# Hugging Face Inference Providers vs SambaCloud

> SambaCloud scores 64.9 (B) to Hugging Face Inference Providers's 54 (C) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-sambanova
- Markdown: https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-sambanova.md (~6,800 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

SambaCloud scores 64.9 (B) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 5 of 7 scored categories. Hugging Face Inference Providers leads on security & auth. Both do llm inference.

- Hugging Face Inference Providers: grade C, 54/100, rank #926 of 1510. Markdown https://www.anchorterminal.com/tools/hugging-face-inference-providers.md · JSON https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-providers.json
- SambaCloud: grade B, 64.9/100, rank #446 of 1510. Markdown https://www.anchorterminal.com/tools/sambanova.md · JSON https://www.anchorterminal.com/api/v1/tools/sambanova.json
- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md
- All 830 models comparisons: https://www.anchorterminal.com/compare/inference/index.md

## Which one, for what

### Hugging Face Inference Providers (C)

Good for: Agents and developers who want open-weight models from several hosts on one token and one bill, with a public price and capability list per provider.

Ahead on:
- Security & auth, 79 against 61

Also in its favour:
- No incidents deducted, where SambaCloud loses 5 points for them

Watch for: No rate limits, 429 behaviour or error responses documented for the router

### SambaCloud (B)

Good for: Agents that want open-weight models behind an OpenAI or Anthropic client with a free start and prices an agent can read from the API.

Ahead on:
- Reliability, 85 against 25
- Schema & documentation, 81 against 62
- Agent ergonomics, 67 against 58
- Payments & pricing, 40 against 20

Also in its favour:
- Free to start without a card

Watch for: Production models get a notice of two to three weeks, and 13 model ids were removed between 9 March and 9 June 2026


## Why the edge

### Reliability: SambaCloud +60

- Hugging Face Inference Providers (25): Hosted lines. status.huggingface.co is a Better Stack page with 90-day component history for the Hub, Inference Endpoints, Spaces, the CDNs and Jobs, but no component for Inference Providers or the router (10 of 20). With no component, there is no readable incident history for the surface agents call, and the feed's 23 items from 10 June to 7 October 2026 don't name it (5). No rate limits for the router were found; the Hub rate-limits page gives numbers for Hub APIs, resolvers and pages only (0). No 429 or overload guidance for the router was found (0). No SLA found (0). Chat completions on the router is generally available; the Responses API is labelled beta (10). Routing between providers with `:fastest` or `:cheapest` softens a single provider's outage, which this checklist doesn't score.
- SambaCloud (85): Hosted reading. Status page at status.sambanova.ai on Statuspage, with components for the API gateway, the Playground and each model, read from the page itself on 1 November (20). Its history.atom feed, read on 1 November (the 8 October reading came from the /api/ path, which robots.txt disallows, and is struck), has nothing newer than an 8-minute Playground login fault on 25 June 2026, so nothing is posted for the window from 3 August (30). Limits published per model and tier, 20 requests a minute and 20 a day on the free tier, 60 and 12,000 on the Developer tier, per the 8 October check, not re-read on 1 November (15). `x-ratelimit-*` headers on every response, the error table says to retry `queue_full` after a delay, and the SDKs retry 429 and server errors twice with backoff, per the 8 October check. No `Retry-After` header was found in the docs or the OpenAPI document (10 of 15). No SLA found on the legal page, re-read on 1 November, or in the terms (0). Three production models are generally available, the rest previews, per the 8 October check (10). 20+30+15+10+0+10 = 85.

### Payments & pricing: SambaCloud +20

- Hugging Face Inference Providers (20): No x402, MPP or L402 (0). Per-token prices for every model and provider published without a login in the router's /v1/models and on model pages (20). No free tier since 7 October 2026, when free users lost their included monthly credits; PRO's $2.00 of credits needs a subscription (0). Sign-up, token creation and credit purchase are browser steps (0).
- SambaCloud (40): No machine payment protocol (0). Per-token prices on the pricing page, read without a login on 1 November, such as gpt-oss-120b at $0.22 in and $0.59 out per 1M tokens (20). Free tier with no payment method, per the 8 October check (20). A person signs up in the console to get a key (0).

