Model Comparison

MiniMax M1 80K vs Qwen3 VL 4B Thinking

MiniMax M1 80K significantly outperforms across most benchmarks. Qwen3 VL 4B Thinking is 3.0x cheaper per token.

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

MiniMax M1 80K outperforms in 3 benchmarks (AIME 2025, GPQA, MMLU-Pro), while Qwen3 VL 4B Thinking is better at 0 benchmarks.

MiniMax M1 80K significantly outperforms across most benchmarks.

Wed Jun 03 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3 VL 4B Thinking costs less

For input processing, MiniMax M1 80K ($0.55/1M tokens) is 5.5x more expensive than Qwen3 VL 4B Thinking ($0.10/1M tokens).

For output processing, MiniMax M1 80K ($2.20/1M tokens) is 2.2x more expensive than Qwen3 VL 4B Thinking ($1.00/1M tokens).

In conclusion, MiniMax M1 80K is more expensive than Qwen3 VL 4B Thinking.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Wed Jun 03 2026 • llm-stats.com
MiniMax
MiniMax M1 80K
Input tokens$0.55
Output tokens$2.20
Best providerNovita
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
Input tokens$0.10
Output tokens$1.00
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

452.0B diff

MiniMax M1 80K has 452.0B more parameters than Qwen3 VL 4B Thinking, making it 11300.0% larger.

MiniMax
MiniMax M1 80K
456.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
4.0Bparameters
456.0B
MiniMax M1 80K
4.0B
Qwen3 VL 4B Thinking

Context Window

Maximum input and output token capacity

MiniMax M1 80K accepts 1,000,000 input tokens compared to Qwen3 VL 4B Thinking's 262,144 tokens. Qwen3 VL 4B Thinking can generate longer responses up to 262,144 tokens, while MiniMax M1 80K is limited to 40,000 tokens.

MiniMax
MiniMax M1 80K
Input1,000,000 tokens
Output40,000 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
Input262,144 tokens
Output262,144 tokens
Wed Jun 03 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 4B Thinking supports multimodal inputs, whereas MiniMax M1 80K does not.

Qwen3 VL 4B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

MiniMax M1 80K

Text
Images
Audio
Video

Qwen3 VL 4B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

MiniMax M1 80K is licensed under MIT, while Qwen3 VL 4B Thinking uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

MiniMax M1 80K

MIT

Open weights

Qwen3 VL 4B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

MiniMax M1 80K was released on 2025-06-16, while Qwen3 VL 4B Thinking was released on 2025-09-22.

Qwen3 VL 4B Thinking is 3 months newer than MiniMax M1 80K.

MiniMax M1 80K

Jun 16, 2025

11 months ago

Qwen3 VL 4B Thinking

Sep 22, 2025

8 months ago

3mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

MiniMax M1 80K is available from Novita. Qwen3 VL 4B Thinking is available from DeepInfra.

MiniMax M1 80K

novita logo
Novita
Input Price:Input: $0.55/1MOutput Price:Output: $2.20/1M

Qwen3 VL 4B Thinking

deepinfra logo
Deepinfra
Input Price:Input: $0.10/1MOutput Price:Output: $1.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Larger context window (1,000,000 tokens)
Higher AIME 2025 score (76.9% vs 74.5%)
Higher GPQA score (70.0% vs 64.1%)
Higher MMLU-Pro score (81.1% vs 73.6%)
Alibaba Cloud / Qwen Team

Qwen3 VL 4B Thinking

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
MiniMax
MiniMax M1 80K
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking

FAQ

Common questions about MiniMax M1 80K vs Qwen3 VL 4B Thinking.

Which is better, MiniMax M1 80K or Qwen3 VL 4B Thinking?

MiniMax M1 80K significantly outperforms across most benchmarks. MiniMax M1 80K is made by MiniMax and Qwen3 VL 4B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does MiniMax M1 80K compare to Qwen3 VL 4B Thinking in benchmarks?

MiniMax M1 80K scores MATH-500: 96.8%, ZebraLogic: 86.8%, AIME 2024: 86.0%, MMLU-Pro: 81.1%, AIME 2025: 76.9%. Qwen3 VL 4B Thinking scores DocVQAtest: 94.2%, ScreenSpot: 92.9%, MMBench-V1.1: 86.7%, MMLU-Redux: 86.0%, AI2D: 84.9%.

Is MiniMax M1 80K cheaper than Qwen3 VL 4B Thinking?

Qwen3 VL 4B Thinking is 5.5x cheaper for input tokens. MiniMax M1 80K costs $0.55/M input and $2.20/M output via novita. Qwen3 VL 4B Thinking costs $0.10/M input and $1.00/M output via deepinfra.

What are the context window sizes for MiniMax M1 80K and Qwen3 VL 4B Thinking?

MiniMax M1 80K supports 1.0M tokens and Qwen3 VL 4B Thinking supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between MiniMax M1 80K and Qwen3 VL 4B Thinking?

Key differences include context window (1.0M vs 262K), input pricing ($0.55 vs $0.10/M), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes MiniMax M1 80K and Qwen3 VL 4B Thinking?

MiniMax M1 80K is developed by MiniMax and Qwen3 VL 4B Thinking is developed by Alibaba Cloud / Qwen Team.