OpenClaw vs Hermes Agent: Stars, Downloads & Usage 2026
Stars, tokens, downloads — who actually wins?
Open-source AI agent frameworks are exploding in popularity on GitHub. Two projects at the core of the self-hosted AI systems ecosystem — OpenClaw and Hermes Agent — have pulled so far ahead that the rest of the field is fighting for a distant third place.
Here is the full picture as of May 2026.
The Leaderboard
Star counts are live data fetched from the GitHub API on May 21, 2026. Repos are sorted by current stars, descending.
| Rank | Project | GitHub repo | Language | Stars | Releases last 30 days |
|---|---|---|---|---|---|
| 1 | OpenClaw | openclaw/openclaw |
TypeScript | 373,616 | 62 |
| 2 | Hermes Agent | NousResearch/hermes-agent |
Python | 160,175 | 5 |
| 3 | Nanobot | HKUDS/nanobot |
Python | 42,873 | 2 |
| 4 | AstrBot | AstrBotDevs/AstrBot |
Python | 32,709 | 11 |
| 5 | ZeroClaw | zeroclaw-labs/zeroclaw |
Rust | 31,500 | ≥1 |
| 6 | NanoClaw | nanocoai/nanoclaw |
TypeScript | 29,143 | ≥1 |
| 7 | PicoClaw | sipeed/picoclaw |
Go | 29,121 | 3 |
| 8 | AionUi | iOfficeAI/AionUi |
TypeScript | 26,025 | ≥3 |
| 9 | NemoClaw | NVIDIA/NemoClaw |
TypeScript | 20,571 | 0 |
| 10 | OpenFang | RightNow-AI/openfang |
Rust | 17,599 | ≥5 |
| 11 | LangBot | langbot-app/LangBot |
Python | 16,084 | 1 |
| 12 | memU | NevaMind-AI/memU |
Python | 13,672 | 0 |
| 13 | IronClaw | nearai/ironclaw |
Rust | 12,305 | 4 |
| 14 | Moltworker | cloudflare/moltworker |
TypeScript | 9,899 | 0 |
| 15 | MemOS | MemTensor/MemOS |
Python | 9,246 | ≥2 |
| 16 | ClawWork | HKUDS/ClawWork |
Python | 8,111 | 0 |
| 17 | NullClaw | nullclaw/nullclaw |
Zig | 7,603 | 2 |
| 18 | MimicLaw | memovai/mimiclaw |
C | 5,422 | 0 |
| 19 | Moltis | moltis-org/moltis |
Rust | 2,697 | ≥3 |
| 20 | Clawra | SumeLabs/clawra |
TypeScript | 2,298 | 0 |
OpenClaw: 373k Stars and Still Growing
OpenClaw is a personal AI assistant framework built in TypeScript. It runs entirely on the user’s own device and connects to over 50 messaging platforms — WhatsApp, Telegram, Slack, Discord, and more — through a single unified interface.
The project launched in November 2025 but truly ignited on January 30, 2026, reaching 100,000 stars within 48 hours of its relaunch. By April 2026 it had overtaken React to become the most-starred software repository in GitHub’s history. At the time of this writing it sits at 373,616 stars, 72,000+ forks, and 360 contributors.
The release cadence is extraordinary: 62 tagged releases in the last 30 days puts it in a category of its own in terms of iteration speed. The full arc of how OpenClaw grew from a weekend prototype to GitHub’s most-starred repository — including the economics behind the viral spike and the April 2026 subscription cutoff that reshaped weekly growth — is detailed in the OpenClaw rise and fall timeline.
Hermes Agent: The Challenger
Nous Research’s Hermes Agent markets itself as “the agent that grows with you.” It is a self-improving AI agent built in Python with a built-in learning loop — it creates new skills from experience, searches past conversations for relevant context, and can run on a range of infrastructure options from local hardware to cloud.
Created in July 2025 and now at 160,175 stars, Hermes Agent recently surpassed OpenClaw as the world’s most-used open-source AI agent by daily token processing on OpenRouter — though OpenClaw still leads in cumulative all-time usage. The gap between the two in raw GitHub stars remains large (over 200k), but Hermes Agent’s trajectory is notably steeper.
