ModelsArchitectures & capability
StepFun's Step 5 Preview, a 600B-parameter open-weight agent model, comes to Nous Research's Hermes Agent
StepFun's Step 5 Preview is a sparse mixture-of-experts model with 600B total parameters, 27B active per token and a 1M-token context. It now runs in Hermes Agent. Its free access was a one-week Nous Portal promotion in early October.
From the r/AISEOInsider (via last30days) article of October 25, 2026 and cited sources: Step 5 Preview uses a sparse mixture-of-experts design with 600B total parameters and 27B active per token. [9] [10] [11] [12]
SOURCES[9] StepFun on X: open weights x.com[10] MarkTechPost: open weights marktechpost.com[11] NVIDIA AI on X x.com
AT Pulse research deskPublished · Updated · 5 min read · AI-assisted analysisAI-assisted, not human-edited. Methodology Corrections Who owns this site
- What happened
- Step 5 Preview uses a sparse mixture-of-experts design with 600B total parameters and 27B active per token. [9] [10] [11] [12] [14]
- 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 25, 2026 article published
- Covered
- Oct 25 edition
- Evidence
- 15 sources across 11 sites
- 1Step 5 Preview Free in Hermes: Why It's My New Agent Modelreddit.com
- 2Hermes Agent + Step 5 Is the BEST FREE AI Combo?!reddit.com
- 3Linked video: Step 5 Preview Free in Hermes: Why It's My…youtube.com
- 4StepFun on X: free week via Nous Portalx.com
- 5Hermes-AI: Nous offers Step 5 free for a weekhermes-ai.net
- 6Julian Goldie: Hermes Agent Step 5 setupjuliangoldie.com
RisingHow it’s measured
YouTube video · 1.4K views · 14 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.
Step 5 Preview uses a sparse mixture-of-experts design with 600B total parameters and 27B active per token. It has a 1M-token context window, which interleaved sliding-window and sparse full attention keep affordable. BF16 and FP8 weights are public, and NVIDIA released an NVFP4 checkpoint. [9] [10] [11] [12] [14]
Free use in Hermes was a one-week Nous Portal promotion that started around 8–9 October. Commentary from 25 October still calls the model free. Teams should plan around the paid API rates of $1.00 per million input tokens and $2.70 per million output tokens. [3] [4] [5] [6] [8]
Artificial Analysis scored the model 44 on its Intelligence Index, fourth of 121 comparable open-weight models, at about 229 output tokens per second. It also found the model wordy and priced above its peers. The agentic coding scores, such as 67.7 on DeepSWE v1.1, are vendor-reported. [7] [12] [13]
an independent aggregate ranking puts it near the top of open-weight models, with fast output. Implication: it could serve as a low-cost default agent model or be hosted on-premises, if teams test it on their own tasks first.
Executive brief
StepFun described free access to Step 5 Preview in Hermes Agent as a one-week promotion through Nous Portal, starting around 8–9 October 2026 (StepFun on X; Hermes-AI news). The Reddit commentary, dated 25 October, still calls it free. Its author's own setup guide says no official source confirmed a free window (Julian Goldie guide). The model itself is real and substantial: a 600B-parameter sparse mixture-of-experts (MoE) model with 27B parameters active per token, a 1M-token context window and open weights. Independent results so far are limited to Artificial Analysis's aggregate scoring.
What changed and event timeline
StepFun launches Step 5 Preview
StepFun released its flagship agentic model through its API at $1.00 per million input tokens and $2.70 per million output tokens. All headline benchmarks were vendor-reported (;).
8–9 Oct 2026: Free week on Nous Portal
StepFun said the model was free for one week through Nous Research's portal and invited Hermes Agent users to try it (;).
Early independent review
The review called the launch "honestly positioned." It warned that the benchmarks were self-reported, that StepCodeBench is StepFun's own test, and that outputs were verbose ().
15–16 Oct 2026: Open weights released
BF16 and FP8 weights went up on Hugging Face and ModelScope, with a technical blog post. NVIDIA published an NVFP4 checkpoint (;;).
Commentary pitches "free" Step 5 in Hermes
A Reddit post and YouTube video present the model as a free, fast default for everyday agent work. Both promote a paid community (;).
Capabilities and access
- Model:
step-5-preview. - Access routes:
- StepFun API:
hermes chat --provider stepfun --model step-5-preview
Read the full section
- Model:
step-5-preview. It uses sparse MoE with 600B total and 27B active parameters, has a 1M-token context and supports configurable reasoning effort, parallel tool calls and strict JSON-schema output (Artificial Analysis; StepFun on X). - Access routes:
- StepFun API:
hermes chat --provider stepfun --model step-5-preview - Nous Portal (Goldie guide)
- Self-hosting from the open weights
- License: StepFun Model License 1.0 (Artificial Analysis). The Hugging Face card summary names a "StepFun Community License" that allows commercial use but bans weapons, surveillance and malicious cyber uses (Hugging Face).
Technical analysis for researchers and developers
- Architecture: 92 narrow, deep transformer blocks. Gated sliding-window attention and full attention are interleaved 3:1. This is how the model keeps 1M-token context affordable.
- Self-hosting: By arithmetic, BF16 weights alone come to about 1.2 TB and FP8 to about 600 GB. That means multi-GPU nodes.
