ModelsArchitectures & capability
Reflection's open-weights Beam model is now free for Hermes Agent users on Nous Portal
Reflection's Beam is listed as a free model on Nous Portal, the service behind Hermes Agent. It is a 501B-parameter mixture-of-experts model with 23B active parameters and Apache 2.0 weights. Early tests show it uses few output tokens but hallucinates often.
From the r/AISEOInsider (via last30days) article of October 22, 2026 and cited sources: Beam 1.0 is Reflection's first open-weights model. [4] [6] [9] [11]
SOURCES[4] Introducing Beam — Reflection reflection.ai[6] Unite.ai: Beam open weights under Apache 2.0 unite.ai[9] Nous Portal free tier tracker mvalentsev.github.io
AT Pulse research deskPublished · Updated · 5 min read · AI-assisted analysisAI-assisted, not human-edited. Methodology Corrections Who owns this site
- Original source
- r/AISEOInsider (via last30days) article, independent perspective
- Brief by
- AT Pulse research desk AI-assisted; publisher and contact on the desk page
- When
- October 22, 2026 article published
- Covered
- Oct 22 edition
- Evidence
- 14 sources across 13 sites
- 1Hermes Agent Model Selection: The Free Beam Model Explainedreddit.com
- 2Beam: New FREE Hermes Agent Model!reddit.com
- 3Linked video: Hermes Agent Model Selection: The Free Beam…youtube.com
- 4Introducing Beam — Reflectionreflection.ai
- 5TechCrunch: Reflection debuts Beamtechcrunch.com
- 6Unite.ai: Beam open weights under Apache 2.0unite.ai
QuietHow it’s measured
YouTube video · 1.2K views · 5 likes
Reach blends public engagement (views, likes, comments, shares, stars) from the platforms where the story or its original source lives: YouTube, Hacker News, GitHub, Substack and similar. A video and the article written from its transcript share one score, taken from the video. Platforms with no data are left out rather than counted as zero, and the age of a story never lowers its score.
Beam 1.0 is Reflection's first open-weights model. It is a sparse mixture-of-experts design with 501B total and 23B active parameters, released under Apache 2.0. Nous Portal offers it free with a 262K context window and always-on reasoning. Paid access is also available through OpenRouter and other partners. [4] [6] [9] [11]
Artificial Analysis found Beam to be economical, at about 26k output tokens per task. It also measured a 47% hallucination rate and a 3.0% score on its Terminal-Bench 4.0. Reflection's own figure of 80.1 is on Terminal-Bench 2.1, a different version of the test, so the two scores cannot be compared directly. [4] [8]
Beam is open-weight and free to try, and independent tests show low output-token use and a high hallucination rate. Implication: teams can trial it on agent work cheaply but should add verification steps for fact-heavy tasks.
Executive brief
Reflection's Beam is listed as a free model on Nous Portal, the service behind the Hermes Agent coding agent. The headline number in the linked post is a claim from Reflection: 1 trillion tokens served in 24 hours. Beam is Reflection's first open-weights model. It has 501B total parameters, of which 23B are active for each token, and it is licensed under Apache 2.0. Independent testing so far is mixed. Artificial Analysis rates it as unusually economical with output tokens, but it also measured a 47% hallucination rate and a 3.0% score on its own Terminal-Bench test. The post says the free access lasts "one week". No other source confirms that time limit.
What changed and event timeline
Reflection announces Beam
A 501B sparse mixture-of-experts model with 23B active parameters. Weights were promised "later this month" while red-teaming finished (;).
Weights released
Published on Hugging Face under Apache 2.0 in BF16, FP8 and NVFP4 formats. dates the release Oct 16; says Oct 15.
First independent index
Artificial Analysis scores Beam 30 on its Intelligence Index. That puts it second among US open-weights models and tenth among open-weights models worldwide ().
Free on Nous Portal
A free-tier tracker lists
reflection/beam-1.0-501b-a23b:freewith a 262K context window. It shows no expiry date and no published usage limits ().Video pushes "free for one week"
The creator shows Beam running inside Hermes and repeats Reflection's 1-trillion-token claim (;).
Capabilities and access
- Model: Beam 1.0, 501B total / 23B active parameters. Up to 1M tokens of context (Reflection).
- Where to get it: more than 40 partners, including OpenRouter, AWS, Together and Ollama (Unite.ai).
- In the video: Beam runs as its own Hermes profile and inside the creator's custom workflows (00:32, 01:11).
Read the full section
- Model: Beam 1.0, 501B total / 23B active parameters. Text only. Up to 1M tokens of context (Reflection). The Nous Portal free tier serves 262K context, always reasons, and defaults to medium reasoning effort (tracker).
- Where to get it: more than 40 partners, including OpenRouter, AWS, Together and Ollama (Unite.ai). OpenRouter charges $0.25 per million input tokens and $1 per million output tokens (DIY AI).
- In the video: Beam runs as its own Hermes profile and inside the creator's custom workflows (00:32, 01:11).
Technical analysis for researchers and developers
- Architecture: 52 layers that alternate local and global attention, with fine-grained routed experts and load balancing (Reflection).
- Training: pretrained on 23.8T tokens using 6,144 GB300 GPUs for under four weeks.
- Token budget: during RL the model was penalised for using unnecessary tokens. This is the basis of its efficiency claims (VentureBeat).
Read the full section
- Architecture: 52 layers that alternate local and global attention, with fine-grained routed experts and load balancing (Reflection).
- Training: pretrained on 23.8T tokens using 6,144 GB300 GPUs for under four weeks. Reinforcement learning (RL) then ran on 10.5K GB300s for four weeks, with more than 100M rollouts and 1.3B sandboxes (Reflection).
