Beam 1.0 vs Llama 3.2 90B Instruct
Beam 1.0 leads the LLM Stats Score 44.6 to 4.7. Llama 3.2 90B Instruct is 1.7x cheaper per token.
Reflection AI · Meta · Updated for 2026
Which is better?
Beam 1.0 leads the overall LLM Stats Score 44.6 to 4.7, 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, Llama 3.2 90B Instruct is roughly 1.7x 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 Llama 3.2 90B Instruct
- cost matters — it's about 1.7x 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 · 13 for Llama 3.2 90B Instruct
Beam 1.0 outperforms in 1 benchmarks (GPQA), while Llama 3.2 90B Instruct 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 1.1x more expensive than Llama 3.2 90B Instruct ($0.35/1M tokens).
For output processing, Beam 1.0 ($1.20/1M tokens) is 3.0x more expensive than Llama 3.2 90B Instruct ($0.40/1M tokens).
In conclusion, Beam 1.0 is more expensive than Llama 3.2 90B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Beam 1.0 has 411.3B more parameters than Llama 3.2 90B Instruct, making it 457.0% larger.
Context Window
Maximum input and output token capacity
Beam 1.0 accepts 1,048,576 input tokens compared to Llama 3.2 90B Instruct's 128,000 tokens. Beam 1.0 can generate longer responses up to 131,072 tokens, while Llama 3.2 90B Instruct is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Llama 3.2 90B Instruct supports multimodal inputs, whereas Beam 1.0 does not.
Llama 3.2 90B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
Beam 1.0
Llama 3.2 90B Instruct
License
Usage and distribution terms
Beam 1.0 is licensed under Apache 2.0, while Llama 3.2 90B Instruct uses Llama 3.2.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Llama 3.2
Open weights
Release Timeline
When each model was launched
Beam 1.0 was released on 2026-10-16, while Llama 3.2 90B Instruct was released on 2024-09-25.
Beam 1.0 is 25 months newer than Llama 3.2 90B Instruct.
Oct 16, 2026
4 days ago
2.1yr newerSep 25, 2024
2.1 years ago
Knowledge Cutoff
When training data ends
Beam 1.0 has a documented knowledge cutoff of 2026-06-30, while Llama 3.2 90B Instruct'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 3.2 90B Instruct's cutoff date.
Jun 2026
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Provider Availability
Beam 1.0 is available from Together, Reflection AI. Llama 3.2 90B Instruct is available from DeepInfra, Bedrock, Fireworks, Together, Hyperbolic.
Beam 1.0
Llama 3.2 90B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Beam 1.0 and Llama 3.2 90B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Beam 1.0 vs Llama 3.2 90B Instruct.