DeepSeek-V3.2 (Thinking) vs Mercury 3
DeepSeek-V3.2 (Thinking) and Mercury 3 are closely matched at 32.2 and 36.1 on the LLM Stats Score. Mercury 3 is 1.9x cheaper per token.
DeepSeek · Inception · Updated for 2026
Which is better?
DeepSeek-V3.2 (Thinking) and Mercury 3 are closely matched on the overall LLM Stats Score at 32.2 and 36.1.
In the 1 individual benchmarks reported for both models, Mercury 3 wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Mercury 3 is roughly 1.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Mercury 3 also accepts a larger context window (1,000,000 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 (Thinking)
- you need open weights you can self-host or fine-tune
Choose Mercury 3
- your work emphasizes agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 1.9x cheaper per token
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Individual benchmarks
14 reported for DeepSeek-V3.2 (Thinking) · 12 for Mercury 3
DeepSeek-V3.2 (Thinking) outperforms in 0 benchmarks, while Mercury 3 is better at 1 benchmark (GPQA).
Mercury 3 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 (Thinking) ($0.28/1M tokens) is 2.8x more expensive than Mercury 3 ($0.10/1M tokens).
For output processing, DeepSeek-V3.2 (Thinking) ($0.42/1M tokens) is 1.2x more expensive than Mercury 3 ($0.35/1M tokens).
In conclusion, DeepSeek-V3.2 (Thinking) is more expensive than Mercury 3.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Mercury 3 accepts 1,000,000 input tokens compared to DeepSeek-V3.2 (Thinking)'s 131,072 tokens. Mercury 3 can generate longer responses up to 131,072 tokens, while DeepSeek-V3.2 (Thinking) is limited to 65,536 tokens.
License
Usage and distribution terms
DeepSeek-V3.2 (Thinking) is licensed under MIT, while Mercury 3 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 (Thinking) was released on 2025-12-01, while Mercury 3 was released on 2026-10-19.
Mercury 3 is 11 months newer than DeepSeek-V3.2 (Thinking).
Dec 1, 2025
10 months ago
Oct 19, 2026
5 days 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 (Thinking) is available from DeepSeek. Mercury 3 is available from Inception.
DeepSeek-V3.2 (Thinking)
Mercury 3
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3.2 (Thinking) and Mercury 3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3.2 (Thinking) vs Mercury 3.