Mid-field: The 20k–45k Band
The third through eighth positions are all clustered between 26k and 43k stars, making ranking changes here frequent:
- Nanobot (HKUDS, 42,873 ⭐) — Python, lightweight graph-based task orchestration from the HKU Data Science lab.
- AstrBot (AstrBotDevs, 32,709 ⭐) — Python, multi-platform chatbot framework with active release history (11 releases in the last 30 days).
- ZeroClaw (zeroclaw-labs, 31,500 ⭐) — Rust, systems-level agent runtime targeting low-latency deployments.
- NanoClaw (nanocoai, 29,143 ⭐) — TypeScript, recently migrated from
qwibitai/nanoclawtonanocoai/nanoclaw; the rename caused a brief star-count gap in trackers. - PicoClaw (Sipeed, 29,121 ⭐) — Go, embedded-friendly agent framework. Only 22 stars separate it from NanoClaw.
- AionUi (iOfficeAI, 26,025 ⭐) — TypeScript, focuses on agentic UI generation with a visual workflow editor.
Language Breakdown
| Language | Repos in top 20 | Total stars |
|---|---|---|
| Python | 8 | 294,897 |
| TypeScript | 7 | 470,155 |
| Rust | 3 | 51,502 |
| Go | 1 | 29,121 |
| Zig | 1 | 7,603 |
| C | 1 | 5,422 |
TypeScript leads in total star weight — largely because of OpenClaw itself — while Python holds the most individual projects. Rust is carving out a niche in the performance-sensitive tier (ZeroClaw, OpenFang, IronClaw).
Release Velocity vs Star Count
High star counts do not always mean high release velocity. Several top-starred repos (NemoClaw, memU, ClawWork, Clawra, MimicLaw) show zero releases in the last 30 days — they may be in maintenance mode or experiencing slower development cycles.
AstrBot stands out in the mid-field with 11 releases in 30 days, suggesting active feature development. OpenFang (≥5) and Moltis (≥3) are also moving quickly relative to their star counts, which may signal emerging momentum.
Notable Moves Since Last Snapshot
- NanoClaw renamed org from
qwibitaitonanocoai; updated link in the table above. - NemoClaw language corrected to TypeScript (previously listed as JavaScript in older data).
- AionUi gained ~800 stars, moving from 8th to a stronger 8th position.
- MemOS crossed 9,000 stars.
OpenRouter Usage Rankings
GitHub stars measure mindshare; OpenRouter token volume measures actual runtime usage. The two charts tell different stories.
The table below shows the global daily ranking on OpenRouter as of May 21, 2026, filtered to apps and agents that have opted into usage attribution. Counts are daily tokens processed through the platform.
| Rank | App / Agent | Category | Daily tokens |
|---|---|---|---|
| 1 | Hermes Agent | Personal / CLI Agents | 458 B |
| 2 | OpenClaw | Personal / CLI Agents | 173 B |
| 3 | Kilo Code | CLI / IDE Agents | 163 B |
| 4 | Descript | Video Generation | 68.1 B |
| 5 | Claude Code | CLI Agents | 64.1 B |
| 6 | pi | CLI Agents | 58 B |
| 8 | Janitor AI | Roleplay | 28.4 B |
| 9 | ISEKAI ZERO | Game | 26.8 B |
| 10 | CSS AI Pro | — | 25.4 B |
| 11 | Cline | IDE / CLI Agents | 23.5 B |
| 12 | Roo Code | IDE / Cloud Agents | 20.1 B |
| 13 | Lemonade | Programming App | 20 B |
| 14 | Mira | Personal Agents | 15.2 B |
| 15 | VidMuse | Video Generation | 13.3 B |
| 16 | AA-LCR Benchmark | Research | 9.42 B |
| 18 | SillyTavern | Roleplay | 7.84 B |
| 19 | OpenHands | CLI Agents | 7.21 B |
| 20 | Nous Research API | General Chat | 6.63 B |
Gaps in rank numbers (e.g., no 7 or 17) reflect apps without public attribution at the time of retrieval; OpenRouter lists 60 apps in total.
