DeepSeek-V3.2-Speciale vs Devstral Medium
DeepSeek-V3.2-Speciale leads the LLM Stats Score 33.9 to 13.6. DeepSeek-V3.2-Speciale is 2.5x cheaper per token.
DeepSeek · Mistral AI · Updated for 2026
Which is better?
DeepSeek-V3.2-Speciale leads the overall LLM Stats Score 33.9 to 13.6, ranking #102 overall.
In the 1 individual benchmarks reported for both models, DeepSeek-V3.2-Speciale wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V3.2-Speciale is roughly 2.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V3.2-Speciale also accepts a larger context window (131,072 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-V3.2-Speciale
- overall performance matters — it scores 33.9 and ranks #102 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 2.5x cheaper per token
- you process long inputs — it offers a 131,072 token context window
- you want the most recent training data — it shipped Dec 2025
- you need open weights you can self-host or fine-tune
Choose Devstral Medium
- you want predictable pricing at $0.40/M input and $2.00/M output
At a glance
The differences that matter most.
Individual benchmarks
8 reported for DeepSeek-V3.2-Speciale · 1 for Devstral Medium
DeepSeek-V3.2-Speciale outperforms in 1 benchmarks (SWE-Bench Verified), while Devstral Medium is better at 0 benchmarks.
DeepSeek-V3.2-Speciale 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-V3.2-Speciale ($0.28/1M tokens) is 1.4x cheaper than Devstral Medium ($0.40/1M tokens).
For output processing, DeepSeek-V3.2-Speciale ($0.42/1M tokens) is 4.8x cheaper than Devstral Medium ($2.00/1M tokens).
In conclusion, Devstral Medium is more expensive than DeepSeek-V3.2-Speciale.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
DeepSeek-V3.2-Speciale accepts 131,072 input tokens compared to Devstral Medium's 128,000 tokens. DeepSeek-V3.2-Speciale can generate longer responses up to 131,072 tokens, while Devstral Medium is limited to 128,000 tokens.
License
Usage and distribution terms
DeepSeek-V3.2-Speciale is licensed under MIT, while Devstral Medium 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-V3.2-Speciale was released on 2025-12-01, while Devstral Medium was released on 2025-07-10.
DeepSeek-V3.2-Speciale is 5 months newer than Devstral Medium.
Dec 1, 2025
9 months ago
4mo newerJul 10, 2025
1.2 years 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
DeepSeek-V3.2-Speciale is available from DeepSeek. Devstral Medium is available from Mistral AI.
DeepSeek-V3.2-Speciale
Devstral Medium
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3.2-Speciale and Devstral Medium side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3.2-Speciale vs Devstral Medium.