ministral 3 (14B Base 2512) was released on 2025-12-04, while Qwen3 VL 4B Instruct was released on 2025-09-22.
Ministral 3 (14B Base 2512) is 2 months newer than Qwen3 VL 4B Instruct.
Dec 4, 2025
9 months ago
2mo newerSep 22, 2025
11 months ago
Knowledge 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 Ministral 3 (14B Base 2512) and Qwen3 VL 4B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Ministral 3 (14B Base 2512) vs Qwen3 VL 4B Instruct.