All-time cumulative tokens
The daily leader and the all-time leader have swapped since earlier in the year. As of today Hermes Agent has also overtaken OpenClaw on the all-time chart — a milestone that crossed some time after the May 10 daily flip.
| App / Agent | All-time tokens |
|---|---|
| Hermes Agent | 8.14 T |
| OpenClaw | 7.18 T |
| Kilo Code | 5.21 T |
| Claude Code | 2.6 T |
What the numbers mean
The gap between Hermes Agent (458 B daily) and OpenClaw (173 B) is now wider than it was on May 10, when the flip first happened at 224 B vs 186 B. Hermes has more than doubled its daily volume in 11 days; OpenClaw’s daily volume has declined.
The architecture difference explains a lot of this. OpenClaw is session-native — it resets between runs, which means every session re-pays the full context-stuffing cost. Hermes is a persistent runtime with a three-layer memory system (identity snapshot, SQLite FTS5 session database, self-written procedural skill files). Once a skill is written, repeat tasks cost a fraction of the tokens.
For the coding-agent sub-category specifically, the top five are Hermes Agent, OpenClaw, Kilo Code, Claude Code, and pi. Cline (#11) and Roo Code (#12) round out the open-source coding-agent tier, both crossing 20 B daily tokens.
The driver of Hermes’s May acceleration was the v0.13.0 “Tenacity” release (May 7, 2026): 864 commits, 588 merged PRs, 295 contributors. That release shipped a Kanban-style durable multi-agent task board with heartbeat monitoring and hallucination recovery, plus eight P0 security fixes and Google Chat as the 20th messaging integration.
Community Health
GitHub repository metrics reveal a sharp contrast in project maturity and maintenance style between the two leaders.
| Metric | OpenClaw | Hermes Agent |
|---|---|---|
| Issue close rate | 89.9 % | 37.2 % |
| Contributors | 360 | 400 |
| Forks | 72,696 | 26,000 |
| Releases shipped (total) | 82+ | 14+ |
| Disclosed CVEs (2026 YTD) | 9 in 4 days (March 2026) | 0 |
| Worst CVE severity | CVSS 9.9 | — |
| Exposed public instances | 135,000+ across 82 countries | Not separately tracked |
| Security response (v0.13.0) | — | 8 P0 fixes, default redaction on |
OpenClaw’s 89.9 % issue close rate reflects a well-staffed, responsive maintainer team — the highest of any project in this space. Its release cadence (62 in the last 30 days alone) is exceptional, but that velocity has a cost: roughly a quarter of updates reportedly break response delivery on at least one channel, and the March 2026 CVE cluster (nine issues in four days, the worst at CVSS 9.9) forced emergency patching at scale. Shadowserver confirmed over 135,000 exposed Gateway instances across 82 countries in the same window. The OpenClaw team does publish fixes fast; the problem is that a community of this size patches slowly.
Hermes Agent’s 37.2 % issue close rate is the expected profile for a three-month-old project with a backlog accumulating faster than it can be triaged. The security record so far is clean — zero disclosed agent-specific CVEs as of May 2026 — though that partly reflects fewer eyes on the codebase. The v0.13.0 “Tenacity” release shipped eight P0 fixes proactively, before any public disclosure, which is a good signal of security culture.
Ecosystem Size
Package downloads
| Package | Registry | Weekly downloads |
|---|---|---|
openclaw (main) |
npm | 5,344,931 |
@tencent-weixin/openclaw-weixin |
npm | 230,903 |
@ollama/openclaw-web-search |
npm | 160,221 |
@paperclipai/adapter-openclaw-gateway |
npm | 159,310 |
@larksuite/openclaw-lark |
npm | 115,964 |
hermes-agent (main) |
PyPI | 53,134 |
The raw numbers are not directly comparable — npm counts installs on every npm install (including CI runs), while PyPI counts pip installs. OpenClaw also has a larger ecosystem of third-party adapter packages that each pull in the core. Even so, the order-of-magnitude difference reflects OpenClaw’s deeper penetration of automated pipelines and developer toolchains.
Hermes Agent at 53,000 PyPI downloads per week is not a small number for a three-month-old Python tool. Its install rate has grown roughly linearly with the GitHub star count.
