DeepSeek-V3.1 vs Qwen3 Max
DeepSeek-V3.1 and Qwen3 Max are closely matched at 22.1 and 21.7 on the LLM Stats Score. DeepSeek-V3.1 is 3.8x cheaper per token.
DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
DeepSeek-V3.1 and Qwen3 Max are closely matched on the overall LLM Stats Score at 22.1 and 21.7.
In the 3 individual benchmarks reported for both models, Qwen3 Max wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V3.1 is roughly 3.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 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-V3.1
- cost matters — it's about 3.8x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Qwen3 Max
- you value its reported benchmark strengths — it wins 2 of 3 exact shared results
- you process long inputs — it offers a 256,000 token context window
- you want the most recent training data — it shipped Dec 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
16 reported for DeepSeek-V3.1 · 6 for Qwen3 Max
DeepSeek-V3.1 outperforms in 1 benchmarks (GPQA), while Qwen3 Max is better at 2 benchmarks (AIME 2025, SWE-Bench Verified).
Qwen3 Max shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3.1 ($0.25/1M tokens) is 2.0x cheaper than Qwen3 Max ($0.50/1M tokens).
For output processing, DeepSeek-V3.1 ($0.95/1M tokens) is 5.3x cheaper than Qwen3 Max ($5.00/1M tokens).
In conclusion, Qwen3 Max is more expensive than DeepSeek-V3.1.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3 Max has 329.0B more parameters than DeepSeek-V3.1, making it 49.0% larger.
Context Window
Maximum input and output token capacity
Qwen3 Max accepts 256,000 input tokens compared to DeepSeek-V3.1's 163,840 tokens. DeepSeek-V3.1 can generate longer responses up to 163,840 tokens, while Qwen3 Max is limited to 131,072 tokens.
License
Usage and distribution terms
DeepSeek-V3.1 is licensed under MIT, while Qwen3 Max 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-V3.1 was released on 2025-01-10, while Qwen3 Max was released on 2025-12-15.
Qwen3 Max is 11 months newer than DeepSeek-V3.1.
Jan 10, 2025
1.7 years ago
Dec 15, 2025
9 months ago
11mo 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-V3.1 is available from DeepInfra, Novita. Qwen3 Max is available from Novita, DeepInfra.
DeepSeek-V3.1
Qwen3 Max
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3.1 and Qwen3 Max side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3.1 vs Qwen3 Max.