Beam 1.0 vs MiniMax M3
Beam 1.0 and MiniMax M3 are closely matched at 44.6 and 40.9 on the LLM Stats Score. MiniMax M3 is 1.2x cheaper per token.
Reflection AI · MiniMax · Updated for 2026
Which is better?
Beam 1.0 and MiniMax M3 are closely matched on the overall LLM Stats Score at 44.6 and 40.9.
In the 6 individual benchmarks reported for both models, Beam 1.0 wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, MiniMax M3 is roughly 1.2x 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
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 6 exact shared results
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Oct 2026
Choose MiniMax M3
- cost matters — it's about 1.2x cheaper per token
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 · 35 for MiniMax M3
Beam 1.0 outperforms in 4 benchmarks (MCP Atlas, SWE-Bench Pro, SWE-Bench Verified, Terminal-Bench 2.1), while MiniMax M3 is better at 2 benchmarks (BrowseComp, SWE Atlas - Codebase QnA).
Beam 1.0 shows notably better performance in the majority of 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 1.4x more expensive than MiniMax M3 ($0.28/1M tokens).
For output processing, Beam 1.0 ($1.20/1M tokens) is 1.1x more expensive than MiniMax M3 ($1.10/1M tokens).
In conclusion, Beam 1.0 is more expensive than MiniMax M3.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Beam 1.0 has 73.3B more parameters than MiniMax M3, making it 17.1% larger.
Context Window
Maximum input and output token capacity
Beam 1.0 accepts 1,048,576 input tokens compared to MiniMax M3's 524,288 tokens. MiniMax M3 can generate longer responses up to 524,288 tokens, while Beam 1.0 is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
MiniMax M3 supports multimodal inputs, whereas Beam 1.0 does not.
MiniMax M3 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Beam 1.0
MiniMax M3
License
Usage and distribution terms
Beam 1.0 is licensed under Apache 2.0, while MiniMax M3 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Beam 1.0 was released on 2026-10-16, while MiniMax M3 was released on 2026-06-01.
Beam 1.0 is 5 months newer than MiniMax M3.
Oct 16, 2026
4 days ago
4mo newerJun 1, 2026
4 months ago
Knowledge Cutoff
When training data ends
Beam 1.0 has a documented knowledge cutoff of 2026-06-30, while MiniMax M3'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 MiniMax M3's cutoff date.
Jun 2026
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Provider Availability
Beam 1.0 is available from Together, Reflection AI. MiniMax M3 is available from DeepInfra, Fireworks, MiniMax, Novita, Together.
Beam 1.0
MiniMax M3
Outputs Comparison
Judge for yourself.
Run your own prompts against Beam 1.0 and MiniMax M3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Beam 1.0 vs MiniMax M3.