Mistral Large 4 vs QwQ-32B-Preview
Mistral Large 4 leads the LLM Stats Score 46.4 to 9.0. QwQ-32B-Preview is 6.4x cheaper per token.
Mistral AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Mistral Large 4 leads the overall LLM Stats Score 46.4 to 9.0, ranking #32 overall.
On price, QwQ-32B-Preview is roughly 6.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Mistral Large 4 also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Mistral Large 4
- overall performance matters — it scores 46.4 and ranks #32 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Oct 2026
Choose QwQ-32B-Preview
- cost matters — it's about 6.4x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
15 reported for Mistral Large 4 · 4 for QwQ-32B-Preview
Mistral Large 4 and QwQ-32B-Previewdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Mistral Large 4 ($0.68/1M tokens) is 4.5x more expensive than QwQ-32B-Preview ($0.15/1M tokens).
For output processing, Mistral Large 4 ($2.09/1M tokens) is 10.4x more expensive than QwQ-32B-Preview ($0.20/1M tokens).
In conclusion, Mistral Large 4 is more expensive than QwQ-32B-Preview.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Mistral Large 4 has 1017.5B more parameters than QwQ-32B-Preview, making it 3130.8% larger.
Context Window
Maximum input and output token capacity
Mistral Large 4 accepts 1,000,000 input tokens compared to QwQ-32B-Preview's 32,768 tokens. Only QwQ-32B-Preview specifies output context (32,768 tokens).
Input capabilities
Documented input modalities across available providers
Mistral Large 4 supports multimodal inputs, whereas QwQ-32B-Preview does not.
Mistral Large 4 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Mistral Large 4
QwQ-32B-Preview
License
Usage and distribution terms
Mistral Large 4 is licensed under a proprietary license, while QwQ-32B-Preview uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
Mistral Large 4 was released on 2026-10-06, while QwQ-32B-Preview was released on 2024-11-28.
Mistral Large 4 is 23 months newer than QwQ-32B-Preview.
Oct 6, 2026
1 days ago
1.9yr newerNov 28, 2024
1.9 years ago
Knowledge Cutoff
When training data ends
QwQ-32B-Preview has a documented knowledge cutoff of 2024-11-28, while Mistral Large 4's cutoff date is not specified.
We can confirm QwQ-32B-Preview's training data extends to 2024-11-28, but cannot make a direct comparison without Mistral Large 4's cutoff date.
—
Nov 2024
Provider Availability
Mistral Large 4 is available from Mistral AI. QwQ-32B-Preview is available from DeepInfra, Hyperbolic, Fireworks, Together.
Mistral Large 4
QwQ-32B-Preview
Outputs Comparison
Judge for yourself.
Run your own prompts against Mistral Large 4 and QwQ-32B-Preview side-by-side, then vote on the output you prefer.
FAQ
Common questions about Mistral Large 4 vs QwQ-32B-Preview.