Beam 1.0 vs GPT OSS 120B High
Beam 1.0 leads the LLM Stats Score 44.6 to 25.0. GPT OSS 120B High is 3.0x cheaper per token.
Reflection AI · OpenAI · Updated for 2026
Which is better?
Beam 1.0 leads the overall LLM Stats Score 44.6 to 25.0, 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, GPT OSS 120B High is roughly 3.0x 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 GPT OSS 120B High
- cost matters — it's about 3.0x 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 · 7 for GPT OSS 120B High
Beam 1.0 outperforms in 2 benchmarks (GPQA, IFBench), while GPT OSS 120B High 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 4.0x more expensive than GPT OSS 120B High ($0.10/1M tokens).
For output processing, Beam 1.0 ($1.20/1M tokens) is 2.4x more expensive than GPT OSS 120B High ($0.50/1M tokens).
In conclusion, Beam 1.0 is more expensive than GPT OSS 120B High.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Beam 1.0 has 384.5B more parameters than GPT OSS 120B High, making it 329.2% larger.
Context Window
Maximum input and output token capacity
Beam 1.0 accepts 1,048,576 input tokens compared to GPT OSS 120B High's 131,072 tokens. Both models can generate responses up to 131,072 tokens.
License
Usage and distribution terms
Both models are licensed under Apache 2.0.
Both models share the same licensing terms, providing consistent usage rights.
Apache 2.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Beam 1.0 was released on 2026-10-16, while GPT OSS 120B High was released on 2025-08-05.
Beam 1.0 is 15 months newer than GPT OSS 120B High.
Oct 16, 2026
6 days ago
1.2yr newerAug 5, 2025
1.2 years ago
Knowledge Cutoff
When training data ends
Beam 1.0 has a documented knowledge cutoff of 2026-06-30, while GPT OSS 120B High'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 GPT OSS 120B High's cutoff date.
Jun 2026
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Provider Availability
Beam 1.0 is available from Together, Reflection AI. GPT OSS 120B High is available from OpenAI, Fireworks.
Beam 1.0
GPT OSS 120B High
Outputs Comparison
Judge for yourself.
Run your own prompts against Beam 1.0 and GPT OSS 120B High side-by-side, then vote on the output you prefer.
FAQ
Common questions about Beam 1.0 vs GPT OSS 120B High.