DeepSeek-V3.2-Speciale vs GPT-5.1 Codex High
DeepSeek-V3.2-Speciale and GPT-5.1 Codex High are closely matched at 33.8 and 29.3 on the LLM Stats Score. DeepSeek-V3.2-Speciale is 10.9x cheaper per token.
DeepSeek · OpenAI · Updated for 2026
Which is better?
DeepSeek-V3.2-Speciale and GPT-5.1 Codex High are closely matched on the overall LLM Stats Score at 33.8 and 29.3.
In the 1 individual benchmarks reported for both models, GPT-5.1 Codex High wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V3.2-Speciale is roughly 10.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5.1 Codex High also accepts a larger context window (400,000 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-V3.2-Speciale
- cost matters — it's about 10.9x cheaper per token
- you want the most recent training data — it shipped Dec 2025
- you need open weights you can self-host or fine-tune
Choose GPT-5.1 Codex High
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you process long inputs — it offers a 400,000 token context window
At a glance
The differences that matter most.
Individual benchmarks
8 reported for DeepSeek-V3.2-Speciale · 1 for GPT-5.1 Codex High
DeepSeek-V3.2-Speciale outperforms in 0 benchmarks, while GPT-5.1 Codex High is better at 1 benchmark (AIME 2025).
GPT-5.1 Codex High 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 4.5x cheaper than GPT-5.1 Codex High ($1.25/1M tokens).
For output processing, DeepSeek-V3.2-Speciale ($0.42/1M tokens) is 23.8x cheaper than GPT-5.1 Codex High ($10.00/1M tokens).
In conclusion, GPT-5.1 Codex High 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
GPT-5.1 Codex High accepts 400,000 input tokens compared to DeepSeek-V3.2-Speciale's 131,072 tokens. DeepSeek-V3.2-Speciale can generate longer responses up to 131,072 tokens, while GPT-5.1 Codex High is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-5.1 Codex High supports multimodal inputs, whereas DeepSeek-V3.2-Speciale does not.
GPT-5.1 Codex High can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3.2-Speciale
GPT-5.1 Codex High
License
Usage and distribution terms
DeepSeek-V3.2-Speciale is licensed under MIT, while GPT-5.1 Codex High 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 GPT-5.1 Codex High was released on 2025-11-12.
DeepSeek-V3.2-Speciale is 1 month newer than GPT-5.1 Codex High.
Dec 1, 2025
10 months ago
2w newerNov 12, 2025
11 months 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. GPT-5.1 Codex High is available from OpenAI.
DeepSeek-V3.2-Speciale
GPT-5.1 Codex High
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3.2-Speciale and GPT-5.1 Codex High side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3.2-Speciale vs GPT-5.1 Codex High.
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