Gemma 4 E4B vs Mercury 3
Mercury 3 leads the LLM Stats Score 36.1 to 13.3. Gemma 4 E4B is 4.1x cheaper per token.
Google · Inception · Updated for 2026
Which is better?
Mercury 3 leads the overall LLM Stats Score 36.1 to 13.3, ranking #98 overall.
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, Gemma 4 E4B is roughly 4.1x 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 Gemma 4 E4B
- cost matters — it's about 4.1x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Mercury 3
- overall performance matters — it scores 36.1 and ranks #98 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- 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
11 reported for Gemma 4 E4B · 12 for Mercury 3
Gemma 4 E4B 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, Gemma 4 E4B ($0.02/1M tokens) is 5.0x cheaper than Mercury 3 ($0.10/1M tokens).
For output processing, Gemma 4 E4B ($0.10/1M tokens) is 3.5x cheaper than Mercury 3 ($0.35/1M tokens).
In conclusion, Mercury 3 is more expensive than Gemma 4 E4B.*
* 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 Gemma 4 E4B's 131,072 tokens. Both models can generate responses up to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Gemma 4 E4B supports multimodal inputs, whereas Mercury 3 does not.
Gemma 4 E4B can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemma 4 E4B
Mercury 3
License
Usage and distribution terms
Gemma 4 E4B is licensed under Apache 2.0, while Mercury 3 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Gemma 4 E4B was released on 2026-04-02, while Mercury 3 was released on 2026-10-19.
Mercury 3 is 7 months newer than Gemma 4 E4B.
Apr 2, 2026
6 months ago
Oct 19, 2026
0 days ago
6mo newerKnowledge Cutoff
When training data ends
Gemma 4 E4B has a documented knowledge cutoff of 2025-01-01, while Mercury 3's cutoff date is not specified.
We can confirm Gemma 4 E4B's training data extends to 2025-01-01, but cannot make a direct comparison without Mercury 3's cutoff date.
Jan 2025
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Provider Availability
Gemma 4 E4B is available from DeepInfra. Mercury 3 is available from Inception.
Gemma 4 E4B
Mercury 3
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 4 E4B and Mercury 3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 4 E4B vs Mercury 3.