DeepSeek-V4-Flash-Max vs Mercury 3
DeepSeek-V4-Flash-Max and Mercury 3 are closely matched at 38.9 and 36.1 on the LLM Stats Score. DeepSeek-V4-Flash-Max is 1.4x cheaper per token.
DeepSeek · Inception · Updated for 2026
Which is better?
DeepSeek-V4-Flash-Max and Mercury 3 are closely matched on the overall LLM Stats Score at 38.9 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, DeepSeek-V4-Flash-Max is roughly 1.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-Max also accepts a larger context window (1,048,576 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-V4-Flash-Max
- cost matters — it's about 1.4x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you need open weights you can self-host or fine-tune
Choose Mercury 3
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
19 reported for DeepSeek-V4-Flash-Max · 12 for Mercury 3
DeepSeek-V4-Flash-Max 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-V4-Flash-Max ($0.09/1M tokens) is 1.1x cheaper than Mercury 3 ($0.10/1M tokens).
For output processing, DeepSeek-V4-Flash-Max ($0.18/1M tokens) is 1.9x cheaper than Mercury 3 ($0.35/1M tokens).
In conclusion, Mercury 3 is more expensive than DeepSeek-V4-Flash-Max.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-Max accepts 1,048,576 input tokens compared to Mercury 3's 1,000,000 tokens. DeepSeek-V4-Flash-Max can generate longer responses up to 1,048,576 tokens, while Mercury 3 is limited to 131,072 tokens.
License
Usage and distribution terms
DeepSeek-V4-Flash-Max 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-V4-Flash-Max was released on 2026-04-23, while Mercury 3 was released on 2026-10-19.
Mercury 3 is 6 months newer than DeepSeek-V4-Flash-Max.
Apr 23, 2026
5 months ago
Oct 19, 2026
0 days ago
5mo 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-V4-Flash-Max is available from DeepInfra, DeepSeek. Mercury 3 is available from Inception.
DeepSeek-V4-Flash-Max
Mercury 3
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-Max and Mercury 3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-Max vs Mercury 3.