Beam 1.0 Intelligence, Performance and Price Analysis

Reflection released Beam 1.0 on October 16, 2026, a 501B-parameter open-weights reasoning model with 23B active parameters, a 1M-token context window, and an Apache 2.0 license, according to Artificial Analysis. Beam 1.0 scores 30 on the Artificial Analysis Intelligence Index, above the median of 19 for comparable open-weights models, while generating 79M tokens on the index versus a median of 130M. Model weights are published on Hugging Face as Beam-1.0-501B-A23B.

Beam 1.0 Intelligence, Performance & Price Analysis Model summary Speed Beam 1.0 is amongst the leading models in intelligence when comparing to other open weight models of similar size. The model supports text input, outputs text, and has a 1M tokens context window. Beam 1.0 scores 30 on the Artificial Analysis Intelligence Index, placing it well above average among comparable models median: 19 . When evaluating the Intelligence Index, it generated 79M tokens, which is very concise in comparison to the median of 130M. | Reasoning | Yes This page shows the reasoning version of this model. A non-reasoning variant may also exist. | |---|---| | Input modality | Supports: text | | Output modality | Supports: text | | Context window | 1M ~1573 A4 pages of size 12 Arial font | | Total parameters | 501B | | Active parameters | 23B Number of parameters active per token during inference | | License | Apache 2.0 https://www.apache.org/licenses/LICENSE-2.0 | | Model weights | Hugging Face https://huggingface.co/reflection/Beam-1.0-501B-A23B | Metrics are compared against models of the same class: - Non-reasoning models → compared only with other non-reasoning models - Reasoning models → compared across both reasoning and non-reasoning - Open weights models → compared only with other open weights models of the same size class: - Tiny: ≤4B parameters - Small: 4B–40B parameters - Medium: 40B–150B parameters - Large: 150B parameters - Proprietary models → compared across proprietary and open weights models of the same price range, using a blended 3:1 input/output price ratio: - <$0.15 per 1M tokens - $0.15–$1 per 1M tokens - $1 per 1M tokens Speed Intelligence Artificial Analysis Intelligence Index https://artificialanalysis.ai/evaluations/artificial-analysis-intelligence-index Artificial Analysis Intelligence Index by Open Weights / Proprietary Intelligence Index vs. Cost per Task Measures the performance of models on specific capabilities and industries Artificial Analysis Finance & Accounting Index https://artificialanalysis.ai/models/capabilities/finance-and-accounting Evaluations AA-Briefcase v1.1 https://artificialanalysis.ai/evaluations/aa-briefcase Updated Agentic knowledge work, Elo-500 /2000 Knowledge 1 - hallucination rate Agentic SaaS workflows GDPval-AA v2.1 https://artificialanalysis.ai/evaluations/gdpval-aa Updated Agentic real-world work tasks, Elo-500 /2000 Reasoning & knowledge Professional document reasoning, All-pass Agentic coding & terminal use Long context reasoning SciCode https://artificialanalysis.ai/evaluations/scicode Under review Coding CritPt https://artificialanalysis.ai/evaluations/critpt Under review Physics reasoning Agentic scientific research workflows in a terminal Agentic software engineering in open-source repositories Quantitative analysis on spreadsheets & documents Harvey LAB-AA v1.1 https://artificialanalysis.ai/evaluations/harvey-lab-aa Updated Legal agentic work, Hallucination-Gated All-Pass Rate Agentic business operations Kubernetes incident root-cause analysis Medical long context reasoning Visual reasoning AA-Briefcase v1.1Updated AA-Briefcase Elo AA-Omniscience AA-Omniscience Index Openness Index Artificial Analysis Openness Index: Score Intelligence Index Comparisons Intelligence Index vs. Cost per Task Token Use Output Tokens per Intelligence Index Task Cost Cost per Intelligence Index Task Cost to Run Artificial Analysis Intelligence Index Pricing: Cache Hit, Input, and Output Context Window Context Window Model Size Open Weights Models Only Model Size: Total and Active Parameters Frequently Asked Questions Common questions about Beam 1.0 Beam 1.0 was released on October 16, 2026. Beam 1.0 was created by Reflection. Beam 1.0 scores 30 on the Artificial Analysis Intelligence Index, placing it well above average among other open weight models of similar size median: 19 . When evaluated on the Intelligence Index, Beam 1.0 generated 79M output tokens, which is very competitive compared to other open weight models of similar size median: 130M . Yes, Beam 1.0 is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer. Beam 1.0 supports text input. Beam 1.0 supports text output. No, Beam 1.0 does not support image input. It can only process text. No, Beam 1.0 is not multimodal. It only supports text input. Beam 1.0 has a context window of 1.0M tokens. This determines how much text and conversation history the model can process in a single request. Yes, Beam 1.0 is open weights. The model weights are publicly available and can be downloaded for self-hosting. Beam 1.0 has 501 billion parameters 23 billion active . Beam 1.0 is a Mixture of Experts MoE model with 501 billion total parameters, but only 23 billion active parameters are used during inference. Beam 1.0 is released under the Apache 2.0 license. This license allows commercial use. View license https://www.apache.org/licenses/LICENSE-2.0 Beam 1.0 achieves a score of 30 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding. Beam 1.0 is an open weights model that can be self-hosted. View providers https://artificialanalysis.ai/models/reflection-beam/providers Beam 1.0 is an open weights model that can be downloaded and self-hosted. Compare providers https://artificialanalysis.ai/models/reflection-beam/providers