Beam 1.0 vs Llama 4 Scout
Beam 1.0 leads the LLM Stats Score 44.6 to 7.3. Llama 4 Scout is 4.4x cheaper per token.
Reflection AI · Meta · Updated for 2026
Which is better?
Beam 1.0 leads the overall LLM Stats Score 44.6 to 7.3, 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, Llama 4 Scout is roughly 4.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Llama 4 Scout also accepts a larger context window (10,000,000 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 coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you want the most recent training data — it shipped Oct 2026
Choose Llama 4 Scout
- cost matters — it's about 4.4x cheaper per token
- you process long inputs — it offers a 10,000,000 token context window
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 Llama 4 Scout
Beam 1.0 outperforms in 2 benchmarks (GPQA, LiveCodeBench), while Llama 4 Scout 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 5.0x more expensive than Llama 4 Scout ($0.08/1M tokens).
For output processing, Beam 1.0 ($1.20/1M tokens) is 4.0x more expensive than Llama 4 Scout ($0.30/1M tokens).
In conclusion, Beam 1.0 is more expensive than Llama 4 Scout.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Beam 1.0 has 392.3B more parameters than Llama 4 Scout, making it 359.9% larger.
Context Window
Maximum input and output token capacity
Llama 4 Scout accepts 10,000,000 input tokens compared to Beam 1.0's 1,048,576 tokens. Llama 4 Scout can generate longer responses up to 10,000,000 tokens, while Beam 1.0 is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Llama 4 Scout supports multimodal inputs, whereas Beam 1.0 does not.
Llama 4 Scout can handle both text and other forms of data like images, making it suitable for multimodal applications.
Beam 1.0
Llama 4 Scout
License
Usage and distribution terms
Beam 1.0 is licensed under Apache 2.0, while Llama 4 Scout uses Llama 4 Community License Agreement.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Llama 4 Community License Agreement
Open weights
Release Timeline
When each model was launched
Beam 1.0 was released on 2026-10-16, while Llama 4 Scout was released on 2025-04-05.
Beam 1.0 is 19 months newer than Llama 4 Scout.
Oct 16, 2026
4 days ago
1.5yr newerApr 5, 2025
1.5 years ago
Knowledge Cutoff
When training data ends
Beam 1.0 has a documented knowledge cutoff of 2026-06-30, while Llama 4 Scout'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 Llama 4 Scout's cutoff date.
Jun 2026
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Provider Availability
Beam 1.0 is available from Together, Reflection AI. Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together.
Beam 1.0
Llama 4 Scout
Outputs Comparison
Judge for yourself.
Run your own prompts against Beam 1.0 and Llama 4 Scout side-by-side, then vote on the output you prefer.
FAQ
Common questions about Beam 1.0 vs Llama 4 Scout.