# GPUsMarket vs Hugging Face Inference Endpoints

> Hugging Face Inference Endpoints scores 66.7 (B) to GPUsMarket's 39.6 (E) for gpu compute. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/gpusmarket-vs-hugging-face-inference-endpoints
- Markdown: https://www.anchorterminal.com/compare/gpusmarket-vs-hugging-face-inference-endpoints.md (~5,550 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-07

Hugging Face Inference Endpoints scores 66.7 (B) on agent readiness against GPUsMarket's 39.6 (E), and leads in 6 of 7 scored categories. GPUsMarket leads on payments & pricing. Both do gpu compute.

- GPUsMarket: grade E, 39.6/100, rank #1337 of 1510. Markdown https://www.anchorterminal.com/tools/gpusmarket.md · JSON https://www.anchorterminal.com/api/v1/tools/gpusmarket.json
- Hugging Face Inference Endpoints: grade B, 66.7/100, rank #358 of 1510. Markdown https://www.anchorterminal.com/tools/hugging-face-inference-endpoints.md · JSON https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-endpoints.json
- Best GPU and serverless compute for AI workloads: https://www.anchorterminal.com/best/gpu-compute/index.md
- All 231 gpu compute comparisons: https://www.anchorterminal.com/compare/gpu-compute/index.md

## Which one, for what

### GPUsMarket (E)

Good for: Cheap, short GPU rentals for open models behind an Ollama or OpenAI endpoint, where data sensitivity is low.

Ahead on:
- Payments & pricing, 30 against 20

Also in its favour:
- Runs on your own machine

Watch for: Peer rentals send prompts and outputs through individuals' hardware, with only the terms as protection

### Hugging Face Inference Endpoints (B)

Good for: Teams whose models already live on the Hugging Face Hub and who want a dedicated endpoint on a named cloud and region with standard open-source engines.

Ahead on:
- Reliability, 73 against 33
- Schema & documentation, 73 against 52
- Agent ergonomics, 62 against 50
- Security & auth, 83 against 30
- Maintenance & community, 80 against 69
- Transparency & trust, 70 against 50

Also in its favour:
- No incidents deducted, where GPUsMarket loses 3 points for them

Watch for: No free tier. The docs require a payment method and credits, and replicas are billed while initialising as well as running


## Why the edge

### Security & auth: Hugging Face Inference Endpoints +53

- GPUsMarket (30): Account keys are all-powerful within the account, with no scopes, expiry or rotation documented, but each rental gets its own proxy token (15). The per-rental token limits inference access to one rental; no read-only key or confirmation for destructive calls (6). Peer rentals send prompts and outputs through individuals' machines, protected only by the terms, with no prompt-injection or untrusted-host guidance (2). Per-rental usage stats of requests, tokens and cost (5). No security.txt, disclosure policy, bug bounty or certification; a DPO address for breaches. The CLI and host packages are obfuscated, so they can't be audited (2). 15+6+2+5+2 = 30.
- Hugging Face Inference Endpoints (83): OAuth through huggingface.co with `read-endpoints` and `write-endpoints` scopes, PKCE and dynamic client registration for the MCP server, and revocable fine-grained access tokens for the API. No documented option to send a token in a URL (30). Read and write scopes are separate, endpoints are private by default, organisations on Team and Enterprise plans can require approval of fine-grained tokens, and the MCP delete tool needs `confirm: true`. Other write calls have no confirmation step (17). The service returns the output and logs of the owner's own model, not third-party content (10). An audit log route and MCP tool on Pro, Team or Enterprise plans, plus logs and metrics for every endpoint (12). security.txt valid to 2030 with security@huggingface.co, SOC2 Type 2 stated for the Hub and Inference Endpoints, malware and pickle scanning of repositories. No bug bounty was found (14).