### Schema & documentation: SambaCloud +19

- Hugging Face Inference Providers (62): No OpenAPI document for the router (openapi.json paths answer 404). The task reference pages are generated from typed JSON Schema specs in huggingface.js, and the router's /v1/models gives a machine-readable catalogue, so 12 of 25. llms.txt for the Inference Providers docs and a Markdown twin of every page via `.md` (10). Guides say what each task and policy is for, with a quick setup page for coding agents (14 of 20). Parameter tables with types for chat completion, though `response_format` and `tool_choice` show as unknown types (9 of 15). Examples in Python, JavaScript and curl on every task page, but no documented error responses for the router (9 of 15). No changelog of its own; the Hub changelog doesn't cover it and dated changes are only in the hub-docs history (8 of 15).
- SambaCloud (81): Public OpenAPI 3.1.1 document, still labelled version 1.2.0 though its content changed on 27 October 2026, with 10 operations and 165 schemas (25). `llms.txt` at docs.sambanova.ai/docs/llms.txt and a Markdown copy of each page, per the 8 October check (docs.sambanova.ai answered robots.txt with a bot check on 1 November, so it wasn't read) (10). 718 descriptions in the document, with pages for function calling, Responses, Messages and caching. When not to use a route is rarely stated (15 of 20). Typed parameters with 150 enums, and request bodies now declare `additionalProperties: false`, but JSON schema output is best effort and `strict: true` has no effect (10 of 15). Code examples in Python and TypeScript, and an errors page with 13 codes and a recovery suggestion for each, per the 8 October check (13 of 15). The spec is versioned in its repository, but the version label didn't move with the 27 October changes, the newest SambaCloud release note seen is 7 July 2026, and the models page disagreed with `/v1/models` on 8 October (8 of 15). 25+10+15+10+13+8 = 81.

### Security & auth: Hugging Face Inference Providers +18

- Hugging Face Inference Providers (79): Model reading. Fine-grained user access tokens that can be limited to the `Make calls to Inference Providers` permission, rotated and revoked, plus a public revocation endpoint for leaked tokens, and organisation approval of fine-grained tokens on paid plans (30). Hugging Face says it doesn't store user data for training, but data handling past the router follows each provider's policy, with no per-request filter to exclude providers that train or retain (12 of 20). Request bodies and responses aren't stored when routed and debug logs are kept up to 30 days without user data or tokens, with provider retention outside that statement (10 of 15). Usage by model and provider in account settings, an Enterprise usage API, and Team and Enterprise admins can disable providers and set a spending limit (13 of 15). SOC 2 Type 2 for the Hub, of which the docs say Inference Providers is a feature, and security.txt valid to 2030 per the Inference Endpoints check; no bug bounty found (14 of 20).
- SambaCloud (61): Model reading. Bearer keys from the console, up to 25 per user and shown once. No scopes, project limits or rotation guidance were found, and the key travels in a header, never in the URL (18 of 30). The terms let SambaNova access, store and process Customer Content solely to supply the service and for no other purposes, which rules out training without naming it (18 of 20). The DPA's Annex I, read on 1 November, keeps prompts, inputs and completions no more than 30 days for security, fraud and abuse monitoring. No zero-retention option was found in the pages read, and the product page says SambaCloud never sees or collects prompts, against that retention and terms that grant a right to store content and to use query logs (10 of 15, between deepseek-api's 5 and siliconflow's 6 with no period stated and the 15 groq, mistral-api and xai-api take for 30 days with a zero-retention route). The console has a Usage page. No request logs or audit log were found in the docs (5 of 15). The trust centre states SOC 2 Type 2 and ISO 27001. No security.txt, disclosure policy or bug bounty was found, and the SDK's SECURITY.md sends service reports to a general address (10 of 20).

### Agent ergonomics: SambaCloud +9

- Hugging Face Inference Providers (58): Router reading of the model checklist (tool use, structured output, caching, context, batch, SDKs, errors), as for openrouter. Tool calling through the OpenAI-compatible API with `tool_choice`, support flagged per provider in /v1/models (15 of 20). Structured output documented, support flagged per provider and false on some (10 of 15). No prompt caching guidance found, though the Enterprise usage API counts cached input tokens (3 of 15). Routes to models with up to 1,048,576 tokens of context per the model list, a judgement call since a router has no default model (15). No batch API (0 of 10). Official clients in Python and JavaScript, plus any OpenAI SDK (10). Errors not documented (5 of 15).
- SambaCloud (67): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Function calling with `tool_choice` to force a function, on six listed models, and a July 2026 fix for tool calls that were buffered when streaming (17 of 20). `json_object` and `json_schema` output, best effort only, with a known failure on DeepSeek-V3.2 recorded in July 2026 (8 of 15). Automatic prompt caching on the MiniMax models only, with cached input on MiniMax-M3.1-Flash at a tenth of the input price on the 1 November pricing page, a 4,096-token minimum and no guaranteed persistence (10 of 15). 131,072-token context on four of six models, 1M on the MiniMax-M3 preview, and output capped at 7,168 tokens on DeepSeek and 3,072 on Llama 3.3 70B (8 of 15). No batch API found in the docs index or the OpenAPI document (0 of 10). Official SDKs for Python and TypeScript, and the OpenAI and Anthropic clients work with a changed base URL (10). Errors carry `type`, `param`, `code` and `request_id` (14 of 15).

