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Beam 1.0 vs MiniMax M2.7

Beam 1.0 leads the LLM Stats Score 44.6 to 35.4. MiniMax M2.7 is 1.1x cheaper per token.

Reflection AI · MiniMax · Updated for 2026

Which is better?

Beam 1.0 leads the overall LLM Stats Score 44.6 to 35.4, ranking #46 overall.

In the 2 individual benchmarks reported for both models, Beam 1.0 wins 2; this is a narrower head-to-head signal than the composite indexes.

On price, MiniMax M2.7 is roughly 1.1x 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 and agents — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 2 of 2 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 M2.7

  • cost matters — it's about 1.1x cheaper per token

At a glance

The differences that matter most.

Beam 1.0
Reflection AI
MiniMax M2.7
MiniMax
Core performance indexes
LLM Stats Score
44.6
#46
35.4
#105
Reasoning
45.5
#37
34.5
#106
Coding
33.7
#39
27.1
#77
Agents
28.8
#53
15.6
#105
Cost, coverage & limits
Benchmark wins
2 of 2
0 of 2
Input price
$0.40 / M
$0.30 / M
Output price
$1.20 / M
$1.20 / M
Context window
1,048,576
196,608

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Beam 1.0
MiniMax M2.7
Tool use
26.4#32
15.2#108
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

22 reported for Beam 1.0 · 11 for MiniMax M2.7

2 shared

Beam 1.0 outperforms in 2 benchmarks (SWE-bench Multilingual, SWE-Bench Pro), while MiniMax M2.7 is better at 0 benchmarks.

Beam 1.0 significantly outperforms across most benchmarks.

Thu Oct 22 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

MiniMax M2.7 costs less

For input processing, Beam 1.0 ($0.40/1M tokens) is 1.3x more expensive than MiniMax M2.7 ($0.30/1M tokens).

For output processing, Beam 1.0 ($1.20/1M tokens) costs the same as MiniMax M2.7 ($1.20/1M tokens).

In conclusion, Beam 1.0 is more expensive than MiniMax M2.7.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Thu Oct 22 2026 • llm-stats.com
Reflection AI
Beam 1.0
Input tokens$0.40
Output tokens$1.20
Best providerTogether
MiniMax
MiniMax M2.7
Input tokens$0.30
Output tokens$1.20
Best providerFireworks
Notice missing or incorrect data?

Context Window

Maximum input and output token capacity

Beam 1.0 accepts 1,048,576 input tokens compared to MiniMax M2.7's 196,608 tokens. MiniMax M2.7 can generate longer responses up to 196,608 tokens, while Beam 1.0 is limited to 131,072 tokens.

Reflection AI
Beam 1.0
Input1,048,576 tokens
Output131,072 tokens
MiniMax
MiniMax M2.7
Input196,608 tokens
Output196,608 tokens
Thu Oct 22 2026 • llm-stats.com

License

Usage and distribution terms

Beam 1.0 is licensed under Apache 2.0, while MiniMax M2.7 uses MIT.

License differences may affect how you can use these models in commercial or open-source projects.

Beam 1.0

Apache 2.0

Open weights

MiniMax M2.7

MIT

Open weights

Release Timeline

When each model was launched

Beam 1.0 was released on 2026-10-16, while MiniMax M2.7 was released on 2026-03-18.

Beam 1.0 is 7 months newer than MiniMax M2.7.

Beam 1.0

Oct 16, 2026

4 days ago

7mo newer
MiniMax M2.7

Mar 18, 2026

7 months ago

Knowledge Cutoff

When training data ends

Beam 1.0 has a documented knowledge cutoff of 2026-06-30, while MiniMax M2.7'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 M2.7's cutoff date.

Beam 1.0

Jun 2026

MiniMax M2.7

—

Provider Availability

Beam 1.0 is available from Together, Reflection AI. MiniMax M2.7 is available from Fireworks, MiniMax, Novita, DeepInfra.

Beam 1.0

together logo
Together
Input Price:Input: $0.40/1MOutput Price:Output: $1.20/1M
reflection logo
Unknown Organization

MiniMax M2.7

fireworks logo
Fireworks
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
minimax logo
MiniMax
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
novita logo
Novita
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.38/1MOutput Price:Output: $1.70/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Beam 1.0 and MiniMax M2.7 side-by-side, then vote on the output you prefer.

Beam 1.0
✓ Preferred
MiniMax M2.7
Open in Playground

FAQ

Common questions about Beam 1.0 vs MiniMax M2.7.

Which is better, Beam 1.0 or MiniMax M2.7?

Beam 1.0 leads the LLM Stats Score 44.6 to 35.4. Beam 1.0 is made by Reflection AI and MiniMax M2.7 is made by MiniMax. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Beam 1.0 compare to MiniMax M2.7 in benchmarks?

Beam 1.0 scores AIME 2026: 97.7%, GPQA: 90.6%, LiveCodeBench: 88.3%, SWE-Bench Verified: 81.6%, MCP Atlas: 80.8%. MiniMax M2.7 scores SWE-bench Multilingual: 76.5%, MLE-Bench Lite: 66.6%, MM-ClawBench: 62.7%, Terminal-Bench 2.0: 57.0%, SWE-Bench Pro: 56.2%.

Is Beam 1.0 cheaper than MiniMax M2.7?

MiniMax M2.7 is 1.3x cheaper for input tokens. Beam 1.0 costs $0.40/M input and $1.20/M output via together. MiniMax M2.7 costs $0.30/M input and $1.20/M output via fireworks.

What are the context window sizes for Beam 1.0 and MiniMax M2.7?

Beam 1.0 supports 1.0M tokens and MiniMax M2.7 supports 197K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Beam 1.0 and MiniMax M2.7?

Key differences include LLM Stats Score (44.6 vs 35.4), context window (1.0M vs 197K), input pricing ($0.40 vs $0.30/M), licensing (Apache 2.0 vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Beam 1.0 and MiniMax M2.7?

Beam 1.0 is developed by Reflection AI and MiniMax M2.7 is developed by MiniMax.

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