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Beam 1.0 vs Mistral Small 3.2 24B Instruct

Beam 1.0 leads the LLM Stats Score 44.6 to 8.0. Mistral Small 3.2 24B Instruct is 5.6x cheaper per token.

Reflection AI · Mistral AI · Updated for 2026

Which is better?

Beam 1.0 leads the overall LLM Stats Score 44.6 to 8.0, ranking #46 overall.

In the 1 individual benchmarks reported for both models, Beam 1.0 wins 1; this is a narrower head-to-head signal than the composite indexes.

On price, Mistral Small 3.2 24B Instruct is roughly 5.6x 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 1 of 1 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 Mistral Small 3.2 24B Instruct

  • cost matters — it's about 5.6x cheaper per token

At a glance

The differences that matter most.

Beam 1.0
Reflection AI
Mistral Small 3.2 24B Instruct
Mistral AI
Core performance indexes
LLM Stats Score
44.6
#46
8.0
#304
Reasoning
45.5
#37
7.5
#305
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$0.40 / M
$0.07 / M
Output price
$1.20 / M
$0.20 / M
Context window
1,048,576
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Beam 1.0
Mistral Small 3.2 24B Instruct
Math
35.1#45
11.1#257
Vision
15.9#105
10.0#142
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

22 reported for Beam 1.0 · 15 for Mistral Small 3.2 24B Instruct

1 shared

Beam 1.0 outperforms in 1 benchmarks (GPQA), while Mistral Small 3.2 24B Instruct is better at 0 benchmarks.

Beam 1.0 significantly outperforms across most benchmarks.

Sat Oct 24 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Mistral Small 3.2 24B Instruct costs less

For input processing, Beam 1.0 ($0.40/1M tokens) is 5.3x more expensive than Mistral Small 3.2 24B Instruct ($0.07/1M tokens).

For output processing, Beam 1.0 ($1.20/1M tokens) is 6.0x more expensive than Mistral Small 3.2 24B Instruct ($0.20/1M tokens).

In conclusion, Beam 1.0 is more expensive than Mistral Small 3.2 24B Instruct.*

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

Lowest available price from all providers
Sat Oct 24 2026 • llm-stats.com
Reflection AI
Beam 1.0
Input tokens$0.40
Output tokens$1.20
Best providerTogether
Mistral AI
Mistral Small 3.2 24B Instruct
Input tokens$0.07
Output tokens$0.20
Best providerDeepinfra
Notice missing or incorrect data?

Model Size

Parameter count comparison

477.7B diff

Beam 1.0 has 477.7B more parameters than Mistral Small 3.2 24B Instruct, making it 2024.2% larger.

Reflection AI
Beam 1.0
501.3Bparameters
Mistral AI
Mistral Small 3.2 24B Instruct
23.6Bparameters
501.3B
Beam 1.0
23.6B
Mistral Small 3.2 24B Instruct

Context Window

Maximum input and output token capacity

Beam 1.0 accepts 1,048,576 input tokens compared to Mistral Small 3.2 24B Instruct's 128,000 tokens. Beam 1.0 can generate longer responses up to 131,072 tokens, while Mistral Small 3.2 24B Instruct is limited to 128,000 tokens.

Reflection AI
Beam 1.0
Input1,048,576 tokens
Output131,072 tokens
Mistral AI
Mistral Small 3.2 24B Instruct
Input128,000 tokens
Output128,000 tokens
Sat Oct 24 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Mistral Small 3.2 24B Instruct supports multimodal inputs, whereas Beam 1.0 does not.

Mistral Small 3.2 24B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

Beam 1.0

Text
Images
Audio
Video

Mistral Small 3.2 24B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

Both models share the same licensing terms, providing consistent usage rights.

Beam 1.0

Apache 2.0

Open weights

Mistral Small 3.2 24B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Beam 1.0 was released on 2026-10-16, while Mistral Small 3.2 24B Instruct was released on 2025-06-20.

Beam 1.0 is 16 months newer than Mistral Small 3.2 24B Instruct.

Beam 1.0

Oct 16, 2026

4 days ago

1.3yr newer
Mistral Small 3.2 24B Instruct

Jun 20, 2025

1.3 years ago

Knowledge Cutoff

When training data ends

Beam 1.0 has a knowledge cutoff of 2026-06-30, while Mistral Small 3.2 24B Instruct has a cutoff of 2023-10-01.

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 Mistral Small 3.2 24B Instruct (2023-10-01).

Beam 1.0

Jun 2026

2.7 yr newer
Mistral Small 3.2 24B Instruct

Oct 2023

Provider Availability

Beam 1.0 is available from Together, Reflection AI. Mistral Small 3.2 24B Instruct is available from DeepInfra.

Beam 1.0

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

Mistral Small 3.2 24B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.07/1MOutput Price:Output: $0.20/1M
* 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 Mistral Small 3.2 24B Instruct side-by-side, then vote on the output you prefer.

Beam 1.0
✓ Preferred
Mistral Small 3.2 24B Instruct
Open in Playground

FAQ

Common questions about Beam 1.0 vs Mistral Small 3.2 24B Instruct.

Which is better, Beam 1.0 or Mistral Small 3.2 24B Instruct?

Beam 1.0 leads the LLM Stats Score 44.6 to 8.0. Beam 1.0 is made by Reflection AI and Mistral Small 3.2 24B Instruct is made by Mistral AI. 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 Mistral Small 3.2 24B Instruct 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%. Mistral Small 3.2 24B Instruct scores DocVQA: 94.9%, AI2D: 92.9%, HumanEval Plus: 92.9%, ChartQA: 87.4%, IF: 84.8%.

Is Beam 1.0 cheaper than Mistral Small 3.2 24B Instruct?

Mistral Small 3.2 24B Instruct is 5.3x cheaper for input tokens. Beam 1.0 costs $0.40/M input and $1.20/M output via together. Mistral Small 3.2 24B Instruct costs $0.07/M input and $0.20/M output via deepinfra.

What are the context window sizes for Beam 1.0 and Mistral Small 3.2 24B Instruct?

Beam 1.0 supports 1.0M tokens and Mistral Small 3.2 24B Instruct supports 128K 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 Mistral Small 3.2 24B Instruct?

Key differences include LLM Stats Score (44.6 vs 8.0), context window (1.0M vs 128K), input pricing ($0.40 vs $0.07/M), multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.

Who makes Beam 1.0 and Mistral Small 3.2 24B Instruct?

Beam 1.0 is developed by Reflection AI and Mistral Small 3.2 24B Instruct is developed by Mistral AI.

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