## Score by category

| Category | Weight | Hugging Face Inference Providers | SambaCloud | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 25 | 85 | SambaCloud +60 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 62 | 81 | SambaCloud +19 |
| Agent ergonomics | 13% (16.2 this run) | 58 | 67 | SambaCloud +9 |
| Security & auth | 14% (17.5 this run) | 79 | 61 | Hugging Face Inference Providers +18 |
| Payments & pricing | 10% (12.5 this run) | 20 | 40 | SambaCloud +20 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 80 | 77 | Hugging Face Inference Providers +3 |
| Transparency & trust | 7% (8.8 this run) | 71 | 73 | SambaCloud +2 |
| Negative events | ≤15 | 0 | -5 | |
| **Total** | | **54 · C** | **64.9 · B** | |

## Facts side by side

| Fact | Hugging Face Inference Providers | SambaCloud |
| --- | --- | --- |
| Kind | Model router | Model API |
| Vendor | Hugging Face, Inc. | SambaNova Systems, Inc. |
| Hosted endpoint | `https://router.huggingface.co/v1` | `https://api.sambanova.ai/v1` |
| Transports | HTTP | HTTP |
| Auth | API key | API key |
| Pricing | Pay per use | Freemium |
| x402 | no | no |
| Licence | Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT | Proprietary service under the SambaCloud Terms of Service. The SDKs and the OpenAPI document are Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-10-29 | 2026-10-27 |
| Terms last updated | 2022-09-15 | no date given |
| Privacy policy last updated | 2023-03-28 | 2023-05-27 |
| 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 | yes |
| Terms or service can change without notice | yes | not found in the text |
| Arbitration or class-action waiver | not found in the text | not found in the text |
| Popularity | 483k npm/wk, 71.5M PyPI/wk | 2 stars, 76 npm/wk, 6.1k PyPI/wk |
| Agent reviews | none | 3.5/5 (4) |

## How the scores have moved

### Hugging Face Inference Providers

No score change since it was listed.

### SambaCloud

- -1.5 on 1 November 2026: new evidence, negative event
- -0.1 on 28 October 2026: correction
- +0.1 on 27 October 2026: checklist

## Verdicts

**Hugging Face Inference Providers.** One Hugging Face token reaches open models on 18 partner providers at the providers' own prices, with a public model list that shows each provider's price, context and tool support. Router rate limits, error responses and its own status component were not found in the reviewed documentation, and free accounts have had no included credits since 7 October 2026.

**SambaCloud.** Per-token prices are readable without a login, a free tier needs no card, and no incident has been posted since 25 June 2026. A Data Processing Addendum now names 24 sub-processors. Production models get two to three weeks' notice before removal, 13 model ids left between March and June 2026, and the product page's privacy claim contradicts the terms.

## Before you call either

### Hugging Face Inference Providers

1. Read https://router.huggingface.co/v1/models before choosing a provider; it shows price, context and `supports_tools` per provider
2. Pin a provider with `model:<provider>` when tool calling or structured output matters, since support varies by provider
3. Use a fine-grained token with only the Inference Providers permission, and send `X-HF-Bill-To` to bill an organisation
4. Back off on 429 without assuming a Retry-After header, since none is documented for the router

### SambaCloud

1. Call `GET https://api.sambanova.ai/v1/models` at start-up and use only ids it returns. The docs and status page have named models the API no longer serves
2. Read `x-ratelimit-remaining-requests` and `x-ratelimit-remaining-requests-day` on every response. The free tier allows 20 requests a day per model
3. Treat 429 `queue_full` and 503 `maintenance` as retryable after a delay, and 410 `model_deprecated` as a signal to change model
4. Validate JSON output yourself. Schema enforcement is best effort and `strict: true` changes nothing
5. Drop `do_sample` before moving to Python SDK 1.14.0 or TypeScript 1.11.0. Those releases removed it

## Questions

### Which is better for AI agents, Hugging Face Inference Providers or SambaCloud?

SambaCloud scores 64.9 (B) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 5 of 7 scored categories. Hugging Face Inference Providers leads on security & auth.

### Do Hugging Face Inference Providers and SambaCloud need an API key?

Both need an API key.

### Can an agent call Hugging Face Inference Providers and SambaCloud without installing anything?

Yes. Hugging Face Inference Providers has a hosted endpoint at https://router.huggingface.co/v1 and SambaCloud at https://api.sambanova.ai/v1.


## For agents

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

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- [Hugging Face Inference Providers vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-nemotron-3-5-super-vl.md)
- [Hugging Face Inference Providers vs Prism Inference](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-prism-inference.md)
- [Nemotron 3.5 Super VL vs SambaCloud](https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-sambanova.md)
- [Prism Inference vs SambaCloud](https://www.anchorterminal.com/compare/prism-inference-vs-sambanova.md)

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