Model Comparison

Mistral Small 3.1 24B Base vs Qwen3 VL 4B ThinkingWhich is better in 2026?

Qwen3 VL 4B Thinking significantly outperforms across most benchmarks. Mistral Small 3.1 24B Base is 2.2x cheaper per token.

Verdict: Mistral Small 3.1 24B Base vs Qwen3 VL 4B Thinking — which is better?

Mistral Small 3.1 24B Base (by Mistral AI) and Qwen3 VL 4B Thinking (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.

Mistral Small 3.1 24B Base outperforms in 0 benchmarks, while Qwen3 VL 4B Thinking is better at 3 benchmarks (GPQA, MMLU, MMLU-Pro). Qwen3 VL 4B Thinking significantly outperforms across most benchmarks.

On price, Mistral Small 3.1 24B Base is roughly 2.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Qwen3 VL 4B Thinking also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.

Choose Mistral Small 3.1 24B Base if…

  • cost matters — it's about 2.2x cheaper per token

Choose Qwen3 VL 4B Thinking if…

  • you want the strongest raw capability — it leads on 3 of 3 shared benchmarks
  • you process long inputs — it offers a 262,144 token context window
  • you want the most recent training data — it shipped Sep 2025

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

Mistral Small 3.1 24B Base outperforms in 0 benchmarks, while Qwen3 VL 4B Thinking is better at 3 benchmarks (GPQA, MMLU, MMLU-Pro).

Qwen3 VL 4B Thinking significantly outperforms across most benchmarks.

Mon Jul 27 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Mistral Small 3.1 24B Base costs less

For input processing, Mistral Small 3.1 24B Base ($0.10/1M tokens) costs the same as Qwen3 VL 4B Thinking ($0.10/1M tokens).

For output processing, Mistral Small 3.1 24B Base ($0.30/1M tokens) is 3.3x cheaper than Qwen3 VL 4B Thinking ($1.00/1M tokens).

In conclusion, Qwen3 VL 4B Thinking is more expensive than Mistral Small 3.1 24B Base.*

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

Lowest available price from all providers
Mon Jul 27 2026 • llm-stats.com
Mistral AI
Mistral Small 3.1 24B Base
Input tokens$0.10
Output tokens$0.30
Best providerMistral
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

20.0B diff

Mistral Small 3.1 24B Base has 20.0B more parameters than Qwen3 VL 4B Thinking, making it 500.0% larger.

Mistral AI
Mistral Small 3.1 24B Base
24.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
4.0Bparameters
24.0B
Mistral Small 3.1 24B Base
4.0B
Qwen3 VL 4B Thinking

Context Window

Maximum input and output token capacity

Qwen3 VL 4B Thinking accepts 262,144 input tokens compared to Mistral Small 3.1 24B Base's 128,000 tokens. Qwen3 VL 4B Thinking can generate longer responses up to 262,144 tokens, while Mistral Small 3.1 24B Base is limited to 128,000 tokens.

Mistral AI
Mistral Small 3.1 24B Base
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
Input262,144 tokens
Output262,144 tokens
Mon Jul 27 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Mistral Small 3.1 24B Base and Qwen3 VL 4B Thinking support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Mistral Small 3.1 24B Base

Text
Images
Audio
Video

Qwen3 VL 4B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

Both models share the same licensing terms, providing consistent usage rights.

Mistral Small 3.1 24B Base

Apache 2.0

Open weights

Qwen3 VL 4B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Mistral Small 3.1 24B Base was released on 2025-03-17, while Qwen3 VL 4B Thinking was released on 2025-09-22.

Qwen3 VL 4B Thinking is 6 months newer than Mistral Small 3.1 24B Base.

Mistral Small 3.1 24B Base

Mar 17, 2025

1.4 years ago

Qwen3 VL 4B Thinking

Sep 22, 2025

10 months ago

6mo 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

Mistral Small 3.1 24B Base is available from Mistral AI. Qwen3 VL 4B Thinking is available from DeepInfra.

Mistral Small 3.1 24B Base

mistral logo
Mistral
Input Price:Input: $0.10/1MOutput Price:Output: $0.30/1M

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

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Mistral AI
Less expensive output tokens
Alibaba Cloud / Qwen Team

Qwen3 VL 4B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)
Higher GPQA score (64.1% vs 37.5%)
Higher MMLU score (81.5% vs 81.0%)
Higher MMLU-Pro score (73.6% vs 56.0%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Mistral Small 3.1 24B Base and Qwen3 VL 4B Thinking side-by-side, then vote on the output you prefer.

Mistral Small 3.1 24B Base
✓ Preferred
Qwen3 VL 4B Thinking
Open in Playground
AI Model Comparison Table
Feature
Mistral AI
Mistral Small 3.1 24B Base
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking

FAQ

Common questions about Mistral Small 3.1 24B Base vs Qwen3 VL 4B Thinking.

Which is better, Mistral Small 3.1 24B Base or Qwen3 VL 4B Thinking?

Qwen3 VL 4B Thinking significantly outperforms across most benchmarks. Mistral Small 3.1 24B Base is made by Mistral AI 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 Mistral Small 3.1 24B Base compare to Qwen3 VL 4B Thinking in benchmarks?

Mistral Small 3.1 24B Base scores MMLU: 81.0%, TriviaQA: 80.5%, MMMU: 59.3%, MMLU-Pro: 56.0%, GPQA: 37.5%. Qwen3 VL 4B Thinking scores DocVQAtest: 94.2%, ScreenSpot: 92.9%, MMBench-V1.1: 86.7%, MMLU-Redux: 86.0%, AI2D: 84.9%.

Is Mistral Small 3.1 24B Base cheaper than Qwen3 VL 4B Thinking?

Both models cost $0.10 per million input tokens.

What are the context window sizes for Mistral Small 3.1 24B Base and Qwen3 VL 4B Thinking?

Mistral Small 3.1 24B Base supports 128K 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 Mistral Small 3.1 24B Base and Qwen3 VL 4B Thinking?

Key differences include context window (128K vs 262K). See the full comparison above for benchmark-by-benchmark results.

Who makes Mistral Small 3.1 24B Base and Qwen3 VL 4B Thinking?

Mistral Small 3.1 24B Base is developed by Mistral AI and Qwen3 VL 4B Thinking is developed by Alibaba Cloud / Qwen Team.

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