Hetzner Inference dropped Kimi-K2.7-Code, GLM-5.2-NVFP4 and DeepSeek-V4-Flash-0731 from /v1/models; the 6 suppliers serving them are deregistered (adverts retired on-chain 2026-08-21, containers removed): kimi-code 3f37082166faf2b2220e6476235bae8723af9a3434a6aaf60277366ff1f62bfb kimi-code-chat 3d1b43645c00bdb7b429f29ced798bc4af206c9dc56074e955d84b603b64f50c glm bf3ee48addb32e2b0726066f1806b9d84ad64b86c7d41d379abd4b439c522696 glm-chat b910327023edb6a3f31696b7feaa9448a151c671c2ff303c4c3dd5a07d03c6b5 ds-flash-htz 61dd30deb1cd3d6c3f73792bda46ecea6890735237d8329ade2b8449d298f24e ds-flash-htz-chat 348a278c81a2bf664ea65705a6245df31e81f64c0ffa6e04a59b248fcdae3d9f New qwen38 + qwen38-chat suppliers serve Hetzner's new Qwen3.8-27B (ctx 262144; ping + tools round-trip verified 2026-08-21), reusing the retired kimi-code / kimi-code-chat wallets. Adverts: qwen38 bb8a7078098dc5e60b3f97b040e38f05e6cca662497d4bea471e1dff19c1e1ae#0 qwen38-chat 31e3a6e258ceaa0d1eaabe61fa3fbe3abcbbb400a7b885e05c8dbcdcf4924eda#0
7.0 KiB
Hetzner Inference Supplier Fleet — Setup Runbook
Status: shipped; fleet trimmed 2026-08-21. Hetzner retired
Kimi-K2.7-Code,GLM-5.2-NVFP4, andDeepSeek-V4-Flash-0731from Inference (gone from/v1/models), so the 6 suppliers serving them were deregistered (adverts retired on-chain, containers removed).Qwen3.8-27Bwas added in their place, reusing the retired kimi-code wallets. Configures mainnet supplier nodes that use Hetzner Inference (https://inference.hetzner.com) as their compute backend for bonded inference work commissioned on Vector. Config only — no code changes.
1. What this is
Hetzner Inference is an OpenAI-compatible hosted API. Because the supplier's
upstream client (supplier/src/openai.ts) already speaks plain
POST /v1/chat/completions with a Bearer token, pointing it at Hetzner is
pure configuration: LLM_BACKEND=openai + OPENAI_BASE_URL + the API key.
This is the same pattern as the DeepSeek-direct and OpenRouter suppliers, and
the direct sibling of docs/HUGGINGFACE_ROUTER_SETUP.md.
One supplier per (model × capability) — both the one-off
llm.text.generate.v1 and the multi-turn llm.chat.v1 capability:
| Supplier name | Model (on-chain + API param, verbatim) | Capability | Advert max_output_tokens |
|---|---|---|---|
qwen35b |
Qwen/Qwen3.6-35B-A3B-FP8 |
llm.text.generate.v1 |
262144 |
qwen35b-chat |
Qwen/Qwen3.6-35B-A3B-FP8 |
llm.chat.v1 |
262144 |
qwen38 |
Qwen3.8-27B |
llm.text.generate.v1 |
262144 |
qwen38-chat |
Qwen3.8-27B |
llm.chat.v1 |
262144 |
Deregistered 2026-08-21 (models dropped by Hetzner): kimi-code,
kimi-code-chat (Kimi-K2.7-Code), glm, glm-chat (GLM-5.2-NVFP4),
ds-flash-htz, ds-flash-htz-chat (DeepSeek-V4-Flash-0731). The qwen38
pair reuses the kimi-code / kimi-code-chat wallets; the other four wallets
still hold funds and their env files remain on the host.
Shared advert parameters: price 200000 lovelace (0.2 AP3X) flat per job,
bonds 1000000 lovelace (1 AP3X) both sides, max_processing_ms 300000
for one-off / 1800000 for chat (the session spans the whole conversation).
max_output_tokens is set to the model's context length: no max_tokens is
forwarded upstream (OPENAI_MAX_TOKENS unset), so the advert value only gates
what buyers may request.
Names follow the brand-by-model convention; the retired ds-flash-htz
carried a -htz suffix only because deepseek-flash-* was already taken by
the OpenRouter fleet serving deepseek/deepseek-v4-flash.
2. Prerequisites
- A Hetzner account with Inference access and an API key (usage-based billing to you as the node operator — the flat 0.2 AP3X job price is a business choice, not cost-derived). One key is shared by all suppliers; Hetzner rate limits apply to the aggregate.