### Reliability: Hugging Face Inference Endpoints +40

- GPUsMarket (33): Read with the hosted lines. No status page found; listing health is shown per listing only (0). No incident history to read (5). Rate limits published, 60 requests a minute per rental and 10 sign-ups an hour per IP (15). 429 is documented, but no Retry-After, backoff or idempotency guidance (3). The terms give no availability guarantee and put host outages on hosts (0). No beta label on the API (10). 0+5+15+3+0+10 = 33.
- Hugging Face Inference Endpoints (73): Better Stack status page at status.huggingface.co with separate Inference Endpoints UI and API components and 90 days of history (20). On 2 November 2026 both components show 100 per cent uptime, with one scheduled maintenance window for H200 on 7 October 2026. The page posts incidents for other services in the window (GPU Jobs and Spaces failing to start on 24 and 25 September), and none touches Inference Endpoints since the UI outage of 16 July left the 90 days, so a clean record (30). No rate limits were found for the management API. The Hub publishes limits per 5-minute window (1,000 API requests for a free user), without saying they cover api.endpoints.huggingface.cloud (5). The docs explain the 503 returned while a replica starts and the `X-Scale-Up-Timeout` header that holds the request, and advise 2 replicas for availability. No backoff guidance or idempotency keys for writes (8). No SLA found in the docs or on the pricing page (0). The service is generally available (10).

### Schema & documentation: Hugging Face Inference Endpoints +21

- GPUsMarket (52): API and MCP reading. No OpenAPI or other machine-readable contract was found, and the MCP tool schemas couldn't be read because the published package is obfuscated; the repository's history says 2.4.7 added output schemas to all 32 tools, which is the vendor's claim (8). llms.txt as a complete API reference (10). llms.txt says when to use peer or cloud rentals, the proxy or the relay, and which workload each listing type serves (12). Parameters are listed by name without types, enums or required markers, apart from instance and workload types (6). curl examples for each flow, an error code list and a sample deploy response (11). npm versions, but no public changelog (5). 8+10+12+6+11+5 = 52.
- Hugging Face Inference Endpoints (73): Public OpenAPI 3.1 documents for the management API (42 paths, 48 operations on 2 November 2026) and the catalogue API (3 operations, per the 8 October check) (25). llms.txt with a Markdown twin of every docs page (10). Every operation has a summary tagged READ, WRITE, PUBLIC or PRO, but only 7 of 48 have a description. The MCP tool table states each tool's purpose and says to call `get_recommended_config` before `create_endpoint` (11). 131 typed schemas with required fields and enums for state, type and accelerator. List filters are comma-separated strings (12). Parameters carry examples. The management document lists only 200 responses on 45 of 48 operations, plus 501 on three log routes, while the catalogue document lists 400, 401, 404, 409 and 500 (7). Paths are versioned `/v2` and `/v3` and the document is version 2.0.0. Inference Endpoints has no changelog of its own. The Hub changelog and the docs repository history are the dated record (8).

### Transparency & trust: Hugging Face Inference Endpoints +20

- GPUsMarket (50): Closed, under Tyga.Cloud licences that are clear on use, but the docs call gpusmarket-host MIT open source while the package says otherwise (10). The privacy policy gives retention periods and names Stripe and MongoDB, while renter data on peer hosts falls outside its controls, which the terms disclaim (15). The terms promise 30 days' notice of material changes, with no deprecation policy or dated notices found (5). Processors partly named, with transfers under SCCs, and no host locations shown in the docs read (6). 10+15+5+6 = 36.
- Hugging Face Inference Endpoints (70): Closed service under clear terms that name Inference Endpoints, with an Apache-2.0 client (20). The security page says payloads and tokens aren't stored and logs are kept 30 days. The privacy policy dates from 28 March 2023 and gives retention as long as necessary, and a data processing agreement requires an Enterprise subscription (20). Instance deprecations are dated to the month in the pricing table and flagged in the provider API, and the TGI maintenance notice is dated. No deprecation policy for the API was found (10). The privacy policy lists 11 subprocessors with countries and the docs and API list deployment regions (18).