Skills and integrations
| Dimension | OpenClaw | Hermes Agent |
|---|---|---|
| Third-party skill marketplace | ClawHub — 44,000+ skills | None yet (self-generated only) |
| Messaging integrations (official) | 50+ channels | 20 channels |
| Community repositories (GitHub) | Large (untracked by maintainers) | 80+ quality-filtered |
| Skill libraries (community) | Embedded in ClawHub | 17 curated |
| Multi-agent orchestration frameworks | Built-in ACP swarm | 9 third-party |
| External memory providers | Via skills | 8 native |
ClawHub is OpenClaw’s most durable moat: 44,000 community-maintained skills covering integrations, automations, and workflows that would take months to replicate. Hermes’s answer is to generate skills from its own task completions rather than pull them from a marketplace — a fundamentally different philosophy that pays off on deep, repeated tasks but leaves gaps on long-tail integrations. The eight external memory backends Hermes ships natively — Honcho, OpenViking, Mem0, Hindsight, and four more — are compared in detail in Agent Memory Providers Compared.
One security note on ClawHub: in Q1 2026 Koi Security identified 341 malicious entries in the registry, prompting OpenClaw to add a verification layer to the skill submission pipeline. A detailed guide to vetting skills, understanding which are safe to install, and navigating ClawHub’s quality tiers is in OpenClaw Skills Ecosystem and Practical Production Picks.
Community Sentiment
A synthesis of Reddit threads across r/homeautomation, r/selfhosted, and r/MachineLearning (compiled by kilo.ai) breaks down operator preferences as follows:
| Stance | Share |
|---|---|
| Stay on OpenClaw | 35 % |
| Switched fully to Hermes | 30 % |
| Run both side by side | 20 % |
| Withholding judgment on Hermes | 15 % |
The 15 % holding off on Hermes are primarily concerned about what some users characterise as coordinated promotion activity from newly created accounts in Hermes-related threads — a pattern common to fast-growing projects but notable enough that veteran community members flag it.
Top OpenClaw complaints (by upvote volume)
- Release breakage — most-upvoted complaint has 305 votes: “Every single update ships more bugs and problems than before.” An estimated 25 % of releases break response delivery on at least one channel.
- Memory drift — agents forget prior instructions across sessions, requiring users to re-establish context manually.
- Self-host friction — disproportionate time spent on Docker configuration, SSH setup, and YAML tuning relative to actual agent work.
Top Hermes Agent complaints (by frequency)
- Unreliable self-evaluation — the agent occasionally reports task success when the outcome was a partial failure.
- Skill file overwriting — auto-improvement rewrites manually tuned skill files, discarding intentional customisation.
- Integration gaps — ClawHub has a skill for almost everything; Hermes does not, and self-generation takes time to catch up.
The “run both” pattern (20 % of operators) is the most architecturally interesting: OpenClaw as the channel-and-routing layer up front, with Hermes as the deep-specialist backend. Messages arrive via Telegram or Slack, OpenClaw routes them, and the tasks where compounding matters are dispatched to a Hermes instance that has been improving on exactly those workflows for weeks.
Search Interest Trend
Tracking the project growth leaderboard (weekly new GitHub stars, a cleaner signal than raw star count) shows a clear momentum reversal as of May 2026.
| Project | Weekly star growth | Leaderboard position |
|---|---|---|
| Claw-code | +7,000 | #1 |
| Hermes Agent | +3,800 | #3 |
| OpenClaw | +1,700 | #11 |
OpenClaw had a +40,000/week peak in early February 2026 during the post-relaunch explosion. At +1,700/week in May, it is still growing in absolute terms — 373k stars does not happen without weekly adds — but it has settled into a mature project cadence, not a growth sprint.
Hermes Agent at +3,800/week is the fastest-growing agent runtime on the leaderboard right now, despite having less than half of OpenClaw’s cumulative stars. Its growth curve is steeper than OpenClaw’s was at the same age (week 12 post-launch).
The broader search interest trend corroborates the star-growth pattern. Queries for “Hermes Agent” and “hermes-agent install” have been rising consistently since the February launch; “OpenClaw” search volume peaked in late January and has been flat-to-declining since. The intersection point — where Hermes search volume equals OpenClaw’s — has not yet been reached, but the trajectories suggest it will cross sometime in Q3 2026 if current rates hold.
The HN community has also shifted: threads about OpenClaw now centre on security hardening, transport trust (Telegram’s lack of default end-to-end encryption), and maintenance overhead. Threads about Hermes Agent are still mostly “how do I set this up for X” — an earlier-stage energy that reflects a project still in its adoption phase.
