Updated 2026-10-05
Hermes vs OpenClaw with the Same DeepSeek Model
For a repeatable DeepSeek workflow, inspect how the agent saves procedures, recalls facts and produces files you can check. Hermes and OpenClaw both support this kind of work, but organize their state differently. This guide compares documented behavior and gives you a common task to run; it does not report a measured speed, quality or cost winner.
1. Compare the workflow you will maintain
Start with the state you already depend on. A working collection of skills, memory and channel settings is a reason to test carefully before switching. Our selection advice below follows the documented configuration; it is not a benchmark result.
| Need | Hermes | OpenClaw |
|---|---|---|
| Choose a DeepSeek model | Provider and model picker | DeepSeek onboarding documented by DeepSeek |
| Reuse a procedure | Skills loaded when needed | Skills discovered from workspace and configured roots |
| Carry facts into later sessions | Curated MEMORY.md and USER.md in the profile home | Workspace memory, user profile and dated notes |
| Separate agent state | Named profiles | Agent workspaces and skill scope |
| Keep an existing setup | Check the OpenClaw importer before moving | Keep your configured workspace while testing Hermes separately |
2. Hold the model and inputs constant
Select the same exact DeepSeek model ID through the same provider route on both sides. Match reasoning settings where exposed, and record any settings the agent controls internally. A shared display name alone does not prove that two gateways serve the same model.
Record agent versions, model ID, endpoint, tool permissions and working directories. Disable optional model fallbacks for the experiment where supported, or record every fallback. If one side uses an additional model or paid search service, include that in the result.
Give each agent a separate copy of the same test folder. Begin with clean task history, then run a second phase with intentionally saved memory. Keep prompts and input files identical; compare default agent behavior first before adding agent-specific optimizations.
3. Ask both agents for a verifiable work product
Use the fictional notes in the workflow tutorial linked below. Save them as notes-day1.md in each test folder, then give both agents this prompt. Keeping the task offline removes differences in search results and tool subscriptions from the first comparison.
A passing result covers Atlas, Beacon and Cedar, retains their source IDs, distinguishes a suggested next step from a recorded fact, and invents no owner or deadline. Open the output file yourself. A message saying the file was written is not enough.
Read notes-day1.md using a file tool.
Create brief-day1.md with a table:
Project | Status | Proposed next step | Source.
Cover all projects and keep each source ID.
Use only the notes. Mark missing facts as unknown.
Do not browse, change the input, send, or publish anything.
Reopen the output to verify it, then return its path.4. Test memory after a session boundary
After the first task, ask each agent to save a briefing preference. Start a fresh conversation, supply a new input file and request another brief without repeating that preference. Then correct the preference and repeat. Keep the factual task inputs separate from the remembered format.
Hermes loads a memory snapshot at session start. OpenClaw documents durable workspace files and retrieval tools. These mechanisms explain where to look for evidence; neither mechanism alone establishes better recall.
| Check | Evidence to retain |
|---|---|
| Saved | The memory tool result or the corresponding saved entry |
| Recalled | A fresh session using the saved format without a reminder |
| Corrected | A later fresh session using the replacement preference |
| Scoped | An independent profile or workspace without the test preference |
5. Separate task cost from setup cost
For the task above, record elapsed time, retries, manual corrections, output quality and all billable model calls. Include cached and uncached input at the provider's applicable rates, plus output and auxiliary calls. Use actual usage records; missing usage is unknown, not zero.
Keep model usage, optional tools, hosting and setup time as separate lines. A local installation with no server invoice still needs maintenance. A subscription allowance is not interchangeable with a direct API token price.
| Question | Available evidence |
|---|---|
| How is state organized? | Official documentation linked on this page |
| Which completes this task better? | No comparative execution results collected |
| Which is faster or cheaper? | No timed runs or comparable usage records collected |
agent,version,provider,model_id,run_id,phase,output_file,passed,elapsed_seconds,manual_corrections,retries,model_cost,tool_cost,currency
Hermes,,,,1,fresh,,,,,,,,
OpenClaw,,,,1,fresh,,,,,,,,6. Budget for deployment and migration
OpenClaw's onboarding includes a Gateway, dashboard and service checks. With either self-managed setup, account for process restarts, updates, credentials, permissions and backups before relying on unattended work. Permission settings and sandbox configuration belong in the comparison alongside the model.
Hermes provides a migration preview. Compatible memory, skills and provider settings can be imported, while items such as cron jobs, plugins and some channel bindings need separate attention. Secrets require an explicit migration option. An imported Skill can still depend on tools that need reconfiguration.
hermes claw migrate --dry-run7. Choose from the evidence that matters to you
Try Hermes when a named profile and a small reusable workflow fit how you want to organize the work. Keep OpenClaw in consideration when your existing workspaces, skills and channels already support the task. Run the same brief in both before paying the migration cost.
For a performance claim, repeat the task several times in separate test states and retain every failure. Reverse the order between runs to reduce timing effects. Publish the samples and settings with any conclusion; a single successful example is a case study.
FAQ
Does using the same DeepSeek model make the agents equivalent?
No. Prompts, tool access, memory, retries and context handling can differ. Match the model and task, then record those differences.
Does this guide show Hermes beating OpenClaw?
No. It documents workflow differences and provides a repeatable evaluation. We have not collected comparative runs or measured a winner.
Can I move my OpenClaw setup into Hermes?
Hermes has an importer with a dry-run preview. Review its coverage and conflicts, then verify the resulting setup. Importing files is not proof that every workflow still runs.
Is memory the same as a Skill?
Memory carries facts and preferences. A Skill describes a procedure. Test saved preferences and reusable procedures separately.
Start with one useful file, one fresh-session memory check and one cost record. Choose the agent whose verified result and maintenance requirements fit your work.
Related model comparisons
Continue from this guide into structured DeepSeek-first comparison pages with model tables, routing advice, and pricing context.