Speka API — live system status

What does this page show?

Speka is an AI API gateway that gives developers a single endpoint to access frontier models — chat completions, text embeddings, and image generation. This page is generated from real health checks: each model is called with an actual inference request on a schedule, and what you see below is the result of the most recent one.

Partial outage

Last check 11 min ago
Models running
20/23
1 degraded · 2 unavailable
Health-check success rate
87.12%
12,424 live checks recorded
Median response
573ms
across models that are up
Chat completions18 modelsDegraded
Embeddings4 modelsOperational
Image generation1 modelOperational

Model availability

Verified by calling each model for real — not by reading a vendor list.

GLM 5.2
z-ai/glm-5.2
Running· verified 11 min ago · 4493ms
Llama 3.1 8B Instruct
meta/llama-3.1-8b-instruct
Running· verified 11 min ago · 202ms
Llama 3.2 3B Instruct
meta/llama-3.2-3b-instruct
Running· verified 11 min ago · 160ms
Llama 3.3 70B Instruct
meta/llama-3.3-70b-instruct
Unavailable· verified 11 min ago
MiniMax M3
minimaxai/minimax-m3
Running· verified 11 min ago · 243ms
Mistral Nemotron
mistralai/mistral-nemotron
Running· verified 11 min ago · 735ms
Nemotron 3 Ultra 550B
nvidia/nemotron-3-ultra-550b-a55b
Running· verified 11 min ago · 971ms
Step 3.7 Flash
stepfun-ai/step-3.7-flash
Running· verified 11 min ago · 410ms
GPT-OSS 20B
openai/gpt-oss-20b
Running· verified 11 min ago · 365ms
Laguna XS 2.1
poolside/laguna-xs-2.1
Unavailable· verified 11 min ago
Llama Nemotron Embed 1B v2
nvidia/llama-nemotron-embed-1b-v2
Running· verified 11 min ago · 5858ms
Nemotron 3 Embed 1B
nvidia/nemotron-3-embed-1b
Running· verified 11 min ago · 217ms
NV-Embed v1
nvidia/nv-embed-v1
Running· verified 11 min ago · 247ms
NV-EmbedQA E5 v5
nvidia/nv-embedqa-e5-v5
Running· verified 11 min ago · 225ms
FLUX.1 [dev]
black-forest-labs/flux.1-dev
Running· verified 4h ago · 2689ms
Inkling
thinkingmachines/inkling
Running· verified 11 min ago · 573ms
Nemotron 3 Nano 30B
nvidia/nemotron-3-nano-30b-a3b
Running· verified 11 min ago · 677ms
Nemotron 3 Super 120B
nvidia/nemotron-3-super-120b-a12b
Running· verified 11 min ago · 725ms
Nemotron Nano 9B
nvidia/nvidia-nemotron-nano-9b-v2
Running· verified 11 min ago · 665ms
Nemotron Super 49B
nvidia/llama-3.3-nemotron-super-49b-v1.5
Running· verified 11 min ago · 3360ms
Llama 3.2 11B Vision
meta/llama-3.2-11b-vision-instruct
Running· verified 11 min ago · 282ms
Llama 3.2 90B Vision
meta/llama-3.2-90b-vision-instruct
Degraded· verified 11 min ago
Nemotron Nano 12B VL
nvidia/nemotron-nano-12b-v2-vl
Running· verified 11 min ago · 196ms

Models that fail their live checks are removed from the public catalog automatically and restored when they recover. Machine-readable status is available on GET speka.me/v1/models.

FAQ

Frequently asked questions about Speka's reliability

When Speka's API gateway shows 'Operational,' all requests are routing normally across chat completions, embeddings, and image generation endpoints, and response times are within expected ranges. A status of 'Degraded' means elevated latency or partial errors — retry with exponential backoff. 'Outage' means the endpoint is unreachable and the team is actively investigating.
Speka does not rely on the upstream provider's model listing — a listed model can still fail on inference. Instead, every model in the catalog is probed on a schedule with a real request: a short chat completion, an embedding call, or a small image generation. The result (HTTP status, response time, and returned content) is what drives the status shown on this page, and models that fail repeatedly are removed from the public catalog automatically until they recover.
A 503 response means the service is temporarily unavailable. Implement exponential backoff — start at one second and double up to 30 seconds maximum — and retry the request. Check this status page for the current component health; most incidents resolve within minutes of detection. If a specific model shows as unavailable here, switch to another model with the same capability — your API key and base URL stay the same.
Chat completions accept a conversation thread and return a generated text response — used for dialogue, summarization, and instruction-following. Embeddings accept text and return a dense numeric vector used for semantic search, similarity ranking, and retrieval-augmented generation (RAG). The two serve different model types and are tracked separately on the status page.