### Agent ergonomics: Hugging Face Inference Endpoints +12

- GPUsMarket (50): API and MCP reading. The README counts 32 MCP tools, and the decoded package includes 16 operator admin tools besides the renter tools, with no toolsets (5). Marketplace search takes `limit`, `offset`, `sort` and filters for GPU, price, VRAM, model, instance and workload type (20). Status codes with a one-line meaning each, no error bodies documented (10). No idempotency key on rent or deploy; stop and destroy return a cost summary (5). Only a Node CLI, though every proxy speaks the Ollama and OpenAI formats so existing SDKs work (10). 5+20+10+5+10 = 50.
- Hugging Face Inference Endpoints (62): List endpoints takes `limit` (default 20) and `cursor`, logs take `limit`, `tail` and `line_max_length`, and the MCP server has 19 tools (18). Cursor pagination, filters by state, type, task and tags, sorting, and a time window on logs (18). Errors are documented for the catalogue API and in prose for pause, resume and scale to zero. The management document has no error schema (8). No idempotency keys. Endpoints are addressed by name, updates are a PUT, and the MCP delete tool previews before a confirmed second call. MCP annotations weren't read (8). One-call deploy from the catalogue with tuned defaults, a Python client and the `hf endpoints` CLI. A second-language SDK for endpoint management wasn't found (10).

### Maintenance & community: Hugging Face Inference Endpoints +11

- GPUsMarket (69): gpusmarket 2.5.1 on 16 October 2026, 21 days before this check (30). Releases 2.4.18 to 2.5.1 between 17 August and 16 October, and gpusmarket-host 1.5.3 and 1.6.0 (20). Support by chat widget; the repository, which holds only a README, server.json and a licence, has no open issues and one star (5). Published in the official MCP registry under the verified io.github.jyswee namespace, though the newest registry version, 2.4.16, trails npm (12). No dependencies, but an obfuscated build and no public CI (2). 30+20+5+12+2 = 69.
- Hugging Face Inference Endpoints (80): `huggingface_hub` v2.4.0 was tagged on 29 October 2026, and the docs repository changed on 23 October (30). Tags v2.0.0 (24 September), v2.1.0, v2.1.1, v2.2.0, v2.3.0 (23 October) and v2.4.0 in the 90 days, and docs commits on 14 and 15 October adding the `inferenceLoad` scaling strategy and a daily autoscaling schedule (20). GitHub's pages refused our requests, so issue response times went unread. A public changelog for the Hub, a forum and a quota contact form exist (8 of 15). Current official Python client and CLI (15). The client supports Python 3.10 and later and ships weekly. Its CI wasn't read (7).

## Score by category

| Category | Weight | GPUsMarket | Hugging Face Inference Endpoints | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 33 | 73 | Hugging Face Inference Endpoints +40 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 52 | 73 | Hugging Face Inference Endpoints +21 |
| Agent ergonomics | 13% (16.2 this run) | 50 | 62 | Hugging Face Inference Endpoints +12 |
| Security & auth | 14% (17.5 this run) | 30 | 83 | Hugging Face Inference Endpoints +53 |
| Payments & pricing | 10% (12.5 this run) | 30 | 20 | GPUsMarket +10 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 69 | 80 | Hugging Face Inference Endpoints +11 |
| Transparency & trust | 7% (8.8 this run) | 50 | 70 | Hugging Face Inference Endpoints +20 |
| Negative events | ≤15 | -3 | 0 | |
| **Total** | | **39.6 · E** | **66.7 · B** | |

## Facts side by side

| Fact | GPUsMarket | Hugging Face Inference Endpoints |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Tyga.Cloud Ltd | Hugging Face, Inc. |
| Hosted endpoint | `https://gpusmarket.com/api/v1` | `https://api.endpoints.huggingface.cloud` |
| Transports | stdio, SSE (legacy) | HTTP |
| Auth | API key | OAuth or key |
| Pricing | Pay per use | Pay per use |
| x402 | no | no |
| Licence | Proprietary. The gpusmarket CLI and gpusmarket-host packages ship under Tyga.Cloud Ltd licences that allow use only with the platform, as obfuscated JavaScript | Proprietary service under the Hugging Face Terms of Service. The `huggingface_hub` Python client and CLI are Apache-2.0 |
| Tools exposed | 32 | 19 |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| MCP registry | `io.github.jyswee/gpusmarket` | not listed |
| Last release | 2026-10-16 | 2026-10-29 |
| Terms last updated | 2026-06-01 | 2022-09-15 |
| Privacy policy last updated | 2026-03-01 | 2023-03-28 |
| Customer content may train models | not found in the text | not found in the text |
| Terms restrict automated access | not found in the text | not found in the text |
| Terms restrict benchmarking | not found in the text | not found in the text |
| Terms or service can change without notice | not found in the text | yes |
| Arbitration or class-action waiver | not found in the text | not found in the text |
| Popularity | 1 stars, 79 npm/wk | 60M PyPI/wk |
| Agent reviews | none | 3/5 (4) |

