Research / developmentPrivateHigh confidence

Albert API

Operated by DINUM, French Government

No-cost research and development inference across 10 models; not unrestricted production use.

Visit provider
Free accessResearch / development
Payment cardUnknown
AccountRequired
Sources7 first-party links
API endpointhttps://albert.api.etalab.gouv.fr/v1

Models mentioned

10
openai/gpt-oss-120bmistralai/Mistral-Small-3.2-24B-Instruct-2506mistralai/Ministral-3-8B-Instruct-2512Qwen/Qwen3-Coder-30B-A3B-Instructdeepseek-ai/DeepSeek-V4-Flashopenai/whisper-large-v3BAAI/bge-m3Qwen/Qwen3-VL-Embedding-8BBAAI/bge-reranker-v2-m3lightonai/LightOnOCR-2-1B

Equivalent paid value

At least $6.62/mo
Daily$0.22
Weekly$1.52
Monthly$6.62
One-timeNot available

How this was valued: GPT-OSS-120B's 1.28M-token daily shared envelope is assigned entirely to the more expensive exact-model output direction at $0.17/M. Other Albert models and the unlimited test route are excluded.

Limits and terms

Vector Storage Tokens
300,000
Experiment Model Limits
Id
openai/gpt-oss-120b
RPM
10
Rpd
1,000
TPM
128,000
TPD
1,280,000
Id
mistralai/Mistral-Small-3.2-24B-Instruct-2506
RPM
50
Rpd
1,000
TPM
128,000
TPD
2,460,000
Id
mistralai/Ministral-3-8B-Instruct-2512
RPM
50
Rpd
1,000
TPM
128,000
TPD
2,460,000
Id
Qwen/Qwen3-Coder-30B-A3B-Instruct
RPM
50
Rpd
1,000
TPM
128,000
TPD
2,460,000
Id
deepseek-ai/DeepSeek-V4-Flash
RPM
50
Rpd
unlimited
TPM
246,000
TPD
unlimited
Id
openai/whisper-large-v3
RPM
50
Rpd
1,000
Id
BAAI/bge-m3
RPM
500
Rpd
50,000
Id
Qwen/Qwen3-VL-Embedding-8B
RPM
50
Rpd
1,000
Id
BAAI/bge-reranker-v2-m3
RPM
500
Rpd
50,000
Id
lightonai/LightOnOCR-2-1B
RPM
50
Rpd
1,000
TPM
128,000
TPD
2,460,000

What happens to your prompts?

PrivateReviewed

Albert says conversation traces are not retained, request data is not sent to model vendors, and data is not used for vendor training on its sovereign self-hosted stack.

Plan Scope
Albert experimental access on sovereign self-hosted routes for eligible French central-government users.
Prompt Retention
DINUM says no conversation traces are retained and request data is not sent to the Internet.
Response Retention
Conversation traces encompassing exchanges are not retained.
Ordinary Logging
Non-content request/account metadata fields and retention are not separately enumerated.
Model Training
User data is neither sent to model vendors nor used for their model training.
Product Improvement
No content-based improvement right is disclosed.
Human Or Operator Access
Persistent review is constrained by the no-trace statement; transient operational access is not described.
Subprocessors And Routing
Models run on sovereign SecNumCloud-qualified Outscale infrastructure in France and data is not sent to model vendors.
Deletion Controls
No ordinary conversation copy should remain; metadata deletion controls are not documented.

No provider terms or privacy-policy link is captured in this snapshot. Review the provider’s current legal documents before sending sensitive data.

Eligibility

Account Required
Yes
Eligible Users
French central-government civil servants
Territorial Or Local Authorities Eligible
No
Production Access
Partner or supported project; cofunding may apply.

Primary sources

7

Before you build with Albert API

Read the classification narrowly

This record has current first-party evidence for some zero-cost hosted inference. The label describes the bounded offer supported by evidence on 2026-09-19; it does not guarantee permanence, production suitability, uptime, latency, model quality, or access from every region.

Resolve the live model route

This snapshot records 10 model IDs. Match the exact ID against the provider's live catalog before using it in code; zero-price routes and aliases can rotate while an older documentation page remains online. The recorded base endpoint is https://albert.api.etalab.gouv.fr/v1, but the provider's current API reference remains authoritative for paths, authentication, and request shape.

Confirm account and billing boundaries

An account is required, so public catalog evidence cannot by itself prove the limits, balance, or billing behavior attached to your workspace. The payment-card requirement is conditional or not clearly documented. Treat signup friction and billing exposure as unresolved until the account flow confirms them. The equivalent paid value shown here prices a documented allowance where possible; it is not cash, guaranteed savings, or protection from overage.

Re-read the prompt policy for your plan

This record classifies the reviewed handling as “Private”: Albert says conversation traces are not retained, request data is not sent to model vendors, and data is not used for vendor training on its sovereign self-hosted stack. Provider policies can distinguish free, paid, enterprise, opted-in, and feature-specific traffic, so verify the governing terms for the exact account and route that will receive your data.

Follow the evidence, then re-check it

The record links 7 first-party sources covering the offer, catalog, limits, pricing, terms, privacy, or adoption evidence available to the audit. Prefer the newest governing document or live catalog when sources disagree, and submit a correction when a provider changes a material term.

Match the quota to the workload shape

Translate the published allowance into the traffic pattern you actually expect instead of comparing headline totals alone. A daily token pool can look generous while a low requests-per-minute or concurrency ceiling blocks interactive bursts; a high request limit can still fail a long-context job when input, output, or per-request tokens are capped. Separate prompt tokens from generated tokens, include retries and tool calls, and test the largest realistic payload. If the provider documents more than one limit window, the tightest window at your peak load is the practical ceiling. Research, experimental, and community access can also carry eligibility or fair-use constraints that cannot be modeled as a simple number.

Plan fallback without changing the rules

A fallback should preserve more than API syntax. Confirm that the substitute route supports the required modality, context length, streaming behavior, structured output, tools, and safety controls, then compare its prompt-retention and training terms. An OpenAI-compatible request shape does not make providers operationally or contractually equivalent. Decide which errors may trigger a retry, cap retry storms, and prevent an exhausted free route from silently switching to a billable model. If deterministic output matters, record the model revision and sampling settings; rotating aliases and free-model pools can change behavior even when the endpoint remains available.

Monitor the offer as a dependency

Capture the model ID, response model field, rate-limit headers, usage fields, latency, HTTP status, and any provider request identifier for each test. Watch for authorization failures, quota exhaustion, catalog removal, policy revisions, and dashboard balance changes as separate failure modes. Re-check the provider’s live catalog and governing pages on a schedule proportionate to the workload’s importance, and keep the dated sources that supported your decision. Free capacity is especially suitable for prototypes, evaluations, fallbacks, and bounded workloads when the application can tolerate change; a production dependency still needs observability, an exit path, and an owner responsible for re-verification.

Test one complete request before scaling

Start with the smallest permitted request using the exact credential, model ID, endpoint, and account type you intend to deploy. Record the HTTP status, response headers, usage fields, latency, and any dashboard balance change. Then exercise the failure path: an invalid model, an exhausted quota, or a rate-limit response should fail clearly without silently switching to a paid route. If the provider supports streaming or tool calls, validate those features separately because a free model can expose a narrower capability set than its paid counterpart. Keep a budget ceiling outside the application whenever billing is possible, and avoid sending sensitive data until the observed route matches the reviewed data agreement.