Beam 1.0 vs Mercury 3
Beam 1.0 leads the LLM Stats Score 44.6 to 36.1. Mercury 3 is 3.7x cheaper per token.
Reflection AI · Inception · Updated for 2026
Which is better?
Beam 1.0 leads the overall LLM Stats Score 44.6 to 36.1, ranking #46 overall.
In the 5 individual benchmarks reported for both models, Beam 1.0 wins 5; this is a narrower head-to-head signal than the composite indexes.
On price, Mercury 3 is roughly 3.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Beam 1.0 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 Beam 1.0
- overall performance matters — it scores 44.6 and ranks #46 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 5 of 5 exact shared results
- 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
- cost matters — it's about 3.7x cheaper per token
- 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
22 reported for Beam 1.0 · 12 for Mercury 3
Beam 1.0 outperforms in 5 benchmarks (AA-LCR, DeepSearchQA, GPQA, IFBench, Tau3 Banking), while Mercury 3 is better at 0 benchmarks.
Beam 1.0 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, Beam 1.0 ($0.40/1M tokens) is 4.0x more expensive than Mercury 3 ($0.10/1M tokens).
For output processing, Beam 1.0 ($1.20/1M tokens) is 3.4x more expensive than Mercury 3 ($0.35/1M tokens).
In conclusion, Beam 1.0 is more expensive than Mercury 3.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Beam 1.0 accepts 1,048,576 input tokens compared to Mercury 3's 1,000,000 tokens. Both models can generate responses up to 131,072 tokens.
License
Usage and distribution terms
Beam 1.0 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
Beam 1.0 was released on 2026-10-16, while Mercury 3 was released on 2026-10-19.
Mercury 3 is 0 month newer than Beam 1.0.
Oct 16, 2026
4 days ago
Oct 19, 2026
1 days ago
3d newerKnowledge Cutoff
When training data ends
Beam 1.0 has a documented knowledge cutoff of 2026-06-30, while Mercury 3's cutoff date is not specified.
We can confirm Beam 1.0's training data extends to 2026-06-30, but cannot make a direct comparison without Mercury 3's cutoff date.
Jun 2026
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Provider Availability
Beam 1.0 is available from Together, Reflection AI. Mercury 3 is available from Inception.
Beam 1.0
Mercury 3
Outputs Comparison
Judge for yourself.
Run your own prompts against Beam 1.0 and Mercury 3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Beam 1.0 vs Mercury 3.