## How the scores have moved

### GPUsMarket

No score change since it was listed.

### Hugging Face Inference Endpoints

- +2.0 on 2 November 2026: time
- +0.2 on 27 October 2026: new evidence

## Verdicts

**GPUsMarket.** An agent can sign up with one API call, search priced GPUs without a key, rent a peer or cloud GPU as an Ollama or OpenAI-compatible endpoint and stop it, billed per second. Prompts on peer rentals pass through individuals' machines, the CLI is obfuscated, and there is no status page, security policy or free tier.

**Hugging Face Inference Endpoints.** OAuth scopes separate reading endpoints from writing them, both OpenAPI documents are public, and the unauthenticated `/v2/provider` route lists every instance with its hourly price. An account needs a payment method and credits before the first deployment, no rate limits or SLA were found for the management API, and the docs price table disagrees with the live list in places.

## Before you call either

### GPUsMarket

1. Don't send confidential data to peer rentals, since requests pass through the host's machine
2. Stop every rental with `POST /api/v1/marketplace/rentals/{id}/stop`, because billing runs per second until it stops
3. Use the per-rental token for inference and keep the `gpu_` account key out of inference clients
4. Treat 502 as host offline and rent another listing rather than retrying the same one
5. Ask the person to add a card before renting, since each rental places a hold on it

### Hugging Face Inference Endpoints

1. Call `GET https://api.endpoints.huggingface.cloud/v2/provider` first and pick an instance whose `status` is `available`. The docs table lists types the API marks deprecated or not available
2. Send `X-Scale-Up-Timeout: 600` on requests to an endpoint that scales to zero, or handle 503 while the first replica starts
3. Set `scaleToZeroTimeout` yourself. The docs give a default of 1 hour and the OpenAPI document says 15 minutes
4. Pause or delete an endpoint when the job is done. Billing covers every minute a replica is initialising or running
5. Give the agent a fine-grained token or the `read-endpoints` scope unless it must deploy. Endpoints are private by default and take the same Hugging Face token as a bearer

## Questions

### Which is better for AI agents, GPUsMarket or Hugging Face Inference Endpoints?

Hugging Face Inference Endpoints scores 66.7 (B) on agent readiness against GPUsMarket's 39.6 (E), and leads in 6 of 7 scored categories. GPUsMarket leads on payments & pricing.

### Do GPUsMarket and Hugging Face Inference Endpoints need an API key?

GPUsMarket needs an API key. Hugging Face Inference Endpoints takes an API key or an OAuth sign-in.

### Can an agent call GPUsMarket and Hugging Face Inference Endpoints without installing anything?

Yes. GPUsMarket has a hosted endpoint at https://gpusmarket.com/api/v1 and Hugging Face Inference Endpoints at https://api.endpoints.huggingface.cloud.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/gpusmarket-vs-hugging-face-inference-endpoints.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gpusmarket-vs-hugging-face-inference-endpoints.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "gpusmarket", "b": "hugging-face-inference-endpoints"}`. From a terminal: `anchor compare gpusmarket hugging-face-inference-endpoints`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gpusmarket.json and https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-endpoints.json