- Token budget: during RL the model was penalised for using unnecessary tokens. This is the basis of its efficiency claims (VentureBeat).
- Measurement caveat: Reflection's compute estimates leave out prompt prefill (the cost of reading the input) and serving overhead (Reflection). That matters for coding agents, which read long contexts.
- Tooling: serving support from day one in vLLM, SGLang and Transformers, plus a speculative-decoding drafter model. Reflection also open-sourced Mirror, a terminal agent harness. Beam was tested with Hermes and OpenCode (Unite.ai).
Claims and evidence
- Benchmarks reported by Reflection: SWE-Bench Pro 65.5, Terminal-Bench 2.1 80.1, GPQA Diamond 90.5.
- Independent measurement: Artificial Analysis found Beam uses about 26k output tokens per task, roughly half what K2 Horizon uses (Artificial Analysis).
- Usage claim: the 1-trillion-tokens-in-24-hours figure comes only from Reflection (X).
Read the full section
- Benchmarks reported by Reflection: SWE-Bench Pro 65.5, Terminal-Bench 2.1 80.1, GPQA Diamond 90.5. Reflection also says Beam matches GLM-5.2 on reasoning while using 3–4× less inference compute (Reflection). As of Oct 18, no neutral head-to-head comparison with GLM-5.2 had been published (Shattered).
- Independent measurement: Artificial Analysis found Beam uses about 26k output tokens per task, roughly half what K2 Horizon uses (Artificial Analysis).
- Usage claim: the 1-trillion-tokens-in-24-hours figure comes only from Reflection (X).
- Free-week claim: the one-week limit appears only in the video (00:08) and the post. No other source confirms it.
Context and prior work
- Company: Reflection is a Brooklyn lab founded in 2024. It has raised about $4.7B from backers including Nvidia and Sequoia (TechCrunch).
- Pitch: it presents Beam as a US alternative to Chinese open models from DeepSeek, Qwen and Z.ai.
- Nous Portal precedent: the portal has previously offered time-limited free models, such as Step 3.5 Flash for ten days (CO/AI).
Read the full section
- Company: Reflection is a Brooklyn lab founded in 2024. It has raised about $4.7B from backers including Nvidia and Sequoia (TechCrunch).
- Pitch: it presents Beam as a US alternative to Chinese open models from DeepSeek, Qwen and Z.ai. The video makes the same point for users who avoid Chinese models (02:31).
- Nous Portal precedent: the portal has previously offered time-limited free models, such as Step 3.5 Flash for ten days (CO/AI).
- Hermes Agent scale: it processed 1.5T tokens on OpenRouter in August 2026 (Crypto Briefing).
Limitations, safety and contested findings
- Hallucination: Artificial Analysis measured a 47% hallucination rate, even though Beam answered 33% of its knowledge questions correctly (Artificial Analysis).
- Terminal tasks conflict: Reflection reports 80.1 on Terminal-Bench 2.1. Artificial Analysis measured 3.0% on its Terminal-Bench 4.0.
- Rivals: on Terminal-Bench, Beam trails DeepSeek V4.1 Flash (90.6%) and Kimi K3 (85.0%).
Read the full section
- Hallucination: Artificial Analysis measured a 47% hallucination rate, even though Beam answered 33% of its knowledge questions correctly (Artificial Analysis).
- Terminal tasks conflict: Reflection reports 80.1 on Terminal-Bench 2.1. Artificial Analysis measured 3.0% on its Terminal-Bench 4.0. These are different versions of the test, so the scores can't be compared directly.
- Rivals: on Terminal-Bench, Beam trails DeepSeek V4.1 Flash (90.6%) and Kimi K3 (85.0%). Reflection's charts leave out DeepSeek (VentureBeat).
- Safety: results are still pending in a promised technical report (Reflection).
- Creator's own caveat: the video says Beam is "not Opus 5.5 level" and not frontier-level (02:52).
- Model names: the post calls the DeepSeek model "DeepSeek 1017". In the video captions, the later mention of Chinese models comes out as "Step Five". No other source confirms either name.
Business and practitioner implications
- Testing cost: free Portal access and low OpenRouter prices make it cheap to trial Beam on agent workloads.
- Measure per task: fewer output tokens doesn't guarantee a lower bill. Test cost per task on your own workloads, including prefill (VentureBeat).
- Facts-heavy work: the 47% hallucination rate argues for retrieval grounding or verification steps on factual tasks.
Read the full section
- Testing cost: free Portal access and low OpenRouter prices make it cheap to trial Beam on agent workloads.
- Measure per task: fewer output tokens doesn't guarantee a lower bill. Test cost per task on your own workloads, including prefill (VentureBeat).
- Facts-heavy work: the 47% hallucination rate argues for retrieval grounding or verification steps on factual tasks.
- Self-hosting: Apache 2.0 weights plus Dell/HPE on-premises options suit sovereign or regulated deployments (Unite.ai).
- The video's main point: easy model switching in Hermes matters more than any single free model. Its memory "vault" lets a new model start with existing context (01:46).
- Commercial interest: the video promotes a paid community (03:02).
The source trail.
Sources (14)
Hermes Agent Model Selection: The Free Beam Model Explained
Feed excerpt only. A transcript of the video linked from this page is supplied (linked video auto captions; https://www.youtube.com/watch?v=F_g5rq8LeN8); automatic text may contain errors.
reddit.comBeam: New FREE Hermes Agent Model!
Related coverage; assess separately
reddit.comLinked video: Hermes Agent Model Selection: The Free Beam Model Explained
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