DeepSeek-V3.2-Exp vs Qwen3.8 Max
Qwen3.8 Max leads the LLM Stats Score 51.9 to 28.2. DeepSeek-V3.2-Exp is 8.1x cheaper per token.
DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3.8 Max leads the overall LLM Stats Score 51.9 to 28.2, ranking #11 overall.
In the 2 individual benchmarks reported for both models, Qwen3.8 Max wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V3.2-Exp is roughly 8.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3.8 Max also accepts a larger context window (256,000 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-Exp
- cost matters — it's about 8.1x cheaper per token
Choose Qwen3.8 Max
- overall performance matters — it scores 51.9 and ranks #11 on LLM Stats
- your work emphasizes reasoning and coding — 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 256,000 token context window
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
14 reported for DeepSeek-V3.2-Exp · 42 for Qwen3.8 Max
DeepSeek-V3.2-Exp outperforms in 0 benchmarks, while Qwen3.8 Max is better at 2 benchmarks (GPQA, Humanity's Last Exam).
Qwen3.8 Max 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-Exp ($0.27/1M tokens) is 6.1x cheaper than Qwen3.8 Max ($1.65/1M tokens).
For output processing, DeepSeek-V3.2-Exp ($0.41/1M tokens) is 12.1x cheaper than Qwen3.8 Max ($4.95/1M tokens).
In conclusion, Qwen3.8 Max is more expensive than DeepSeek-V3.2-Exp.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3.8 Max has 1715.0B more parameters than DeepSeek-V3.2-Exp, making it 250.4% larger.
Context Window
Maximum input and output token capacity
Qwen3.8 Max accepts 256,000 input tokens compared to DeepSeek-V3.2-Exp's 163,840 tokens. Qwen3.8 Max can generate longer responses up to 256,000 tokens, while DeepSeek-V3.2-Exp is limited to 65,536 tokens.
Input capabilities
Documented input modalities across available providers
Qwen3.8 Max supports multimodal inputs, whereas DeepSeek-V3.2-Exp does not.
Qwen3.8 Max can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3.2-Exp
Qwen3.8 Max
License
Usage and distribution terms
DeepSeek-V3.2-Exp is licensed under MIT, while Qwen3.8 Max uses Qwen3.8-Max License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Qwen3.8-Max License
Open weights
Release Timeline
When each model was launched
DeepSeek-V3.2-Exp was released on 2025-09-29, while Qwen3.8 Max was released on 2026-08-02.
Qwen3.8 Max is 10 months newer than DeepSeek-V3.2-Exp.
Sep 29, 2025
11 months ago
Aug 2, 2026
1 months ago
10mo newerKnowledge 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-Exp is available from Novita. Qwen3.8 Max is available from DeepInfra, Fireworks, Novita, Together.
DeepSeek-V3.2-Exp
Qwen3.8 Max
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3.2-Exp and Qwen3.8 Max side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3.2-Exp vs Qwen3.8 Max.