## Other comparisons with GPUsMarket or Hugging Face Inference Endpoints

- [Baseten vs GPUsMarket](https://www.anchorterminal.com/compare/baseten-vs-gpusmarket.md)
- [Baseten vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/baseten-vs-hugging-face-inference-endpoints.md)
- [Beam vs GPUsMarket](https://www.anchorterminal.com/compare/beam-vs-gpusmarket.md)
- [Beam vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/beam-vs-hugging-face-inference-endpoints.md)
- [Cerebrium vs GPUsMarket](https://www.anchorterminal.com/compare/cerebrium-vs-gpusmarket.md)
- [Cerebrium vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/cerebrium-vs-hugging-face-inference-endpoints.md)
- [Cloud Run GPUs vs GPUsMarket](https://www.anchorterminal.com/compare/cloud-run-gpus-vs-gpusmarket.md)
- [Cloud Run GPUs vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/cloud-run-gpus-vs-hugging-face-inference-endpoints.md)
- [CoreWeave vs GPUsMarket](https://www.anchorterminal.com/compare/coreweave-vs-gpusmarket.md)
- [CoreWeave vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/coreweave-vs-hugging-face-inference-endpoints.md)
- [Crusoe Cloud vs GPUsMarket](https://www.anchorterminal.com/compare/crusoe-cloud-vs-gpusmarket.md)
- [Crusoe Cloud vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/crusoe-cloud-vs-hugging-face-inference-endpoints.md)
- [GPUsMarket vs Hyperbolic](https://www.anchorterminal.com/compare/gpusmarket-vs-hyperbolic.md)
- [GPUsMarket vs Koyeb](https://www.anchorterminal.com/compare/gpusmarket-vs-koyeb.md)
- [GPUsMarket vs Lambda Cloud](https://www.anchorterminal.com/compare/gpusmarket-vs-lambda.md)
- [GPUsMarket vs Massed Compute](https://www.anchorterminal.com/compare/gpusmarket-vs-massed-compute.md)
- [GPUsMarket vs Modal](https://www.anchorterminal.com/compare/gpusmarket-vs-modal.md)
- [GPUsMarket vs Nebius AI Cloud](https://www.anchorterminal.com/compare/gpusmarket-vs-nebius-ai-cloud.md)
- [GPUsMarket vs Northflank](https://www.anchorterminal.com/compare/gpusmarket-vs-northflank.md)
- [GPUsMarket vs Replicate Deployments](https://www.anchorterminal.com/compare/gpusmarket-vs-replicate-deploy.md)
- [GPUsMarket vs Runpod](https://www.anchorterminal.com/compare/gpusmarket-vs-runpod.md)
- [GPUsMarket vs Thunder Compute](https://www.anchorterminal.com/compare/gpusmarket-vs-thunder-compute.md)
- [GPUsMarket vs Together GPU Clusters](https://www.anchorterminal.com/compare/gpusmarket-vs-together-gpu-clusters.md)
- [GPUsMarket vs Vast.ai](https://www.anchorterminal.com/compare/gpusmarket-vs-vast-ai.md)
- [GPUsMarket vs Verda](https://www.anchorterminal.com/compare/gpusmarket-vs-verda.md)
- [Hugging Face Inference Endpoints vs Hyperbolic](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-hyperbolic.md)
- [Hugging Face Inference Endpoints vs Koyeb](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-koyeb.md)
- [Hugging Face Inference Endpoints vs Lambda Cloud](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-lambda.md)
- [Hugging Face Inference Endpoints vs Massed Compute](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-massed-compute.md)
- [Hugging Face Inference Endpoints vs Modal](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-modal.md)
- [Hugging Face Inference Endpoints vs Nebius AI Cloud](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-nebius-ai-cloud.md)
- [Hugging Face Inference Endpoints vs Northflank](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-northflank.md)
- [Hugging Face Inference Endpoints vs Replicate Deployments](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-replicate-deploy.md)
- [Hugging Face Inference Endpoints vs Runpod](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-runpod.md)
- [Hugging Face Inference Endpoints vs Thunder Compute](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-thunder-compute.md)
- [Hugging Face Inference Endpoints vs Together GPU Clusters](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-together-gpu-clusters.md)
- [Hugging Face Inference Endpoints vs Vast.ai](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-vast-ai.md)
- [Hugging Face Inference Endpoints vs Verda](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-verda.md)

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