Beam 1.0 vs Gemini 3.1 Pro
Beam 1.0 and Gemini 3.1 Pro are closely matched at 44.6 and 43.0 on the LLM Stats Score. Beam 1.0 is 7.5x cheaper per token.
Reflection AI · Google · Updated for 2026
Which is better?
Beam 1.0 and Gemini 3.1 Pro are closely matched on the overall LLM Stats Score at 44.6 and 43.0.
The models split the 8 individual benchmarks reported for both models evenly.
On price, Beam 1.0 is roughly 7.5x 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
- cost matters — it's about 7.5x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Oct 2026
- you need open weights you can self-host or fine-tune
Choose Gemini 3.1 Pro
- you want predictable pricing at $2.00/M input and $12.00/M output
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 · 20 for Gemini 3.1 Pro
Beam 1.0 outperforms in 4 benchmarks (DeepSWE 1.1, MCP Atlas, SWE-Bench Pro, SWE-Bench Verified), while Gemini 3.1 Pro is better at 4 benchmarks (BrowseComp, GPQA, Humanity's Last Exam, SciCode).
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, Beam 1.0 ($0.40/1M tokens) is 5.0x cheaper than Gemini 3.1 Pro ($2.00/1M tokens).
For output processing, Beam 1.0 ($1.20/1M tokens) is 10.0x cheaper than Gemini 3.1 Pro ($12.00/1M tokens).
In conclusion, Gemini 3.1 Pro is more expensive than Beam 1.0.*
* 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 Gemini 3.1 Pro's 1,000,000 tokens. Gemini 3.1 Pro can generate longer responses up to 1,000,000 tokens, while Beam 1.0 is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Gemini 3.1 Pro supports multimodal inputs, whereas Beam 1.0 does not.
Gemini 3.1 Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.
Beam 1.0
Gemini 3.1 Pro
License
Usage and distribution terms
Beam 1.0 is licensed under Apache 2.0, while Gemini 3.1 Pro 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 Gemini 3.1 Pro was released on 2026-02-19.
Beam 1.0 is 8 months newer than Gemini 3.1 Pro.
Oct 16, 2026
4 days ago
7mo newerFeb 19, 2026
8 months ago
Knowledge Cutoff
When training data ends
Beam 1.0 has a knowledge cutoff of 2026-06-30, while Gemini 3.1 Pro has a cutoff of 2025-01-31.
Beam 1.0 has more recent training data (up to 2026-06-30), making it potentially better informed about events through that date compared to Gemini 3.1 Pro (2025-01-31).
Jun 2026
1.4 yr newerJan 2025
Provider Availability
Beam 1.0 is available from Together, Reflection AI. Gemini 3.1 Pro is available from DeepInfra, Google.
Beam 1.0
Gemini 3.1 Pro
Outputs Comparison
Judge for yourself.
Run your own prompts against Beam 1.0 and Gemini 3.1 Pro side-by-side, then vote on the output you prefer.
FAQ
Common questions about Beam 1.0 vs Gemini 3.1 Pro.