Reflection AI Published Beam Coding Model Specifications
The 501-billion parameter model utilizes a mixture-of-experts architecture to enhance software engineering tasks.
Updated on Oct. 6, 2026 in Artificial Intelligence
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Reflection AI has developed Beam, an open-weight coding model with 501 billion parameters. The company plans to release the model weights under an Apache 2.0 license later this month.
Why it matters
Beam marks a significant entry in the open-weight coding model race, employing a mixture-of-experts approach to handle complex programming benchmarks. It offers developers a new large-scale resource for software engineering tasks.
Beam features 501 billion total parameters, with 23 billion active parameters per token in a mixture-of-experts design. The model achieved scores of 80.1 on Terminal Bench v2.1 and 44.4 on DeepSWE v1.1.
The players
Reflection AI
An artificial intelligence research entity focused on developing large-scale coding models and reinforcement learning training methodologies.
NVIDIA
A leading hardware manufacturer providing the high-performance GPU infrastructure required for training massive AI models.
The details
Beam utilizes a mixture-of-experts architecture—a design where only a subset of the total network parameters is activated for each input—to optimize performance. The model underwent reinforcement learning across 1.3 billion sandboxes, generating over 100 million attempts during a four-week training phase on 10,500 NVIDIA GB300 GPUs. Safety alignment was achieved by distilling a separate safety model into the final architecture.
Timeline
October 2026: Reflection AI plans to release the Beam model weights.
The Tech Race
Beam enters a competitive field where open-weight models are increasingly challenging closed-source proprietary systems. Its performance on Terminal Bench and DeepSWE benchmarks establishes its position within the current landscape of specialized coding AI.
Developers and researchers can expect to access the Beam model weights under an Apache 2.0 license by the end of October 2026. The release will also include a technical report and the company’s internal safety tests for community review.
The takeaway
Reflection AI’s use of 10,500 GPUs for a four-week training run highlights the massive compute resources currently required to push coding model benchmarks. Watch for the official Apache 2.0 repository release later this month to evaluate the model's performance in real-world environments.
Further reading
For more on the latest research in the field, explore Artificial Intelligence.
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