Model Comparison
MiniMax M2.5 vs Qwen3 VL 4B InstructWhich is better in 2026?
Comparing MiniMax M2.5 and Qwen3 VL 4B Instruct across benchmarks, pricing, and capabilities.
Verdict: MiniMax M2.5 vs Qwen3 VL 4B Instruct — which is better?
MiniMax M2.5 (by MiniMax) and Qwen3 VL 4B Instruct (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
On price, Qwen3 VL 4B Instruct is roughly 2.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiniMax M2.5 also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose MiniMax M2.5 if…
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Feb 2026
Choose Qwen3 VL 4B Instruct if…
- cost matters — it's about 2.3x cheaper per token
Performance Benchmarks
Comparative analysis across standard metrics
MiniMax M2.5 and Qwen3 VL 4B Instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, MiniMax M2.5 ($0.30/1M tokens) is 3.0x more expensive than Qwen3 VL 4B Instruct ($0.10/1M tokens).
For output processing, MiniMax M2.5 ($1.20/1M tokens) is 2.0x more expensive than Qwen3 VL 4B Instruct ($0.60/1M tokens).
In conclusion, MiniMax M2.5 is more expensive than Qwen3 VL 4B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiniMax M2.5 has 226.0B more parameters than Qwen3 VL 4B Instruct, making it 5650.0% larger.
Context Window
Maximum input and output token capacity
MiniMax M2.5 accepts 1,000,000 input tokens compared to Qwen3 VL 4B Instruct's 262,144 tokens. MiniMax M2.5 can generate longer responses up to 1,000,000 tokens, while Qwen3 VL 4B Instruct is limited to 262,144 tokens.
Input Capabilities
Supported data types and modalities
Qwen3 VL 4B Instruct supports multimodal inputs, whereas MiniMax M2.5 does not.
Qwen3 VL 4B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
MiniMax M2.5
Qwen3 VL 4B Instruct
License
Usage and distribution terms
MiniMax M2.5 is licensed under MIT, while Qwen3 VL 4B Instruct 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
MiniMax M2.5 was released on 2026-02-12, while Qwen3 VL 4B Instruct was released on 2025-09-22.
MiniMax M2.5 is 5 months newer than Qwen3 VL 4B Instruct.
Feb 12, 2026
3 months ago
4mo newerSep 22, 2025
8 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
MiniMax M2.5 is available from MiniMax. Qwen3 VL 4B Instruct is available from DeepInfra.
MiniMax M2.5
Qwen3 VL 4B Instruct
Outputs Comparison
Key Takeaways
MiniMax M2.5
View detailsMiniMax
Qwen3 VL 4B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about MiniMax M2.5 vs Qwen3 VL 4B Instruct.