IBM Granite 4.2 30B vs Mercury 3
Mercury 3 leads the LLM Stats Score 36.1 to 23.3. Mercury 3 is 1.7x cheaper per token.
IBM · Inception · Updated for 2026
Which is better?
Mercury 3 leads the overall LLM Stats Score 36.1 to 23.3, ranking #98 overall.
The models split the 2 individual benchmarks reported for both models evenly.
On price, Mercury 3 is roughly 1.7x 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 IBM Granite 4.2 30B
- 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 and coding — it leads those capability indexes
- cost matters — it's about 1.7x 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.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
18 reported for IBM Granite 4.2 30B · 12 for Mercury 3
IBM Granite 4.2 30B outperforms in 1 benchmarks (IFBench), while Mercury 3 is better at 1 benchmark (GPQA).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, IBM Granite 4.2 30B ($0.16/1M tokens) is 1.6x more expensive than Mercury 3 ($0.10/1M tokens).
For output processing, IBM Granite 4.2 30B ($0.65/1M tokens) is 1.9x more expensive than Mercury 3 ($0.35/1M tokens).
In conclusion, IBM Granite 4.2 30B 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 IBM Granite 4.2 30B's 131,072 tokens. Both models can generate responses up to 131,072 tokens.
License
Usage and distribution terms
IBM Granite 4.2 30B 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
IBM Granite 4.2 30B was released on 2026-08-25, while Mercury 3 was released on 2026-10-19.
Mercury 3 is 2 months newer than IBM Granite 4.2 30B.
Aug 25, 2026
1 months ago
Oct 19, 2026
0 days ago
1mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
IBM Granite 4.2 30B is available from DeepInfra. Mercury 3 is available from Inception.
IBM Granite 4.2 30B
Mercury 3
Outputs Comparison
Judge for yourself.
Run your own prompts against IBM Granite 4.2 30B and Mercury 3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about IBM Granite 4.2 30B vs Mercury 3.