- Evaluation settings: The Hugging Face card lists the harness and sampling settings, for example SWE-agent at temperature 1.0 and top_p 0.95 for DeepSWE.
Read the full section
- Architecture: 92 narrow, deep transformer blocks. Gated sliding-window attention and full attention are interleaved 3:1. "Sparse GQA" (grouped-query attention) lets each query in the full-attention layers select 4,096 history tokens (Pandaily). This is how the model keeps 1M-token context affordable.
- Self-hosting: By arithmetic, BF16 weights alone come to about 1.2 TB and FP8 to about 600 GB. That means multi-GPU nodes. Serving works with vLLM (
--trust-remote-code) or SGLang (Hugging Face). - Evaluation settings: The Hugging Face card lists the harness and sampling settings, for example SWE-agent at temperature 1.0 and top_p 0.95 for DeepSWE. This allows rerunning the tests, but the reviewed sources contain no third-party replication.
Claims and evidence
- Agentic coding benchmarks (vendor-reported): DeepSWE v1.1 67.7, Terminal-Bench 4 33.3, CyberGym 84.7 (Hugging Face; AIToolsReview).
- Independent aggregate score: 44 on the Artificial Analysis Intelligence Index, ranked #4 of 121 comparable open-weight models.
- "Lightweight, not frontier": The video's own framing (video). It is consistent with a 27B-active design, but the video shows no timing data.
Read the full section
- Agentic coding benchmarks (vendor-reported): DeepSWE v1.1 67.7, Terminal-Bench 4 33.3, CyberGym 84.7 (Hugging Face; AIToolsReview).
- Independent aggregate score: 44 on the Artificial Analysis Intelligence Index, ranked #4 of 121 comparable open-weight models. Measured speed was about 229 output tokens per second, with 1.15 s to the first token (Artificial Analysis).
- "Lightweight, not frontier": The video's own framing (video). It is consistent with a 27B-active design, but the video shows no timing data.
- "In GPT-6 Luna territory on agent benchmarks": Aggregated secondhand from AlphaSignal (Hermes-AI news). No primary evaluation is cited.
- Search visibility: The video says content written with Claude and Hermes appears in Google AI answers (video). This is an anecdote, and the video does not attribute the content to Step 5.
Context and prior work
- Hermes Agent: Nous Research's MIT-licensed agent framework.
- Workflows shown in the video:
- The
/learncommand turns a document into a skill file (video).
Read the full section
- Hermes Agent: Nous Research's MIT-licensed agent framework. It auto-generates skills, keeps memory across sessions and routes to more than 200 models through Nous Portal, whose free tier offers only free models (Hermes Agent).
- Workflows shown in the video:
- The
/learncommand turns a document into a skill file (video). - Built-in web search uses a Perplexity model (video).
- These are Hermes features, not Step 5 capabilities.
- The model's positioning: StepFun aims Step 5 at long-horizon agentic work. NVIDIA cites agent tasks lasting up to 24 hours (NVIDIA AI on X).
Limitations, safety and contested findings
- Video input is disputed. Artificial Analysis and the author's own guide list text and image only (Artificial Analysis; Goldie guide).
- Cache-hit pricing differs between sources: $0.10 per million tokens (Goldie guide) versus $0.05 (AIToolsReview).
- Verbosity: The model used 160M output tokens on the Artificial Analysis index, against a 140M median, and its price ranks higher than comparable open-weight models (Artificial Analysis).
Read the full section
- Video input is disputed. The video says the model accepts video (video), and the Hugging Face card summary lists video input. Artificial Analysis and the author's own guide list text and image only (Artificial Analysis; Goldie guide).
- Cache-hit pricing differs between sources: $0.10 per million tokens (Goldie guide) versus $0.05 (AIToolsReview).
- Verbosity: The model used 160M output tokens on the Artificial Analysis index, against a 140M median, and its price ranks higher than comparable open-weight models (Artificial Analysis).
- Commercial motive: The video repeatedly pitches a paid community (video).
Business and practitioner implications
- StepFun described the window as one week.
- Routing: The video's best idea is cheap-by-default routing, with a switch to stronger models for heavy tasks (video).
- Open weights make on-prem agent deployment possible for teams that can host a model of this size, subject to the license's restrictions.
Read the full section
- Don't plan around "free." StepFun described the window as one week. Check current prices in the Hermes model picker, and budget at $1.00 / $2.70 per million input/output tokens (Goldie guide).
- Routing: The video's best idea is cheap-by-default routing, with a switch to stronger models for heavy tasks (video).
- Open weights make on-prem agent deployment possible for teams that can host a model of this size, subject to the license's restrictions.
- Validate first. Test on your own agent tasks before switching. Apart from Artificial Analysis's aggregate scoring, the performance evidence is vendor-reported.
The source trail.
Sources (15)
Step 5 Preview Free in Hermes: Why It's My New Agent Model
Feed excerpt only. A transcript of the video linked from this page is supplied (linked video auto captions; https://www.youtube.com/watch?v=AQAW0Y0LDfU); automatic text may contain errors.
reddit.comHermes Agent + Step 5 Is the BEST FREE AI Combo?!
Related coverage; assess separately
reddit.comLinked video: Step 5 Preview Free in Hermes: Why It's My New Agent Model
linked video auto captions
www.youtube.com