- One funded supplier wallet per supplier (50 AP3X each recommended; bonds are 1 AP3X per in-flight job and returned on completion).
- The usual mainnet supplier deploy prerequisites (
deploy/README.md). - DNS: one A record per supplier —
mp-suppliers-<name>.vector.apexfusion.org→91.98.147.172, DNS-only/unproxied. There is NO wildcard for*.vector.apexfusion.org; and because traefik issues certs on-box via Let's Encrypt HTTP-01 (port 80), a proxied/CDN record would break issuance. Certs are issued automatically within ~a minute of the record propagating — no restarts needed.
3. Verify the backend before spending on-chain
The model ids come from GET https://inference.hetzner.com/api/v1/models
(this list changes — Hetzner retires models; re-check before any advert)
and are sent verbatim as the upstream model param (the runtime uses
advert.model). Before posting adverts, smoke-test each model:
curl -sS -X POST https://inference.hetzner.com/api/v1/chat/completions \
-H "Authorization: Bearer $HETZNER_KEY" -H "Content-Type: application/json" \
-d '{"model":"Qwen3.8-27B","messages":[{"role":"user","content":"ping"}]}' \
| jq '.choices[0].message.content'
choices[0].message.content must be a non-empty string with no max_tokens
sent (matches runtime config) — the supplier throws openai_malformed
otherwise and forfeits its 1 AP3X bond per failed job. For chat suppliers also
verify a tools/tool_choice round-trip. The original four models passed
both checks on 2026-08-11; Qwen3.8-27B passed both on 2026-08-21.
4. Per-supplier bring-up (repeat per supplier)
# 1. wallet — prints privateKeyHex, publicKeyHex, pubKeyHash, address
pnpm --filter @marketplace/supplier tx:gen-keypair --network 1
# fund the printed address (50 AP3X recommended), then:
# 2. env file on the mainnet host
cp supplier/.env.hetzner.example /root/agents-marketplace/supplier/.env.<name>
chmod 600 /root/agents-marketplace/supplier/.env.<name>
# fill in: ALL FOUR wallet vars (PRIV_KEY_HEX, ADDRESS, PKH, PUB_KEY_HEX —
# they are NOT derived at boot; missing derived vars ⇒ 403 wrong_supplier),
# OPENAI_API_KEY, and the ADVERT_* values from the table above.
# 3. advert (one-off shown; chat: --capability-id llm.chat.v1 --max-processing-ms 1800000)
pnpm --filter @marketplace/supplier tx:post-advert \
--capability-id llm.text.generate.v1 \
--model 'GLM-5.2-NVFP4' \
--max-output-tokens 512000 \
--max-processing-ms 300000 \
--price-lovelace 200000 \
--endpoint-url https://mp-suppliers-<name>.vector.apexfusion.org
# paste the printed "<txHash>#0" into ADVERT_REF in the env file
# 4. first start is always manual (CD skips compose projects with no running
# containers); subsequent rollouts ride the mainnet CD pipeline
docker compose -f deploy/mainnet/docker-compose.supplier-<name>.yml up -d
# 5. register the wallet for balance alerts
# add {name, address} to wallet-monitor/wallets.json on the host
5. Verification
curl https://mp-suppliers-<name>.vector.apexfusion.org/healthz→{"ok":true};/capabilityshows the right model + pkh.- Indexer: buyer
GET /v1/indexer/supplierslists the new entries withadvert_status: Active,status: free. - Gateway
GET /openai/v1/modelsincludes the four Hetzner model ids. - Watch
docker logs -f marketplace-mainnet-supplier-<name>through the first jobs foropenai_malformed(reasoning-model content-shape risk).
6. Footguns
OPENAI_BASE_URL=https://inference.hetzner.com/api— no/v1; the client appends/v1/chat/completions.- Do not set
OPENAI_REASONING—reasoning:{enabled:false}is an OpenRouter-only param. - The advert
--modelmust match the Hetzner id exactly, including theQwen/prefix onQwen/Qwen3.6-35B-A3B-FP8(slash is fine on-chain; precedentmoonshotai/kimi-k2.6). Kimi-K2.7-CodeandDeepSeek-V4-Flash-0731auto-join the buyer's PDF pool (case-insensitive substring allowlist["kimi","deepseek","gpt"]inbuyer/src/pdf/caps.ts); GLM and Qwen stay out. Deliberate — adjustPDF_MODEL_ALLOWLIST/PDF_MODEL_DENYLISTin the buyer env to change it.OPENAI_TIMEOUT_MSmust stay ≤ the advert'smax_processing_ms.