DeepSeek R1 Distill Qwen 32B vs o4-mini
o4-mini leads the LLM Stats Score 27.9 to 13.3. DeepSeek R1 Distill Qwen 32B is 14.3x cheaper per token.
DeepSeek · OpenAI · Updated for 2026
Which is better?
o4-mini leads the overall LLM Stats Score 27.9 to 13.3, ranking #126 overall.
In the 2 individual benchmarks reported for both models, o4-mini wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek R1 Distill Qwen 32B is roughly 14.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
o4-mini also accepts a larger context window (200,000 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 DeepSeek R1 Distill Qwen 32B
- cost matters — it's about 14.3x cheaper per token
- you need open weights you can self-host or fine-tune
Choose o4-mini
- overall performance matters — it scores 27.9 and ranks #126 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you process long inputs — it offers a 200,000 token context window
- you want the most recent training data — it shipped Apr 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
4 reported for DeepSeek R1 Distill Qwen 32B · 14 for o4-mini
DeepSeek R1 Distill Qwen 32B outperforms in 0 benchmarks, while o4-mini is better at 2 benchmarks (AIME 2024, GPQA).
o4-mini significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek R1 Distill Qwen 32B ($0.12/1M tokens) is 9.2x cheaper than o4-mini ($1.10/1M tokens).
For output processing, DeepSeek R1 Distill Qwen 32B ($0.18/1M tokens) is 24.4x cheaper than o4-mini ($4.40/1M tokens).
In conclusion, o4-mini is more expensive than DeepSeek R1 Distill Qwen 32B.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
o4-mini accepts 200,000 input tokens compared to DeepSeek R1 Distill Qwen 32B's 128,000 tokens. DeepSeek R1 Distill Qwen 32B can generate longer responses up to 128,000 tokens, while o4-mini is limited to 100,000 tokens.
Input capabilities
Documented input modalities across available providers
o4-mini supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 32B does not.
o4-mini can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek R1 Distill Qwen 32B
o4-mini
License
Usage and distribution terms
DeepSeek R1 Distill Qwen 32B is licensed under MIT, while o4-mini uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek R1 Distill Qwen 32B was released on 2025-01-20, while o4-mini was released on 2025-04-16.
o4-mini is 3 months newer than DeepSeek R1 Distill Qwen 32B.
Jan 20, 2025
1.6 years ago
Apr 16, 2025
1.4 years ago
2mo newerKnowledge Cutoff
When training data ends
o4-mini has a documented knowledge cutoff of 2024-05-31, while DeepSeek R1 Distill Qwen 32B's cutoff date is not specified.
We can confirm o4-mini's training data extends to 2024-05-31, but cannot make a direct comparison without DeepSeek R1 Distill Qwen 32B's cutoff date.
—
May 2024
Provider Availability
DeepSeek R1 Distill Qwen 32B is available from DeepInfra. o4-mini is available from OpenAI.
DeepSeek R1 Distill Qwen 32B
o4-mini
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek R1 Distill Qwen 32B and o4-mini side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek R1 Distill Qwen 32B vs o4-mini.